diff --git a/f22/meena_lec_notes/lec-12/project.py b/f22/meena_lec_notes/lec-12/project.py
index 1689e4461f9cd30e83c6084431577d9ea99e3dae..ad671f7760f3b5b7b348e0d7226edbbe5dc777c0 100644
--- a/f22/meena_lec_notes/lec-12/project.py
+++ b/f22/meena_lec_notes/lec-12/project.py
@@ -5,7 +5,7 @@ def __init__():
     import csv
     """This function will read in the csv_file and store it in a list of dictionaries"""
     __student__.clear()
-    with open('cs220_survey_data.csv', mode='r') as csv_file:
+    with open('cs220_survey_data.csv', mode='r', encoding='utf-8') as csv_file:
         csv_reader = csv.DictReader(csv_file)
         for row in csv_reader:
             __student__.append(row)
diff --git a/f22/meena_lec_notes/lec-14/.ipynb_checkpoints/lec_14_lists-checkpoint.ipynb b/f22/meena_lec_notes/lec-14/.ipynb_checkpoints/lec_14_lists-checkpoint.ipynb
deleted file mode 100644
index 39feb84f270e81c03729b52ccc651dab8bcafeeb..0000000000000000000000000000000000000000
--- a/f22/meena_lec_notes/lec-14/.ipynb_checkpoints/lec_14_lists-checkpoint.ipynb
+++ /dev/null
@@ -1,1399 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Lists"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import project"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Sequence\n",
-    "\n",
-    "- Definition: a sequence is a collection of numbered/ordered values\n",
-    "- String: a sequence of one-character strings\n",
-    "\n",
-    "Operations:\n",
-    "- `len`\n",
-    "- indexing\n",
-    "- slicing\n",
-    "- `for` loop"
-   ]
-  },
-  {
-   "attachments": {
-    "Strings-2.png": {
-     "image/png": 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"
-    }
-   },
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<div>\n",
-    "<img src=\"attachment:Strings-2.png\" width=\"600\"/>\n",
-    "</div>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Indexing\n",
-    "\n",
-    "- enables you to extract one item in your sequence, that is one character in a string\n",
-    "- Syntax: string_var`[index]`\n",
-    "    - index needs to be in range, that is from `0` to `len(string_var) - 1`\n",
-    "    - other index values will produce `IndexError`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Monday\n",
-      "o\n",
-      "y\n",
-      "y\n",
-      "a\n"
-     ]
-    },
-    {
-     "ename": "IndexError",
-     "evalue": "string index out of range",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/677413304.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mday\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# last\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mday\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# 2nd last\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mday\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m50\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# this won't work\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mIndexError\u001b[0m: string index out of range"
-     ]
-    }
-   ],
-   "source": [
-    "day = \"Monday\"\n",
-    "print(day)\n",
-    "print(day[1])  # 2nd character\n",
-    "print(day[5])  # last\n",
-    "\n",
-    "print(day[-1]) # last\n",
-    "print(day[-2]) # 2nd last\n",
-    "print(day[50]) # this won't work"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Slicing\n",
-    "- enables you to extract a sub-sequence\n",
-    "- sub-sequence will be of same type as original sequence\n",
-    "- Syntax: string_var`[start_index:end_indx]`\n",
-    "    - start_index is inclusive\n",
-    "    - end_index is exclusive\n",
-    "    - index need not be in range. Slicing will ignore indices which are not in range of `0` to `len(string_var) - 1`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Monday\n",
-      "on\n",
-      "onday\n",
-      "onday\n",
-      "Mon\n",
-      "Monday\n",
-      "da\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(day)\n",
-    "print(day[1:3])    # include 1, exclude 3\n",
-    "print(day[1:100])  # slicing is forgiving\n",
-    "print(day[1:])     # can skip 2nd number\n",
-    "print(day[:3])     # can skip 1st number\n",
-    "print(day[:])      # this, too!\n",
-    "print(day[-3:-1])  # can use negative indices"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### for loops\n",
-    "\n",
-    "- can iterate over every item in a sequence"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "M\n",
-      "o\n",
-      "n\n",
-      "d\n",
-      "a\n",
-      "y\n"
-     ]
-    }
-   ],
-   "source": [
-    "# print each letter of the string using while loop\n",
-    "index = 0\n",
-    "while index < len(day):\n",
-    "    print(day[index])\n",
-    "    index += 1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "M\n",
-      "o\n",
-      "n\n",
-      "d\n",
-      "a\n",
-      "y\n"
-     ]
-    }
-   ],
-   "source": [
-    "# print each letter of the string using for loop\n",
-    "# letter is a new variable that is the value of each iteration\n",
-    "\n",
-    "for letter in day:\n",
-    "    print(letter)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'b' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/571427960.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# the 2nd variable must be defined\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;31m# 2nd var b undefined\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'b' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "# the 2nd variable must be defined\n",
-    "# 2nd var b undefined\n",
-    "for a in b: \n",
-    "    print(a)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "M\n",
-      "o\n",
-      "n\n",
-      "d\n",
-      "a\n",
-      "y\n"
-     ]
-    }
-   ],
-   "source": [
-    "# print each letter of the string using for loop with range built-in function call\n",
-    "# range enables us to iterate over every index in the string\n",
-    "\n",
-    "for idx in range(len(day)):\n",
-    "    print(day[idx])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "M\n",
-      "n\n",
-      "a\n"
-     ]
-    }
-   ],
-   "source": [
-    "# range built-in function: an optional 3rd number is the increment\n",
-    "# let's print every other character in the string\n",
-    "for idx in range(0, len(day), 2):  \n",
-    "    print(day[idx])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "NCAA\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Practice: Write a for loop to generate a string that makes an acronym\n",
-    "\n",
-    "phrase = \"National Collegiate Athletic Association 2022\"\n",
-    "acro = \"\"\n",
-    "for letter in phrase:\n",
-    "    if letter.upper() == letter and letter.isalpha():\n",
-    "        #print(letter)\n",
-    "        # How can we make sure you don't consider spaces and numbers?\n",
-    "        # TODO: try isalpha method (update if condition)\n",
-    "        # TODO: now instead of printing the letter, concatenate the letter to acro\n",
-    "        acro += letter\n",
-    "\n",
-    "print(acro)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Other string methods: https://www.w3schools.com/python/python_ref_string.asp. Methods in Python have very intuitive names. Please don't memorize the methods."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Learning Objectives"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "- Create a list and use sequence operations on a list.\n",
-    "- Write loops that process lists\n",
-    "- Explain key differences between strings and lists: type flexibility, mutability\n",
-    "- Mutate a list using:\n",
-    "    - indexing\n",
-    "    - methods such as append, extend, sort, and pop\n",
-    "- split() a string into a list\n",
-    "- join() list elements into a string"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Motivation for lists:\n",
-    "\n",
-    "- what if we want to store a sequence of numbers or a sequence of numbers and strings?\n",
-    "- lists enable us to create flexible sequences: we can store anything inside a list as item, including:\n",
-    "    - int\n",
-    "    - float\n",
-    "    - str\n",
-    "    - bool\n",
-    "    - other lists, etc.,"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "day = \"Monday\"\n",
-    "\n",
-    "# first quotation indicates beginning of string sequence\n",
-    "# second quotation indicates end of string sequence"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "empty_list = []\n",
-    "some_nums = [11, 22, 33, 44]\n",
-    "\n",
-    "# [ indicates beginning of sequence\n",
-    "# ] indicates end of sequence"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "5\n",
-      "broccoli\n",
-      "oranges\n",
-      "['broccoli', 'spinach']\n"
-     ]
-    },
-    {
-     "ename": "IndexError",
-     "evalue": "list index out of range",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/3200803703.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;31m# TODO: discuss why the following gives IndexError\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgrocery_list\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgrocery_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     17\u001b[0m \u001b[0;31m# last possible index is always 1 value lesser than length\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mIndexError\u001b[0m: list index out of range"
-     ]
-    }
-   ],
-   "source": [
-    "grocery_list = [\"apples\", \"milk\", \"broccoli\", \"spinach\", \"oranges\"] \n",
-    "\n",
-    "# TODO: compute length of grocery_list\n",
-    "print(len(grocery_list))\n",
-    "\n",
-    "# TODO: use indexing to display broccoli\n",
-    "print(grocery_list[2])\n",
-    "\n",
-    "# TODO: use indexing to display last item\n",
-    "print(grocery_list[-1])\n",
-    "\n",
-    "# TODO: use slicing to extract only the vegetables\n",
-    "print(grocery_list[2:4])\n",
-    "\n",
-    "# TODO: discuss why the following gives IndexError\n",
-    "print(grocery_list[len(grocery_list)])\n",
-    "# last possible index is always 1 value lesser than length"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "apples purchased!\n",
-      "milk purchased!\n",
-      "broccoli purchased!\n",
-      "spinach purchased!\n",
-      "oranges purchased!\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Iterate over every item in grocery_list to display:\n",
-    "# <Item> purchased!\n",
-    "\n",
-    "for item in grocery_list:\n",
-    "    print(item + \" purchased!\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "110\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Compute sum of numbers in some_nums\n",
-    "# Let's do this example using PythonTutor\n",
-    "\n",
-    "total = 0\n",
-    "\n",
-    "for num in some_nums:\n",
-    "    total += num\n",
-    "    \n",
-    "print(total)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "20"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# We can use a list instead of a variable for each operation\n",
-    "[10, 20, 30][1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[20, 30]"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# We can use a list instead of a variable for each operation\n",
-    "[10, 20, 30][1:]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "How does Python differentiate between two different usages of `[]`?"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Other sequence operations\n",
-    "\n",
-    "- concatentation using `+`\n",
-    "- `in`\n",
-    "- multiply by an `int`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Happy Monday :)\n",
-      "[11, 22, 33, 44, 1, 2, 3]\n"
-     ]
-    }
-   ],
-   "source": [
-    "msg = \"Happy \"\n",
-    "print(msg + \"Monday :)\")\n",
-    "\n",
-    "some_nums = [11, 22, 33, 44]\n",
-    "print(some_nums + [1, 2, 3]) # `+` concatenates two lists"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "True\n",
-      "False\n",
-      "True\n",
-      "False\n"
-     ]
-    }
-   ],
-   "source": [
-    "msg = \"Happy\"\n",
-    "print(\"H\" in msg)\n",
-    "print(\"h\" in msg)\n",
-    "\n",
-    "some_nums = [11, 22, 33, 44]\n",
-    "print(33 in some_nums)\n",
-    "print(55 in some_nums)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Happy :)Happy :)Happy :)\n",
-      "['Go', 'Badgers!', 'Go', 'Badgers!', 'Go', 'Badgers!']\n"
-     ]
-    }
-   ],
-   "source": [
-    "msg = \"Happy :)\"\n",
-    "print(msg * 3)\n",
-    "\n",
-    "print([\"Go\", \"Badgers!\"] * 3)"
-   ]
-  },
-  {
-   "attachments": {
-    "Mutation.png": {
-     "image/png": 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"
-    }
-   },
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Strings versus lists\n",
-    "\n",
-    "<div>\n",
-    "<img src=\"attachment:Mutation.png\" width=\"600\"/>\n",
-    "</div>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Difference 1: lists are flexible"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "hello\n",
-      "14\n",
-      "True\n",
-      "5.678\n",
-      "None\n",
-      "['list', 'inside', 'a', 'list']\n",
-      "['list', 'inside', 'a', 'list']\n",
-      "<class 'list'>\n",
-      "inside\n"
-     ]
-    }
-   ],
-   "source": [
-    "# String sequence can only contain characters as items\n",
-    "# List sequence can contain anything as an item\n",
-    "\n",
-    "l = [\"hello\", 14, True, 5.678, None, [\"list\", \"inside\", \"a\", \"list\"]]\n",
-    "\n",
-    "# TODO: fix the bug in this loop\n",
-    "for i in range(len(l)):\n",
-    "    print(l[i])\n",
-    "    \n",
-    "# TODO: use indexing to extract and print the inner list\n",
-    "print(l[-1])\n",
-    "\n",
-    "# TODO: print type of last item in l\n",
-    "print(type(l[-1]))\n",
-    "\n",
-    "# TODO: use double indexing to extract \"inside\"\n",
-    "print(l[-1][1])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      ".....S\n",
-      ".SSS.S\n",
-      ".....S\n",
-      "......\n",
-      "....S.\n",
-      "....S.\n"
-     ]
-    }
-   ],
-   "source": [
-    "# List of lists usecase example\n",
-    "\n",
-    "game_grid = [\n",
-    "[\".\", \".\", \".\", \".\", \".\", \"S\"],\n",
-    "[\".\", \"S\", \"S\", \"S\", \".\", \"S\"],\n",
-    "[\".\", \".\", \".\", \".\", \".\", \"S\"],\n",
-    "[\".\", \".\", \".\", \".\", \".\", \".\"],\n",
-    "[\".\", \".\", \".\", \".\", \"S\", \".\"],\n",
-    "[\".\", \".\", \".\", \".\", \"S\", \".\"]\n",
-    "]\n",
-    "\n",
-    "for row in game_grid:\n",
-    "    for position in row:\n",
-    "        print(position, end = \"\")\n",
-    "    print()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Difference 2: lists are mutable\n",
-    "\n",
-    "- Mutability has nothing to do with variable assignments / re-assignments\n",
-    "- Mutability has to do with changing values inside a sequence"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "CDE\n",
-      "[3, 4]\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Variables can always be re-assigned\n",
-    "\n",
-    "s = \"AB\"\n",
-    "s = \"CD\"\n",
-    "s += \"E\"\n",
-    "print(s)\n",
-    "\n",
-    "nums = [1, 2]\n",
-    "nums = [3, 4]\n",
-    "print(nums)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "'str' object does not support item assignment",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/719601015.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# TODO: let's try to change \"Andrew\" to \"Andrea\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mname\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"a\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;31m# doesn't work because strings are immutable, that is you cannot change the value inside an existing string\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mTypeError\u001b[0m: 'str' object does not support item assignment"
-     ]
-    }
-   ],
-   "source": [
-    "name = \"Andrew\"\n",
-    "\n",
-    "# TODO: let's try to change \"Andrew\" to \"Andrea\"\n",
-    "name[-1] = \"a\" \n",
-    "\n",
-    "# doesn't work because strings are immutable, that is you cannot change the value inside an existing string"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[2, 2, 0]\n"
-     ]
-    }
-   ],
-   "source": [
-    "nums = [2, 2, 9]\n",
-    "\n",
-    "# TODO: change 9 to 0\n",
-    "nums[2] = 0\n",
-    "print(nums)\n",
-    "\n",
-    "# works because lists are mutable, that is you can change the value inside an existing list"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Mutating a list\n",
-    "\n",
-    "- update using index (works only for existing index)\n",
-    "- `append` method\n",
-    "- `extend` method\n",
-    "- `pop` method\n",
-    "- `sort` method\n",
-    "\n",
-    "Unlike string methods, list methods mutate the original list. String methods produce a new string because strings are immutable."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "IndexError",
-     "evalue": "list assignment index out of range",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/619664973.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# TODO: try to add \"blueberries\" at index 5\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mgrocery_list\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"blueberries\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;31m# doesn't work because grocery_list does not contain a previous item at index 5\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mIndexError\u001b[0m: list assignment index out of range"
-     ]
-    }
-   ],
-   "source": [
-    "grocery_list = [\"apples\", \"milk\", \"broccoli\", \"spinach\", \"oranges\"] \n",
-    "\n",
-    "# TODO: try to add \"blueberries\" at index 5\n",
-    "grocery_list[5] = \"blueberries\" \n",
-    "# doesn't work because grocery_list does not contain a previous item at index 5"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "So, how do we add a new item to a list?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['apples', 'milk', 'broccoli', 'spinach', 'oranges', 'blueberries']\n"
-     ]
-    }
-   ],
-   "source": [
-    "grocery_list.append(\"blueberries\")\n",
-    "print(grocery_list)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Can we add multiple items using `append`?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "list.append() takes exactly one argument (3 given)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/161169733.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mgrocery_list\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"peanut butter\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"jelly\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"bread\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;31m# doesn't work because append only accepts a single argument\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m: list.append() takes exactly one argument (3 given)"
-     ]
-    }
-   ],
-   "source": [
-    "grocery_list.append(\"peanut butter\", \"jelly\", \"bread\")# doesn't work because append only accepts a single argument"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['apples', 'milk', 'broccoli', 'spinach', 'oranges', 'blueberries', ['peanut butter', 'jelly', 'bread']]\n"
-     ]
-    }
-   ],
-   "source": [
-    "grocery_list.append([\"peanut butter\", \"jelly\", \"bread\"])# adds the list argument as such\n",
-    "print(grocery_list)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`extend` method will enable us to add every item in argument list to the original list as individual item."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['apples', 'milk', 'broccoli', 'spinach', 'oranges', 'blueberries', ['peanut butter', 'jelly', 'bread'], 'falafel', 'pita bread', 'hummus']\n"
-     ]
-    }
-   ],
-   "source": [
-    "grocery_list.extend([\"falafel\", \"pita bread\", \"hummus\"])\n",
-    "print(grocery_list)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`pop` enables us to remove item from the list:\n",
-    "\n",
-    "- by default pop() removes the last item from the list\n",
-    "- you can override that by passing an index as argument\n",
-    "- pop remove the item from the original list and also returns it"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'hummus'"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "grocery_list.pop()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['apples',\n",
-       " 'milk',\n",
-       " 'broccoli',\n",
-       " 'spinach',\n",
-       " 'oranges',\n",
-       " 'blueberries',\n",
-       " ['peanut butter', 'jelly', 'bread'],\n",
-       " 'falafel',\n",
-       " 'pita bread']"
-      ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "grocery_list"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "oranges\n",
-      "['apples', 'milk', 'broccoli', 'spinach', 'blueberries', ['peanut butter', 'jelly', 'bread'], 'falafel', 'pita bread']\n"
-     ]
-    }
-   ],
-   "source": [
-    "# TODO: remove \"oranges\" from grocery_list and store it into a variable\n",
-    "some_fruit = grocery_list.pop(4)\n",
-    "print(some_fruit)\n",
-    "print(grocery_list)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`sort` method enables us to sort the list using alphanumeric ordering.\n",
-    "\n",
-    "TODO: Try sorting each of the following lists."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[0, 2, 3, 9, 34, 90]"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "L = [3, 9, 2, 0, 34, 90] # TODO: initialize list with some unordered numbers\n",
-    "L.sort()\n",
-    "L"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['apple', 'hello', 'hi', 'orange', 'world']"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "L = [\"hi\", \"apple\", \"hello\", \"world\", \"orange\"] # TODO: initialize list with some unordered strings\n",
-    "L.sort()\n",
-    "L"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[False, False, True, True, True]"
-      ]
-     },
-     "execution_count": 35,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "L = [False, True, False, True, True]\n",
-    "L.sort()\n",
-    "L"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "'<' not supported between instances of 'int' and 'str'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/4220427818.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mL\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m\"str\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2.0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mL\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Doesn't work as you cannot compare different types!\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m: '<' not supported between instances of 'int' and 'str'"
-     ]
-    }
-   ],
-   "source": [
-    "L = [\"str\", 1, 2.0, False]\n",
-    "L.sort() # Doesn't work as you cannot compare different types!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`split` method splits a string into a list of strings, using a separator (argument)\n",
-    "- Syntax: some_string.split(separator_string)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['a', 'quick', 'brown', 'fox']"
-      ]
-     },
-     "execution_count": 37,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sentence = \"a,quick,brown,fox\"\n",
-    "words = sentence.split(\",\")\n",
-    "words"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`join` method joins a list of strings into a single string using a separator (argument)\n",
-    "- Syntax: separator_string.join(some_list)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'MISSISSIPPI'"
-      ]
-     },
-     "execution_count": 38,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "characters = [\"M\", \"SS\", \"SS\", \"PP\", \"\"]\n",
-    "place = \"I\".join(characters)\n",
-    "place\n",
-    "\n",
-    "# TODO: remove the last item in characters list and see what place you get (re-run cell)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### List all Engineering majors (primary major) among current lecture (example: LEC001) students"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Engineering: Biomedical',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Biomedical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Mechanical']"
-      ]
-     },
-     "execution_count": 39,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "engineering_major_list = []\n",
-    "\n",
-    "for idx in range(project.count()):\n",
-    "    lecture = project.get_lecture(idx)\n",
-    "    major = project.get_primary_major(idx)\n",
-    "    \n",
-    "    if lecture == \"LEC001\":\n",
-    "        if major.startswith(\"Engineering\"):\n",
-    "            engineering_major_list.append(major)\n",
-    "            \n",
-    "engineering_major_list"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Profanity filtering"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'o** the m****** was so awesome!'"
-      ]
-     },
-     "execution_count": 40,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "bad_words = [\"omg\", \"midterm\", \"exam\"]\n",
-    "\n",
-    "def censor(input_string):\n",
-    "    \"\"\"\n",
-    "    replaces every bad word in input string with that word's first\n",
-    "    letter and then * for the remaining characters\n",
-    "    \"\"\"\n",
-    "    # TODO: use split to extract every word \n",
-    "    words = input_string.split(\" \")\n",
-    "\n",
-    "    # Iterate over every word: 1. check if word is in bad_words 2. compute replacement 3. replace word\n",
-    "    for index in range(len(words)):\n",
-    "        curr_word = words[index]\n",
-    "        if curr_word.lower() in bad_words:\n",
-    "            words[index] = curr_word[0] + \"*\" * (len(curr_word) - 1)\n",
-    "    \n",
-    "    # TODO: join the words back using the correct separator and return the joined string\n",
-    "    return \" \".join(words)\n",
-    "    \n",
-    "censor(\"omg the midterm was so awesome!\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Wordle (self-study example)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Welcome to PyWordle!\n",
-      "You have 6 guesses to guess a 5 character word.\n",
-      "X\tThe letter is not in the word.\n",
-      "_\tThe letter is in the word, but in the wrong place.\n",
-      "O\tThe letter is in the correct place!\n",
-      "Guess the word: rance\n",
-      "RANCE\t____O\n",
-      "Guess the word: nacre\n",
-      "NACRE\t____O\n",
-      "Guess the word: crane\n",
-      "CRANE\tOOOOO\n",
-      "You won in 3 guesses!\n"
-     ]
-    }
-   ],
-   "source": [
-    "def get_wordle_results(guess):\n",
-    "    wordle_result = \"\"\n",
-    "    for i in range(len(guess)):\n",
-    "        if guess[i] == word_of_the_day[i]:\n",
-    "            wordle_result += \"O\"\n",
-    "        elif word_of_the_day.find(guess[i]) != -1:\n",
-    "            wordle_result += \"_\"\n",
-    "        else:\n",
-    "            wordle_result += \"X\"\n",
-    "    return wordle_result\n",
-    "\n",
-    "max_num_guesses = 6\n",
-    "current_num_guesses = 1\n",
-    "word_of_the_day = \"CRANE\"\n",
-    "\n",
-    "print(\"Welcome to PyWordle!\")\n",
-    "print(\"You have 6 guesses to guess a 5 character word.\")\n",
-    "print(\"X\\tThe letter is not in the word.\")\n",
-    "print(\"_\\tThe letter is in the word, but in the wrong place.\")\n",
-    "print(\"O\\tThe letter is in the correct place!\")\n",
-    "\n",
-    "while current_num_guesses <= max_num_guesses:\n",
-    "    guess = input(\"Guess the word: \")\n",
-    "    guess = guess.upper()\n",
-    "\n",
-    "    wordle_results = get_wordle_results(guess)\n",
-    "    print(\"{}\\t{}\".format(guess, wordle_results))\n",
-    "    if guess == word_of_the_day:\n",
-    "        break\n",
-    "    current_num_guesses += 1\n",
-    "    \n",
-    "if current_num_guesses > max_num_guesses:\n",
-    "    print(\"Better luck next time!\")\n",
-    "    print(\"The word was: {}\".format(word_of_the_day))\n",
-    "else:\n",
-    "    print(\"You won in {} guesses!\".format(current_num_guesses))"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.7"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/f22/meena_lec_notes/lec-14/.ipynb_checkpoints/lec_14_lists_template-checkpoint.ipynb b/f22/meena_lec_notes/lec-14/.ipynb_checkpoints/lec_14_lists_template-checkpoint.ipynb
deleted file mode 100644
index 01edaa76087499dd816600b07351b59b4a79b4ef..0000000000000000000000000000000000000000
--- a/f22/meena_lec_notes/lec-14/.ipynb_checkpoints/lec_14_lists_template-checkpoint.ipynb
+++ /dev/null
@@ -1,875 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Lists"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import project"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Sequence\n",
-    "\n",
-    "- Definition: a sequence is a collection of numbered/ordered values\n",
-    "- String: a sequence of one-character strings\n",
-    "\n",
-    "Operations:\n",
-    "- `len`\n",
-    "- indexing\n",
-    "- slicing\n",
-    "- `for` loop"
-   ]
-  },
-  {
-   "attachments": {
-    "Strings-2.png": {
-     "image/png": 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"
-    }
-   },
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<div>\n",
-    "<img src=\"attachment:Strings-2.png\" width=\"600\"/>\n",
-    "</div>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Indexing\n",
-    "\n",
-    "- enables you to extract one item in your sequence, that is one character in a string\n",
-    "- Syntax: string_var`[index]`\n",
-    "    - index needs to be in range, that is from `0` to `len(string_var) - 1`\n",
-    "    - other index values will produce `IndexError`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "day = \"Monday\"\n",
-    "print(day)\n",
-    "print(day[1])  # 2nd character\n",
-    "print(day[5])  # last\n",
-    "\n",
-    "print(day[-1]) # last\n",
-    "print(day[-2]) # 2nd last\n",
-    "print(day[50]) # this won't work"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Slicing\n",
-    "- enables you to extract a sub-sequence\n",
-    "- sub-sequence will be of same type as original sequence\n",
-    "- Syntax: string_var`[start_index:end_indx]`\n",
-    "    - start_index is inclusive\n",
-    "    - end_index is exclusive\n",
-    "    - index need not be in range. Slicing will ignore indices which are not in range of `0` to `len(string_var) - 1`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "print(day)\n",
-    "print(day[1:3])    # include 1, exclude 3\n",
-    "print(day[1:100])  # slicing is forgiving\n",
-    "print(day[1:])     # can skip 2nd number\n",
-    "print(day[:3])     # can skip 1st number\n",
-    "print(day[:])      # this, too!\n",
-    "print(day[-3:-1])  # can use negative indices"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### for loops\n",
-    "\n",
-    "- can iterate over every item in a sequence"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# print each letter of the string using while loop\n",
-    "index = 0\n",
-    "while index < len(day):\n",
-    "    print(day[???])\n",
-    "    index += 1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# print each letter of the string using for loop\n",
-    "# letter is a new variable that is the value of each iteration\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# the 2nd variable must be defined\n",
-    "# 2nd var b undefined\n",
-    "for a in b: \n",
-    "    print(a)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# print each letter of the string using for loop with range built-in function call\n",
-    "# range enables us to iterate over every index in the string\n",
-    "\n",
-    "for ??? in range(???):\n",
-    "    print(day[???])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# range built-in function: an optional 3rd number is the increment\n",
-    "# let's print every other character in the string\n",
-    "for idx in range(0, len(day), ???):  \n",
-    "    print(day[idx])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Practice: Write a for loop to generate a string that makes an acronym\n",
-    "\n",
-    "phrase = \"National Collegiate Athletic Association 2022\"\n",
-    "acro = \"\"\n",
-    "for letter in phrase:\n",
-    "    if letter.upper() == letter:\n",
-    "        print(letter)\n",
-    "        # How can we make sure you don't consider spaces and numbers?\n",
-    "        # TODO: try isalpha method (update if condition)\n",
-    "        # TODO: now instead of printing the letter, concatenate the letter to acro\n",
-    "        \n",
-    "        \n",
-    "print(acro)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Other string methods: https://www.w3schools.com/python/python_ref_string.asp. Methods in Python have very intuitive names. Please don't memorize the methods."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Learning Objectives"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "- Create a list and use sequence operations on a list.\n",
-    "- Write loops that process lists\n",
-    "- Explain key differences between strings and lists: type flexibility, mutability\n",
-    "- Mutate a list using:\n",
-    "    - indexing\n",
-    "    - methods such as append, extend, sort, and pop\n",
-    "- split() a string into a list\n",
-    "- join() list elements into a string"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Motivation for lists:\n",
-    "\n",
-    "- what if we want to store a sequence of numbers or a sequence of numbers and strings?\n",
-    "- lists enable us to create flexible sequences: we can store anything inside a list as item, including:\n",
-    "    - int\n",
-    "    - float\n",
-    "    - str\n",
-    "    - bool\n",
-    "    - other lists, etc.,"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "day = \"Monday\"\n",
-    "\n",
-    "# first quotation indicates beginning of string sequence\n",
-    "# second quotation indicates end of string sequence"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "empty_list = None\n",
-    "some_nums = None\n",
-    "\n",
-    "# [ indicates beginning of sequence\n",
-    "# ] indicates end of sequence"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "grocery_list = [\"apples\", \"milk\", \"broccoli\", \"spinach\", \"oranges\"] \n",
-    "\n",
-    "# TODO: compute length of grocery_list\n",
-    "print()\n",
-    "\n",
-    "# TODO: use indexing to display broccoli\n",
-    "print()\n",
-    "\n",
-    "# TODO: use indexing to display last item\n",
-    "print()\n",
-    "\n",
-    "# TODO: use slicing to extract only the vegetables\n",
-    "print()\n",
-    "\n",
-    "# TODO: discuss why the following gives IndexError\n",
-    "print(grocery_list[len(grocery_list)])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Iterate over every item in grocery_list to display:\n",
-    "# <Item> purchased!\n",
-    "\n",
-    "for item in ???:\n",
-    "    print()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Compute sum of numbers in some_nums\n",
-    "# Let's do this example using PythonTutor\n",
-    "\n",
-    "total = 0\n",
-    "\n",
-    "# TODO: for loop to iterate over each number in some_nums\n",
-    "    \n",
-    "print(total)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# We can use a list instead of a variable for each operation\n",
-    "[10, 20, 30][1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# We can use a list instead of a variable for each operation\n",
-    "[10, 20, 30][1:]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "How does Python differentiate between two different usages of `[]`?"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Other sequence operations\n",
-    "\n",
-    "- concatentation using `+`\n",
-    "- `in`\n",
-    "- multiply by an `int`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "msg = \"Happy \"\n",
-    "print(msg + \"Monday :)\")\n",
-    "\n",
-    "some_nums = [11, 22, 33, 44]\n",
-    "print(some_nums + [1, 2, 3]) # `+` concatenates two lists"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "msg = \"Happy\"\n",
-    "print(\"H\" in msg)\n",
-    "print(\"h\" in msg)\n",
-    "\n",
-    "some_nums = [11, 22, 33, 44]\n",
-    "print(33 in some_nums)\n",
-    "print(55 in some_nums)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "msg = \"Happy :)\"\n",
-    "print(msg * 3)\n",
-    "\n",
-    "print([\"Go\", \"Badgers!\"] * 3)"
-   ]
-  },
-  {
-   "attachments": {
-    "Mutation.png": {
-     "image/png": 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"
-    }
-   },
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Strings versus lists\n",
-    "\n",
-    "<div>\n",
-    "<img src=\"attachment:Mutation.png\" width=\"600\"/>\n",
-    "</div>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Difference 1: lists are flexible"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# String sequence can only contain characters as items\n",
-    "# List sequence can contain anything as an item\n",
-    "\n",
-    "l = [\"hello\", 14, True, 5.678, None, [\"list\", \"inside\", \"a\", \"list\"]]\n",
-    "\n",
-    "# TODO: fix the bug in this loop\n",
-    "for i in l:\n",
-    "    print(l[i])\n",
-    "    \n",
-    "# TODO: use indexing to extract and print the inner list\n",
-    "print()\n",
-    "\n",
-    "# TODO: print type of last item in l\n",
-    "print()\n",
-    "\n",
-    "# TODO: use double indexing to extract \"inside\"\n",
-    "print()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# List of lists usecase example\n",
-    "\n",
-    "game_grid = [\n",
-    "[\".\", \".\", \".\", \".\", \".\", \"S\"],\n",
-    "[\".\", \"S\", \"S\", \"S\", \".\", \"S\"],\n",
-    "[\".\", \".\", \".\", \".\", \".\", \"S\"],\n",
-    "[\".\", \".\", \".\", \".\", \".\", \".\"],\n",
-    "[\".\", \".\", \".\", \".\", \"S\", \".\"],\n",
-    "[\".\", \".\", \".\", \".\", \"S\", \".\"]\n",
-    "]\n",
-    "\n",
-    "for row in game_grid:\n",
-    "    for position in row:\n",
-    "        print(position, end = \"\")\n",
-    "    print()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Difference 2: lists are mutable\n",
-    "\n",
-    "- Mutability has nothing to do with variable assignments / re-assignments\n",
-    "- Mutability has to do with changing values inside a sequence"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Variables can always be re-assigned\n",
-    "\n",
-    "s = \"AB\"\n",
-    "s = \"CD\"\n",
-    "s += \"E\"\n",
-    "print(s)\n",
-    "\n",
-    "nums = [1, 2]\n",
-    "nums = [3, 4]\n",
-    "print(nums)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "name = \"Andrew\"\n",
-    "\n",
-    "# TODO: let's try to change \"Andrew\" to \"Andrea\"\n",
-    "\n",
-    "\n",
-    "# doesn't work because strings are immutable, that is you cannot change the value inside an existing string"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "nums = [2, 2, 9]\n",
-    "\n",
-    "# TODO: change 9 to 0\n",
-    "\n",
-    "print(nums)\n",
-    "\n",
-    "# works because lists are mutable, that is you can change the value inside an existing list"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Mutating a list\n",
-    "\n",
-    "- update using index (works only for existing index)\n",
-    "- `append` method\n",
-    "- `extend` method\n",
-    "- `pop` method\n",
-    "- `sort` method\n",
-    "\n",
-    "Unlike string methods, list methods mutate the original list. String methods produce a new string because strings are immutable."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "grocery_list = [\"apples\", \"milk\", \"broccoli\", \"spinach\", \"oranges\"] \n",
-    "\n",
-    "# TODO: try to add \"blueberries\" at index 5\n",
-    "grocery_list[???] = \"blueberries\" \n",
-    "# doesn't work because grocery_list does not contain a previous item at index 5"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "So, how do we add a new item to a list?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "grocery_list.append(\"blueberries\")\n",
-    "print(grocery_list)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Can we add multiple items using `append`?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Let's try to add \"peanut butter\", \"jelly\", \"bread\"\n",
-    "grocery_list.append()# doesn't work because append only accepts a single argument"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "grocery_list.append()# adds the list argument as such\n",
-    "print(grocery_list)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`extend` method will enable us to add every item in argument list to the original list as individual item."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "grocery_list.extend([\"falafel\", \"pita bread\", \"hummus\"])\n",
-    "print(grocery_list)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`pop` enables us to remove item from the list:\n",
-    "\n",
-    "- by default pop() removes the last item from the list\n",
-    "- you can override that by passing an index as argument\n",
-    "- pop remove the item from the original list and also returns it"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "grocery_list.pop()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "grocery_list"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# TODO: remove \"oranges\" from grocery_list and store it into a variable\n",
-    "some_fruit = grocery_list.pop(???)\n",
-    "print(some_fruit)\n",
-    "print(grocery_list)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`sort` method enables us to sort the list using alphanumeric ordering.\n",
-    "\n",
-    "TODO: Try sorting each of the following lists."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "L = None # TODO: initialize list with some unordered numbers\n",
-    "\n",
-    "L"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "L = None # TODO: initialize list with some unordered strings\n",
-    "\n",
-    "L"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "L = [False, True, False, True, True]\n",
-    "\n",
-    "L"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "L = [\"str\", 1, 2.0, False]\n",
-    "L.sort() # Doesn't work as you cannot compare different types!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`split` method splits a string into a list of strings, using a separator (argument)\n",
-    "- Syntax: some_string.split(separator_string)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sentence = \"a,quick,brown,fox\"\n",
-    "words = sentence.split(\",\")\n",
-    "words"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`join` method joins a list of strings into a single string using a separator (argument)\n",
-    "- Syntax: separator_string.join(some_list)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "characters = [\"M\", \"SS\", \"SS\", \"PP\", \"\"]\n",
-    "place = \"I\".join(characters)\n",
-    "place\n",
-    "\n",
-    "# TODO: remove the last item in characters list and see what place you get (re-run cell)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### List all Engineering majors (primary major) among current lecture (example: LEC001) students"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "for idx in range(project.count()):\n",
-    "    lecture = project.get_lecture(idx)\n",
-    "    major = project.get_primary_major(idx)\n",
-    "    \n",
-    "    if lecture == \"LEC001\":\n",
-    "        print(lecture, major)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Profanity filtering"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bad_words = [\"omg\", \"midterm\", \"exam\"]\n",
-    "\n",
-    "def censor(input_string):\n",
-    "    \"\"\"\n",
-    "    replaces every bad word in input string with that word's first\n",
-    "    letter and then * for the remaining characters\n",
-    "    \"\"\"\n",
-    "    # TODO: use split to extract every word \n",
-    "    \n",
-    "    # TODO: Iterate over every word: 1. check if word is in bad_words 2. compute replacement 3. replace word\n",
-    "    \n",
-    "    # TODO: join the words back using the correct separator and return the joined string\n",
-    "    \n",
-    "censor(\"omg the midterm was so awesome!\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Wordle (self-study example)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def get_wordle_results(guess):\n",
-    "    wordle_result = \"\"\n",
-    "    for i in range(len(guess)):\n",
-    "        if guess[i] == word_of_the_day[i]:\n",
-    "            wordle_result += \"O\"\n",
-    "        elif word_of_the_day.find(guess[i]) != -1:\n",
-    "            wordle_result += \"_\"\n",
-    "        else:\n",
-    "            wordle_result += \"X\"\n",
-    "    return wordle_result\n",
-    "\n",
-    "max_num_guesses = 6\n",
-    "current_num_guesses = 1\n",
-    "word_of_the_day = \"CRANE\"\n",
-    "\n",
-    "print(\"Welcome to PyWordle!\")\n",
-    "print(\"You have 6 guesses to guess a 5 character word.\")\n",
-    "print(\"X\\tThe letter is not in the word.\")\n",
-    "print(\"_\\tThe letter is in the word, but in the wrong place.\")\n",
-    "print(\"O\\tThe letter is in the correct place!\")\n",
-    "\n",
-    "while current_num_guesses <= max_num_guesses:\n",
-    "    guess = input(\"Guess the word: \")\n",
-    "    guess = guess.upper()\n",
-    "\n",
-    "    wordle_results = get_wordle_results(guess)\n",
-    "    print(\"{}\\t{}\".format(guess, wordle_results))\n",
-    "    if guess == word_of_the_day:\n",
-    "        break\n",
-    "    current_num_guesses += 1\n",
-    "    \n",
-    "if current_num_guesses > max_num_guesses:\n",
-    "    print(\"Better luck next time!\")\n",
-    "    print(\"The word was: {}\".format(word_of_the_day))\n",
-    "else:\n",
-    "    print(\"You won in {} guesses!\".format(current_num_guesses))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.7"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/f22/meena_lec_notes/lec-14/cs220_survey_data.csv b/f22/meena_lec_notes/lec-14/cs220_survey_data.csv
index 2ecab22259411bdf759cddea3b6be928b7cab6ad..abfd53ba7dfcd37e19c7d2b5ef5b4951d59cfa99 100644
--- a/f22/meena_lec_notes/lec-14/cs220_survey_data.csv
+++ b/f22/meena_lec_notes/lec-14/cs220_survey_data.csv
@@ -1,721 +1,993 @@
-Lecture,Age,Primary major,Other majors,Zip Code,Pizza topping,Pet owner,Runner,Sleep habit,Procrastinator
-LEC002,19,Engineering: Mechanical,,53711,pepperoni,Yes,No,night owl,Maybe
-LEC002,20,Science: Physics,"Astronomy-Physics, History",53726,pineapple,Yes,Yes,night owl,Yes
-LEC001,20,Science: Chemistry,,53703,pepperoni,Yes,No,early bird,No
-LEC004,19,Engineering: Biomedical,,53703,pepperoni,Yes,Yes,night owl,No
-LEC004,20,Other,Economics ,53715,mushroom,Yes,Yes,no preference,Maybe
-LEC003,18,Statistics,,53706,Other,Yes,No,night owl,Yes
-LEC003,18,Mathematics/AMEP,,53706,sausage,No,No,night owl,No
-LEC004,18,Engineering: Biomedical,,53706,pepperoni,Yes,No,night owl,Maybe
-LEC003,19,Data Science,Stats,53715,pineapple,Yes,No,no preference,No
-LEC003,19,Business: Finance,,53703,sausage,Yes,Yes,early bird,Yes
-LEC003,18,Engineering: Mechanical,,53706,Other,No,No,no preference,No
-LEC004,18,Other,I am undecided – thinking about Data Science Major,53706,basil/spinach,Yes,No,night owl,Maybe
-LEC004,19,Engineering: Other,,53706,pepperoni,Yes,No,night owl,Maybe
-LEC003,18,Statistics,psychology,53706,mushroom,No,No,night owl,Yes
-LEC004,20,Statistics,Mathematics ,53726,pepperoni,Yes,Yes,early bird,Maybe
-LEC004,20,Mathematics/AMEP,,53711,sausage,Yes,No,night owl,Yes
-LEC003,18,Science: Physics,Data Science,53706,pepperoni,No,Yes,early bird,No
-LEC003,19,Data Science,Economics,53715,pepperoni,No,Yes,no preference,Maybe
-LEC003,19,Engineering: Mechanical,nuclear engineering,53706,sausage,Yes,No,night owl,Yes
-LEC003,21,Science: Chemistry,,,green pepper,Yes,No,early bird,Maybe
-LEC003,18,Engineering: Other,,53706,pepperoni,Yes,Yes,no preference,Yes
-LEC003,,Engineering: Other,,,pineapple,Yes,No,early bird,Maybe
-LEC002,20,Computer Science,Data Science,53706,basil/spinach,Yes,No,night owl,Maybe
-LEC002,21,Science: Other,,53703,sausage,Yes,No,early bird,Maybe
-LEC001,21,Computer Science,Data Science,53715,pepperoni,Yes,No,night owl,Maybe
-LEC004,18,Engineering: Mechanical,,53706,pepperoni,Yes,No,early bird,Maybe
-LEC002,18,Languages,Linguistics,53706,macaroni/pasta,Yes,Yes,night owl,Yes
-LEC002,18,Engineering: Mechanical,,53706,Other,No,Yes,night owl,Maybe
-LEC002,18,Other,,53706,none (just cheese),Yes,Yes,night owl,Yes
-LEC001,19,Science: Other,,53706,mushroom,Yes,No,night owl,Yes
-LEC001,18,Engineering: Biomedical,,,pepperoni,Yes,No,no preference,Maybe
-LEC003,19,Engineering: Biomedical,,53706,none (just cheese),Yes,No,night owl,Maybe
-LEC001,20,Science: Physics,Mathematics,53703,pineapple,Yes,No,early bird,No
-LEC002,28,Science: Other,,53703,pineapple,Yes,Yes,night owl,Maybe
-LEC001,18,Other,,53706,pepperoni,Yes,No,night owl,Yes
-LEC001,20,Engineering: Other,,53715,pepperoni,Yes,No,night owl,Yes
-LEC001,19,Science: Physics,Life Science Communication,53706,pineapple,Yes,No,night owl,Yes
-LEC003,18,Engineering: Biomedical,pre-medicine,53706,sausage,Yes,Yes,early bird,No
-LEC003,,Engineering: Biomedical,,53706,none (just cheese),No,Yes,early bird,Yes
-LEC001,21,Science: Other,,53711,pepperoni,Yes,No,night owl,No
-LEC002,18,Engineering: Biomedical,,53706,sausage,Yes,No,no preference,No
-LEC001,18,Engineering: Biomedical,,53706,macaroni/pasta,Yes,No,early bird,Yes
-LEC004,21,Engineering: Biomedical,,53703,pepperoni,Yes,No,no preference,Yes
-LEC004,18,Business: Information Systems,,53706,pepperoni,Yes,Yes,night owl,No
-LEC001,19,Business: Actuarial,Data Science and Analytics,53706,pepperoni,Yes,Yes,night owl,No
-LEC001,22,Engineering: Industrial,,,sausage,Yes,No,night owl,Yes
-LEC003,20,Other,"data science, business",53703,mushroom,Yes,Yes,no preference,Maybe
-LEC004,18,Engineering: Mechanical,,53706,pepperoni,Yes,No,night owl,Yes
-LEC001,18,Engineering: Other,,53706,mushroom,No,No,early bird,No
-LEC001,19,Data Science,Sports Journalism certificate,53703,pepperoni,Yes,Yes,no preference,No
-LEC004,18,Data Science,,53706,none (just cheese),Yes,No,night owl,Yes
-LEC002,20,Statistics,"Data Science, Math",53715,mushroom,No,No,night owl,No
-LEC001,19,Engineering: Biomedical,,53706,mushroom,Yes,Yes,early bird,No
-LEC003,20,Other,Data science certificate,,sausage,Yes,Yes,no preference,Yes
-LEC003,20,Engineering: Industrial,Computer science,53719,sausage,No,No,early bird,Maybe
-LEC003,,Computer Science,Minors in Data Science and Chicano and Latino Studies,53715,macaroni/pasta,No,Yes,night owl,Yes
-LEC002,19,Computer Science,,,mushroom,Yes,No,no preference,No
-LEC002,18,Engineering: Biomedical,,,pepperoni,Yes,No,night owl,Yes
-LEC002,20,Business: Finance,Economics,53715,pepperoni,Yes,No,night owl,Yes
-LEC002,19,Engineering: Biomedical,,53706,sausage,Yes,Yes,no preference,Maybe
-LEC002,19,Engineering: Biomedical,,52706,pepperoni,Yes,Yes,early bird,No
-LEC001,19,Science: Biology/Life,,53703,basil/spinach,Yes,No,night owl,Maybe
-LEC002,19,Engineering: Mechanical,History,53706,none (just cheese),No,Yes,no preference,Yes
-LEC002,21,Computer Science,Math,53715,sausage,Yes,No,night owl,Yes
-LEC004,19,Data Science,Economics,53706,pepperoni,No,No,night owl,Yes
-LEC001,18,Engineering: Mechanical,,53715,none (just cheese),Yes,Yes,no preference,Maybe
-LEC004,18,Engineering: Biomedical,,53706,pineapple,Yes,No,night owl,Yes
-LEC003,18,Other,Sociology,53706,pineapple,Yes,No,night owl,Yes
-LEC004,18,Engineering: Biomedical,,53706,pepperoni,Yes,Yes,early bird,No
-LEC001,23,Business: Other,,53705,pineapple,No,No,no preference,No
-LEC004,18,Engineering: Biomedical,,53706,mushroom,Yes,Yes,no preference,Maybe
-LEC001,18,Data Science,,53703,pepperoni,Yes,No,night owl,No
-LEC001,19,Business: Finance,,53706,pineapple,No,No,night owl,Maybe
-LEC004,19,Science: Biology/Life,"Environmental Sciences, Conservation Biology",53715,basil/spinach,Yes,No,no preference,No
-LEC001,20,Computer Science,,53715,pepperoni,Yes,Yes,night owl,Yes
-LEC004,18,Computer Science,Data Science,53706,none (just cheese),Yes,No,early bird,Yes
-LEC003,18,Science: Other,,53706,pepperoni,Yes,No,night owl,Yes
-LEC002,19,Engineering: Biomedical,,53706,sausage,Yes,Yes,no preference,Yes
-LEC001,19,Computer Science,Economics,53715,sausage,Yes,No,no preference,Yes
-LEC001,21,Other,,,mushroom,No,No,night owl,Maybe
-LEC004,21,Data Science,,53703,none (just cheese),Yes,No,night owl,Yes
-LEC002,20,Data Science,,53703,pineapple,Yes,Yes,early bird,Maybe
-LEC002,18,Data Science,,53715,Other,Yes,No,early bird,No
-LEC003,19,Mathematics/AMEP,Double major math and economics,,pepperoni,Yes,Yes,night owl,No
-LEC003,18,Science: Biology/Life,,53706,none (just cheese),No,Yes,night owl,Yes
-LEC003,20,Computer Science,Computer Engineering,,pepperoni,Yes,No,night owl,Maybe
-LEC002,20,Engineering: Industrial,Maybe Data Science,53703,none (just cheese),Yes,No,night owl,Yes
-LEC003,18,Data Science,Biochemistry,53706,basil/spinach,No,Yes,no preference,Yes
-LEC003,19,Science: Other,,53706,Other,No,Yes,early bird,No
-LEC003,20,Engineering: Mechanical,,53706,pepperoni,No,No,night owl,Maybe
-LEC001,36,Other,,53705,sausage,No,No,no preference,Maybe
-LEC003,18,Data Science,,53706,pineapple,Yes,No,early bird,No
-LEC003,19,Engineering: Mechanical,,,pepperoni,Yes,No,no preference,No
-LEC004,20,Science: Biology/Life,,53703,pepperoni,Yes,No,night owl,Yes
-LEC001,22,Engineering: Biomedical,,53703,sausage,Yes,No,night owl,Yes
-LEC002,18,Business: Information Systems,,53706,macaroni/pasta,Yes,Yes,no preference,Maybe
-LEC001,18,Engineering: Other,,53703,basil/spinach,Yes,Yes,no preference,Yes
-LEC002,19,Statistics,mathematics,53703,Other,No,Yes,night owl,Yes
-LEC001,20,Engineering: Biomedical,,53715,pepperoni,Yes,No,early bird,Yes
-LEC002,24,Science: Other,,53703,mushroom,Yes,No,night owl,Yes
-LEC001,20,Computer Science,Data science,53715,pepperoni,Yes,Yes,night owl,No
-LEC001,19,Mathematics/AMEP,Spanish,53715,pepperoni,Yes,Yes,night owl,Yes
-LEC003,19,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,night owl,Yes
-LEC003,20,Data Science,,53726,sausage,Yes,No,night owl,Maybe
-LEC004,20,Other,,53713,pineapple,Yes,No,early bird,Maybe
-LEC002,23,Engineering: Other,,53705,pineapple,Yes,No,night owl,Maybe
-LEC001,21,Engineering: Mechanical,,53706,pepperoni,No,Yes,night owl,Yes
-LEC003,21,Science: Biology/Life,,53726,basil/spinach,Yes,No,night owl,Yes
-LEC003,19,Engineering: Mechanical,,53706,pepperoni,Yes,No,night owl,No
-LEC004,19,Engineering: Other,,53706,sausage,Yes,No,night owl,Yes
-LEC001,19,Science: Physics,,53706,Other,Yes,No,night owl,Maybe
-LEC002,20,Engineering: Industrial,,53715,basil/spinach,Yes,No,night owl,Yes
-LEC003,19,Science: Biology/Life,Data sciences ,53706,pineapple,Yes,Yes,early bird,No
-LEC003,19,Other,undecided/exploring majors in science/math/tech,53706,macaroni/pasta,Yes,Yes,night owl,Maybe
-LEC001,19,Engineering: Industrial,,53703,sausage,Yes,No,night owl,Yes
-LEC003,20,Engineering: Industrial,,53703,sausage,Yes,Yes,night owl,Yes
-LEC002,18,Other,,53706,pepperoni,Yes,No,no preference,Yes
-LEC003,19,Business: Information Systems,Management and Human Resources ,53706,none (just cheese),No,No,night owl,No
-LEC001,19,Computer Science,Computer engineering,53726,pepperoni,Yes,Yes,night owl,Yes
-LEC001,18,Business: Finance,Minor: Data Science,53703,pepperoni,Yes,No,night owl,Maybe
-LEC002,18,Engineering: Mechanical,,53706,Other,Yes,No,night owl,Yes
-LEC004,18,Engineering: Mechanical,,53715,sausage,Yes,No,no preference,Maybe
-LEC002,19,Engineering: Biomedical,,53715,pepperoni,Yes,No,night owl,Maybe
-LEC002,22,Science: Other,,53715,sausage,Yes,Yes,night owl,Yes
-LEC001,19,Other,Education Studies,53715,mushroom,No,No,night owl,Yes
-LEC001,24,Business: Actuarial,,53713,sausage,Yes,No,night owl,Maybe
-LEC001,18,Engineering: Mechanical,,53706,pepperoni,Yes,No,night owl,Yes
-LEC001,25,Engineering: Industrial,,53705,pineapple,No,No,night owl,Maybe
-LEC003,20,Engineering: Biomedical,,53703,pepperoni,Yes,Yes,night owl,Yes
-LEC003,18,Engineering: Mechanical,business,53706,pepperoni,Yes,Yes,night owl,Yes
-LEC002,21,Engineering: Biomedical,,53703,basil/spinach,Yes,No,night owl,Maybe
-LEC003,19,Computer Science,,53703,pepperoni,Yes,No,no preference,No
-LEC003,18,Data Science,,53703,pepperoni,Yes,Yes,early bird,No
-LEC001,19,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,night owl,Yes
-LEC003,18,Mathematics/AMEP,,52706,mushroom,Yes,Yes,night owl,No
-LEC001,19,Data Science,,53706,macaroni/pasta,Yes,No,night owl,Maybe
-LEC003,18,Business: Other,I wasn't sure what to answer in the question above because I'm a Freshman and I'm Pre-Business.,53703,none (just cheese),Yes,No,night owl,Yes
-LEC001,21,Data Science,,53715,pepperoni,Yes,Yes,early bird,No
-LEC003,18,Computer Science,,53706-1203,Other,Yes,No,night owl,Yes
-LEC001,20,Computer Science,,53706,pepperoni,No,No,night owl,Yes
-LEC003,19,Business: Information Systems,,53706,sausage,Yes,Yes,no preference,No
-LEC001,21,Business: Actuarial,Risk Management and Insurance,53715,pineapple,Yes,No,night owl,Maybe
-LEC003,19,Science: Biology/Life,Data Science,53706,pepperoni,Yes,No,night owl,Yes
-LEC003,19,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,night owl,Yes
-LEC004,20,Engineering: Biomedical,,53703,pepperoni,Yes,Yes,early bird,No
-LEC002,21,Other,Economics with Math Emphasis,53703,pepperoni,Yes,No,no preference,Yes
-LEC001,20,Business: Other,Certificates in Data Science and Digital Studies,53715,sausage,Yes,Yes,early bird,Maybe
-LEC001,18,Engineering: Mechanical,,,pineapple,No,No,no preference,Yes
-LEC003,19,Computer Science,,53706,pepperoni,No,Yes,no preference,Maybe
-LEC003,18,Statistics,Data Science ,53706,pepperoni,Yes,No,night owl,No
-LEC004,18,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,night owl,Maybe
-LEC002,26,Engineering: Other,,53705,Other,Yes,Yes,early bird,Yes
-LEC001,19,Engineering: Mechanical,,53706,pepperoni,Yes,No,night owl,Yes
-LEC003,18,Engineering: Mechanical,,53706,basil/spinach,Yes,No,night owl,Yes
-LEC001,27,Computer Science,,53703,sausage,No,No,early bird,Maybe
-LEC003,20,Engineering: Biomedical,,,mushroom,Yes,No,early bird,Yes
-LEC001,18,Statistics,,,sausage,Yes,No,night owl,Maybe
-LEC004,19,Statistics,Considering data science as my secondary field of study.,53726,pepperoni,Yes,No,night owl,Yes
-LEC001,19,Engineering: Industrial,,,basil/spinach,Yes,Yes,night owl,Yes
-LEC001,20,Other,,53706,macaroni/pasta,Yes,Yes,night owl,Maybe
-LEC004,20,Other,,53703,sausage,Yes,Yes,night owl,Yes
-LEC001,21,Engineering: Other,,53715,pepperoni,No,No,night owl,Yes
-LEC004,20,Engineering: Mechanical,,53711,mushroom,Yes,No,night owl,Yes
-LEC003,20,Business: Information Systems,,53715,pepperoni,Yes,No,night owl,Yes
-LEC003,21,Engineering: Other,,,mushroom,Yes,No,night owl,Yes
-LEC001,24,Statistics,data science,53703,basil/spinach,Yes,No,early bird,No
-LEC003,19,Computer Science,math,53706,basil/spinach,Yes,No,early bird,Maybe
-LEC004,21,Computer Science,,53715,pepperoni,Yes,Yes,early bird,No
-LEC002,21,Mathematics/AMEP,,53715,pepperoni,Yes,No,early bird,Maybe
-LEC001,,Science: Biology/Life,,,Other,Yes,Yes,early bird,No
-LEC003,18,Engineering: Mechanical,Computer Science Certificate,53706,basil/spinach,No,Yes,early bird,No
-LEC002,18,Other,Data Science,53706,basil/spinach,Yes,No,early bird,No
-LEC003,18,Business: Information Systems,Data Science Certificate,53706,basil/spinach,Yes,Yes,early bird,No
-LEC002,19,Engineering: Industrial,,53706,sausage,Yes,No,early bird,Maybe
-LEC004,18,Engineering: Mechanical,,53706,sausage,Yes,No,night owl,Maybe
-LEC001,22,Science: Other,Mathematics,53726,pepperoni,Yes,Yes,no preference,Yes
-LEC001,18,Engineering: Industrial,,53706,mushroom,No,Yes,early bird,Yes
-LEC002,19,Engineering: Mechanical,,53706,green pepper,No,Yes,night owl,No
-LEC003,18,Statistics,mathematics,53706,mushroom,Yes,No,night owl,No
-LEC003,19,Other,,53706,pepperoni,Yes,Yes,no preference,Yes
-LEC003,20,Other,"Education, Psychology, Data Science",53715,pineapple,Yes,Yes,no preference,Yes
-LEC003,19,Statistics,,53703,pepperoni,Yes,No,early bird,Maybe
-LEC003,20,Data Science,,53703,macaroni/pasta,Yes,Yes,night owl,Yes
-LEC004,20,Business: Actuarial,,53706,pepperoni,Yes,No,early bird,No
-LEC003,20,Data Science,,53703,mushroom,Yes,No,night owl,Yes
-LEC003,19,Mathematics/AMEP,finance,53706,sausage,No,Yes,early bird,Maybe
-LEC003,21,Other,Political Science,53703,pepperoni,Yes,No,night owl,Maybe
-LEC002,19,Engineering: Mechanical,,53706,basil/spinach,Yes,Yes,night owl,Maybe
-LEC001,19,Mathematics/AMEP,Data Science,53706,pepperoni,Yes,Yes,night owl,Maybe
-LEC001,18,Computer Science,Information Systems (Maybe),53706,sausage,Yes,No,early bird,Yes
-LEC001,20,Business: Actuarial,Business: Risk Management,53703,pepperoni,Yes,No,early bird,Yes
-LEC002,26,Engineering: Other,,53705,mushroom,No,No,night owl,Maybe
-LEC001,18,Business: Information Systems,,53706,pepperoni,Yes,No,night owl,Yes
-LEC003,23,Engineering: Other,Environmental Science,53703,mushroom,Yes,Yes,early bird,Maybe
-LEC003,18,Science: Biology/Life,,53706,pineapple,No,No,early bird,Yes
-LEC002,18,Engineering: Biomedical,,53706,pepperoni,Yes,No,no preference,No
-LEC001,18,Other,,53706,pepperoni,Yes,No,night owl,Yes
-LEC003,19,Engineering: Mechanical,Data Science,53726,sausage,Yes,No,no preference,Yes
-LEC003,20,Data Science,,53715,pepperoni,Yes,No,night owl,Yes
-LEC003,19,Engineering: Biomedical,,53706,pepperoni,No,Yes,early bird,No
-LEC004,19,Business: Information Systems,,53715,none (just cheese),Yes,No,night owl,Yes
-LEC001,20,Computer Science,,53703,mushroom,Yes,Yes,early bird,Maybe
-LEC002,18,Data Science,,53703,none (just cheese),Yes,No,night owl,Yes
-LEC004,19,Engineering: Mechanical,,53575,sausage,Yes,No,night owl,Maybe
-LEC004,20,Business: Other,Information Systems,53703,sausage,Yes,Yes,no preference,Maybe
-LEC003,18,Engineering: Biomedical,,53715,pineapple,Yes,No,no preference,Yes
-LEC004,19,Engineering: Mechanical,,53706,mushroom,Yes,No,early bird,Maybe
-LEC003,,Engineering: Biomedical,Certificate in French,,macaroni/pasta,Yes,Yes,night owl,No
-LEC003,21,Business: Information Systems,,53703,pepperoni,Yes,Yes,night owl,Maybe
-LEC001,,Data Science,,5 3706,mushroom,Yes,No,night owl,No
-LEC004,19,Engineering: Biomedical,,53715,none (just cheese),Yes,Yes,no preference,Yes
-LEC002,19,Engineering: Biomedical,,53703,pepperoni,Yes,Yes,night owl,No
-LEC003,20,Computer Science,,53711,sausage,No,No,night owl,Maybe
-LEC004,21,Science: Biology/Life,,53711,sausage,Yes,Yes,night owl,No
-LEC003,21,Other,"Psychology, Chinese",53703,Other,Yes,Yes,night owl,Maybe
-LEC003,20,Data Science,Minor - Comp Sci,53703,basil/spinach,Yes,Yes,no preference,Yes
-LEC004,21,Science: Other,"Global Health is main major, possibly on the premed track, Data Science Certificate",53715,pineapple,Yes,Yes,early bird,No
-LEC003,20,Engineering: Mechanical,,53726,pepperoni,Yes,Yes,night owl,Yes
-LEC001,22,Science: Biology/Life,,53703,green pepper,Yes,No,night owl,Yes
-LEC002,19,Science: Biology/Life,,53703,pepperoni,Yes,No,night owl,Maybe
-LEC004,21,Engineering: Biomedical,,53715,green pepper,Yes,Yes,night owl,Maybe
-LEC002,20,Business: Finance,Real Estate,53703,pepperoni,Yes,Yes,night owl,No
-LEC004,21,Engineering: Biomedical,,53703,pepperoni,Yes,Yes,night owl,Yes
-LEC002,19,Engineering: Industrial,"not positive on IE, maybe ME",53703,pepperoni,Yes,No,night owl,Maybe
-LEC004,18,Engineering: Biomedical,,53706,mushroom,Yes,No,early bird,No
-LEC003,19,Business: Actuarial,Data Science,53706,pepperoni,Yes,No,night owl,Yes
-LEC001,24,Other,Life Science Communications,53703,pineapple,Yes,No,night owl,No
-LEC004,22,Engineering: Other,,53715,pepperoni,No,Yes,early bird,No
-LEC002,18,Engineering: Mechanical,,53715,pepperoni,Yes,Yes,night owl,Maybe
-LEC004,19,Data Science,business: finance,53703,pepperoni,Yes,Yes,night owl,Yes
-LEC003,19,Business: Other,"Economics, Data Science",53703,pepperoni,Yes,Yes,early bird,No
-LEC004,18,Engineering: Other,,53706,pineapple,Yes,Yes,night owl,Maybe
-LEC003,19,Engineering: Mechanical,,53706,none (just cheese),Yes,No,early bird,No
-LEC002,18,Engineering: Mechanical,,53706,Other,Yes,Yes,early bird,No
-LEC001,19,Other,,53706,green pepper,Yes,Yes,night owl,Yes
-LEC004,18,Engineering: Biomedical,,53706,basil/spinach,Yes,Yes,no preference,No
-LEC001,19,Business: Information Systems,,53726,green pepper,No,Yes,night owl,Maybe
-LEC001,18,Engineering: Biomedical,,53706,sausage,Yes,No,night owl,Yes
-LEC003,19,Engineering: Industrial,,53715,pepperoni,No,Yes,early bird,Yes
-LEC002,27,Business: Information Systems,,53703,mushroom,No,Yes,night owl,No
-LEC001,30,Business: Other,,57305,pineapple,Yes,No,night owl,Yes
-LEC004,18,Engineering: Biomedical,Neuroscience/pre-med,53706,none (just cheese),Yes,No,night owl,Yes
-LEC002,20,Data Science,,53703,mushroom,No,No,early bird,Yes
-LEC001,19,Data Science,,53706,Other,Yes,Yes,no preference,Maybe
-LEC001,22,Engineering: Biomedical,,53706,sausage,Yes,No,night owl,Yes
-LEC003,20,Data Science,,,mushroom,Yes,No,no preference,Maybe
-LEC003,20,Other,Economics with Math emphasis,53703,pineapple,No,No,early bird,Maybe
-LEC002,20,Computer Science,Data Science,53706,basil/spinach,Yes,No,no preference,Yes
-LEC001,24,Science: Biology/Life,,53706,mushroom,Yes,Yes,early bird,No
-LEC004,20,Business: Information Systems,Real Estate,53703,pepperoni,Yes,No,night owl,Maybe
-LEC001,20,Data Science,Economics,53703,sausage,Yes,No,no preference,Maybe
-LEC002,20,Engineering: Mechanical,,53703,pepperoni,Yes,Yes,night owl,Maybe
-LEC004,20,Engineering: Mechanical,,53715,pineapple,Yes,Yes,night owl,No
-LEC004,20,Science: Biology/Life,Data Science Certificate (maybe) ,53703,sausage,Yes,Yes,night owl,Maybe
-LEC004,18,Engineering: Mechanical,,19002,pepperoni,Yes,No,no preference,Yes
-LEC001,19,Engineering: Other,,53706,pepperoni,Yes,No,no preference,Maybe
-LEC002,18,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,early bird,Maybe
-LEC004,19,Computer Science,Mathematics,53706,pineapple,Yes,No,no preference,Maybe
-LEC003,18,Business: Information Systems,,53706,pepperoni,Yes,No,night owl,Yes
-LEC003,19,Science: Physics,,53706,pineapple,Yes,Yes,night owl,Maybe
-LEC004,18,Other,,53706,pepperoni,Yes,Yes,night owl,Maybe
-LEC001,25,Engineering: Other,"Architect, Landscape Planner",,mushroom,Yes,Yes,early bird,No
-LEC001,21,Engineering: Mechanical,Physics,53706,mushroom,No,Yes,no preference,Maybe
-LEC004,20,Other,"I major in economics, hoping to obtain a data science certificate.",53703,pepperoni,Yes,No,night owl,Yes
-LEC001,20,Data Science,Economics,53703,none (just cheese),No,Yes,night owl,Maybe
-LEC001,21,Science: Other,,53703,mushroom,Yes,No,night owl,Yes
-LEC002,18,Data Science,,53706,pepperoni,Yes,No,night owl,No
-LEC002,24,Business: Other,,53711,sausage,Yes,No,night owl,Yes
-LEC001,19,Engineering: Mechanical,,53706,pepperoni,Yes,No,night owl,Maybe
-LEC003,20,Business: Actuarial,,53703,pepperoni,No,Yes,night owl,No
-LEC001,21,Data Science,Economics,53715,pineapple,Yes,No,night owl,Maybe
-LEC001,23,Other,"Marketing, Data science ",,none (just cheese),No,No,early bird,Maybe
-LEC002,22,Engineering: Biomedical,,53703,pepperoni,Yes,Yes,night owl,No
-LEC003,18,Computer Science,,53703,sausage,Yes,No,night owl,Yes
-LEC003,19,Science: Physics,Astronomy-Physics ,53706,pepperoni,Yes,No,night owl,Yes
-LEC003,19,Engineering: Mechanical,,53715,pepperoni,Yes,No,early bird,No
-LEC001,18,Data Science,,53706,pepperoni,Yes,Yes,early bird,Yes
-LEC001,18,Business: Information Systems,,53706,pepperoni,No,No,night owl,Yes
-LEC002,20,Mathematics/AMEP,data and risk analysis (data science),53726,pineapple,Yes,No,night owl,Yes
-LEC001,18,Other,,53706,mushroom,Yes,No,no preference,Yes
-LEC002,20,Science: Biology/Life,Economics with Math Emphasis,53703,pepperoni,Yes,No,early bird,Yes
-LEC001,18,Data Science,,53706,none (just cheese),Yes,No,night owl,Yes
-LEC001,,Statistics,Econ,,pineapple,No,No,night owl,Maybe
-LEC003,19,Engineering: Biomedical,,53706,pineapple,Yes,No,night owl,Yes
-LEC003,18,Engineering: Mechanical,,53706,Other,Yes,Yes,night owl,Yes
-LEC003,18,Engineering: Biomedical,,53089,pepperoni,Yes,No,night owl,Yes
-LEC003,18,Mathematics/AMEP,,53703,sausage,No,No,no preference,Maybe
-LEC001,18,Data Science,,53706,pepperoni,Yes,Yes,night owl,Yes
-LEC003,19,Data Science,,53706,pepperoni,Yes,No,early bird,Yes
-LEC003,21,Engineering: Biomedical,,53726,sausage,Yes,No,early bird,Maybe
-LEC004,22,Business: Other,,53703,green pepper,Yes,Yes,night owl,Yes
-LEC002,19,Engineering: Mechanical,computer science,53706,pineapple,Yes,Yes,night owl,Maybe
-LEC004,21,Science: Biology/Life,,53703,sausage,Yes,No,early bird,No
-LEC002,18,Engineering: Other,,53706,sausage,Yes,Yes,night owl,Maybe
-LEC001,20,Data Science,Economics,53703,pepperoni,Yes,Yes,night owl,Yes
-LEC003,19,Engineering: Industrial,,53703,pepperoni,Yes,Yes,early bird,Maybe
-LEC003,21,Computer Science,no,53703,pineapple,Yes,No,night owl,No
-LEC002,20,Engineering: Mechanical,,53706,mushroom,Yes,No,night owl,Yes
-LEC003,21,Business: Finance,,53715,pepperoni,Yes,No,night owl,Yes
-LEC001,20,Science: Other,,53703,Other,Yes,Yes,night owl,Maybe
-LEC001,20,Engineering: Other,,53715,pepperoni,Yes,Yes,night owl,Yes
-LEC003,19,Engineering: Biomedical,,53706,green pepper,Yes,Yes,early bird,No
-LEC002,19,Engineering: Mechanical,"German Certificate, Theatre Certificate",53706,pepperoni,Yes,No,night owl,Yes
-LEC001,20,Engineering: Biomedical,,53703,pepperoni,Yes,No,night owl,Yes
-LEC001,19,Statistics,,53715,sausage,Yes,No,night owl,Yes
-LEC001,18,Engineering: Industrial,,53706,none (just cheese),Yes,No,night owl,Maybe
-LEC004,22,Data Science,Economics,53703,pepperoni,Yes,No,night owl,Maybe
-LEC001,18,Other,,53703,pepperoni,Yes,No,night owl,Yes
-LEC002,19,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,night owl,Yes
-LEC001,23,Other,Biological Anthropology,53705,none (just cheese),Yes,No,early bird,Yes
-LEC001,19,Engineering: Biomedical,,53706,pineapple,Yes,Yes,no preference,Maybe
-LEC004,19,Business: Actuarial,econ,53715,sausage,Yes,No,night owl,Yes
-LEC001,18,Engineering: Mechanical,,53703,macaroni/pasta,Yes,No,night owl,Yes
-LEC002,18,Business: Other,,53706,mushroom,No,No,night owl,Maybe
-LEC002,20,Other,,53703,mushroom,Yes,Yes,no preference,Yes
-LEC002,19,Business: Actuarial,,53703,Other,Yes,No,no preference,Maybe
-LEC001,21,Business: Other,,53715,pepperoni,Yes,No,night owl,Yes
-LEC001,21,Business: Other,econ with math emphasis,53715,mushroom,Yes,Yes,night owl,Maybe
-LEC004,21,Science: Biology/Life,,53703,none (just cheese),Yes,No,night owl,Maybe
-LEC004,22,Other,"Psychology, communications",53715,basil/spinach,Yes,No,night owl,Yes
-LEC003,18,Statistics,,53706,pepperoni,Yes,Yes,night owl,Maybe
-LEC001,20,Statistics,,53703,pepperoni,Yes,Yes,night owl,Maybe
-LEC002,21,Data Science,,,pepperoni,Yes,Yes,no preference,Maybe
-LEC001,18,Engineering: Biomedical,,,sausage,Yes,Yes,early bird,No
-LEC003,20,Statistics,,53706,sausage,Yes,No,night owl,No
-LEC002,21,Business: Other,,53703,pineapple,Yes,Yes,night owl,Maybe
-LEC001,22,Data Science,,53715,pineapple,Yes,Yes,night owl,Maybe
-LEC003,25,Computer Science,,53705,mushroom,Yes,No,night owl,Yes
-LEC004,20,Other,,53715,pepperoni,Yes,Yes,early bird,Yes
-LEC002,19,Computer Science,"ds,econ",53711,Other,Yes,No,night owl,No
-LEC002,18,Other,,53706,pepperoni,No,No,night owl,Yes
-LEC002,21,Business: Actuarial,Management,53706,pepperoni,Yes,No,night owl,Yes
-LEC001,19,Business: Finance,Data science,53703,pepperoni,No,No,no preference,Maybe
-LEC003,18,Engineering: Mechanical,,53703,pineapple,Yes,Yes,no preference,No
-LEC001,21,Business: Other,"Consumer Behavior & Marketplace Studies, Data Science",53703,pepperoni,Yes,No,night owl,No
-LEC002,20,Business: Finance,,53715,sausage,Yes,No,night owl,Yes
-LEC001,19,Other,Psychology,53703,pepperoni,No,Yes,night owl,Yes
-LEC003,18,Engineering: Biomedical,,53706,pepperoni,Yes,No,night owl,Yes
-LEC001,19,Business: Information Systems,,53711,sausage,Yes,No,night owl,No
-LEC003,21,Computer Science,,53715,sausage,No,Yes,early bird,Yes
-LEC004,20,Business: Other,,53703,pineapple,Yes,Yes,early bird,Yes
-LEC001,,Other,,53706,pineapple,Yes,No,no preference,Maybe
-LEC001,18,Statistics,economics,53703,pineapple,Yes,No,no preference,Yes
-LEC003,19,Business: Finance,,53706,mushroom,Yes,No,night owl,Maybe
-LEC001,18,Computer Science,Data Science,53706,mushroom,No,No,night owl,Maybe
-LEC003,20,Statistics,,53703,pepperoni,Yes,No,night owl,Yes
-LEC002,19,Engineering: Biomedical,,,macaroni/pasta,Yes,No,night owl,Yes
-LEC003,19,Data Science,,53715,green pepper,Yes,No,early bird,Maybe
-LEC001,19,Other,Psychology,53703,pepperoni,Yes,Yes,night owl,Maybe
-LEC003,21,Business: Finance,Economics,53703,pepperoni,Yes,No,night owl,Maybe
-LEC002,24,Engineering: Other,,53703,sausage,Yes,No,night owl,Yes
-LEC003,19,Engineering: Industrial,,53703,pepperoni,Yes,Yes,no preference,Maybe
-LEC002,20,Engineering: Other,"urban & regional planning, environmental engineering, data science",53706-1406,macaroni/pasta,Yes,Yes,night owl,Yes
-LEC003,23,Engineering: Other,,53705,pepperoni,No,Yes,night owl,Yes
-LEC001,19,Science: Biology/Life,,53703,pepperoni,Yes,No,early bird,No
-LEC001,18,Data Science,,53706,basil/spinach,Yes,No,night owl,Maybe
-LEC003,19,Business: Information Systems,,53703,macaroni/pasta,Yes,No,night owl,Yes
-LEC003,19,Engineering: Mechanical,,53706,pepperoni,Yes,No,night owl,Maybe
-LEC004,18,Science: Biology/Life,,53706,pepperoni,Yes,Yes,early bird,No
-LEC003,27,Science: Biology/Life,,53705,mushroom,Yes,No,early bird,Maybe
-LEC004,,Computer Science,,53715,pepperoni,Yes,No,night owl,Yes
-LEC004,20,Engineering: Biomedical,,53715,pepperoni,Yes,Yes,early bird,No
-LEC001,18,Computer Science,,53706,none (just cheese),No,Yes,night owl,Yes
-LEC004,17,Science: Biology/Life,Data science certificate,53706,pepperoni,Yes,No,no preference,Maybe
-LEC002,19,Data Science,"Econ, data science",53715,Other,Yes,No,night owl,Maybe
-LEC001,18,Computer Science,Data Science,53706,mushroom,No,No,night owl,Yes
-LEC002,18,Data Science,Economics,,pineapple,No,Yes,no preference,Yes
-LEC002,18,Engineering: Industrial,,53703-1104,sausage,Yes,No,night owl,Maybe
-LEC001,20,Business: Actuarial,Risk Management & Insurance,53703,pepperoni,Yes,No,early bird,No
-LEC001,19,Data Science,,53715,mushroom,Yes,Yes,no preference,Maybe
-LEC001,18,Engineering: Mechanical,,53706-1127,pepperoni,Yes,Yes,night owl,Yes
-LEC003,18,Engineering: Other,,53703,Other,No,Yes,early bird,No
-LEC001,24,Science: Other,data science,53715,pepperoni,Yes,Yes,early bird,Yes
-LEC004,19,Engineering: Biomedical,,53715,green pepper,Yes,No,early bird,Yes
-LEC003,20,Engineering: Biomedical,,53703,pepperoni,Yes,Yes,early bird,Maybe
-LEC003,21,Mathematics/AMEP,Biochemistry,53715,none (just cheese),Yes,Yes,early bird,No
-LEC003,20,Business: Other,,53706,sausage,Yes,No,night owl,Maybe
-LEC003,19,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,no preference,Yes
-LEC003,21,Engineering: Industrial,,53711,basil/spinach,No,Yes,night owl,Yes
-LEC001,20,Engineering: Industrial,,53703,pepperoni,Yes,Yes,no preference,No
-LEC003,18,Engineering: Industrial,,53706,sausage,Yes,Yes,night owl,No
-LEC003,20,Science: Biology/Life,Global Health,55416,pineapple,Yes,Yes,night owl,Yes
-LEC003,18,Engineering: Biomedical,,53706,basil/spinach,No,No,no preference,Maybe
-LEC003,19,Business: Other,,53706,sausage,Yes,No,night owl,Yes
-LEC003,18,Engineering: Industrial,,53706,green pepper,Yes,Yes,night owl,Yes
-LEC004,20,Data Science,Economics - math emphasis,53703,pepperoni,Yes,No,no preference,Yes
-LEC003,19,Business: Information Systems," Operations, Technology, Management",53715,pepperoni,Yes,No,night owl,Maybe
-LEC004,21,Engineering: Other,,53706,pineapple,No,Yes,early bird,No
-LEC003,19,Engineering: Mechanical,,53715,Other,Yes,No,early bird,No
-LEC003,20,Computer Science,Data Science,53703,none (just cheese),No,Yes,night owl,Maybe
-LEC003,18,Science: Biology/Life,Data science,53706,sausage,Yes,No,night owl,No
-LEC004,20,Engineering: Mechanical,,53715,macaroni/pasta,Yes,Yes,night owl,Yes
-LEC002,,Business: Other,Double Business Major (Supply Chain and Business Management),53703,basil/spinach,Yes,No,night owl,Maybe
-LEC003,18,Business: Finance,,53715,none (just cheese),No,Yes,night owl,Yes
-LEC002,20,Engineering: Industrial,,53703,pepperoni,Yes,Yes,night owl,Yes
-LEC001,22,Data Science,Stat or CS,53705,basil/spinach,Yes,Yes,early bird,No
-LEC003,20,Business: Information Systems,"International Business, French",53703,basil/spinach,Yes,Yes,early bird,No
-LEC004,19,Engineering: Other,,53706,none (just cheese),Yes,Yes,night owl,Maybe
-LEC002,20,Other,ECONOMICS,53715,none (just cheese),Yes,Yes,night owl,Maybe
-LEC004,19,Engineering: Mechanical, ,53715,pepperoni,Yes,No,night owl,Maybe
-LEC004,19,Engineering: Mechanical,,53715,pepperoni,Yes,Yes,no preference,Yes
-LEC004,20,Statistics,,53703,pepperoni,Yes,No,early bird,Yes
-LEC001,19,Business: Actuarial,RMI,53706,basil/spinach,Yes,Yes,night owl,Yes
-LEC001,20,Engineering: Biomedical,,53703,sausage,No,Yes,night owl,Yes
-LEC004,19,Engineering: Biomedical,,53706,basil/spinach,Yes,No,early bird,Yes
-LEC003,18,Data Science,,53706,none (just cheese),Yes,No,night owl,Maybe
-LEC001,21,Computer Science,,53703,Other,Yes,Yes,night owl,Maybe
-LEC001,19,Engineering: Industrial,,53706,pepperoni,Yes,No,night owl,No
-LEC004,20,Science: Other,,53713,pineapple,Yes,Yes,night owl,Maybe
-LEC004,18,Data Science,,53706,macaroni/pasta,Yes,No,night owl,Yes
-LEC004,20,Engineering: Industrial,NA,54636,macaroni/pasta,Yes,Yes,early bird,Maybe
-LEC001,19,Computer Science,,53711,mushroom,Yes,No,night owl,Yes
-LEC004,19,Computer Science,,53711,sausage,No,No,night owl,Maybe
-LEC004,19,Engineering: Biomedical,,53706,pepperoni,Yes,No,night owl,Maybe
-LEC004,19,Engineering: Mechanical,,53711,macaroni/pasta,Yes,No,night owl,Yes
-LEC004,19,Engineering: Mechanical,,53597,pepperoni,No,Yes,night owl,No
-LEC004,18,Engineering: Biomedical,,53706,sausage,Yes,Yes,night owl,Maybe
-LEC004,18,Computer Science,Data science,53706,basil/spinach,No,Yes,no preference,Maybe
-LEC004,21,Engineering: Biomedical,,53703,sausage,Yes,Yes,night owl,Yes
-LEC004,19,Business: Information Systems,Accounting,53706,mushroom,Yes,No,night owl,No
-LEC004,18,Engineering: Other,,53706,sausage,Yes,Yes,night owl,Yes
-LEC004,20,Data Science,,53715,Other,Yes,No,night owl,Yes
-LEC004,18,Engineering: Mechanical,,53706,mushroom,Yes,Yes,night owl,Yes
-LEC004,18,Engineering: Mechanical,,53706,macaroni/pasta,Yes,Yes,no preference,Maybe
-LEC001,18,Engineering: Biomedical,,53706,Other,No,No,night owl,Maybe
-LEC004,19,Business: Finance,Industrial Engineering,53706,sausage,Yes,No,night owl,Maybe
-LEC001,18,Business: Other,Main one is economics and data science,53706,pepperoni,No,No,no preference,Maybe
-LEC004,18,Engineering: Industrial,,83001,sausage,Yes,Yes,night owl,Yes
-LEC004,20,Engineering: Biomedical,,53715,pepperoni,Yes,Yes,night owl,Maybe
-LEC004,18,Engineering: Mechanical,,53706,none (just cheese),No,No,night owl,Yes
-LEC004,20,Other,,53715,sausage,No,No,night owl,Maybe
-LEC004,19,Business: Information Systems,Business: Supply Chain Management,53703,pepperoni,Yes,No,no preference,Maybe
-LEC004,20,Other,,53703,basil/spinach,Yes,No,night owl,Yes
-LEC004,18,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,night owl,Yes
-LEC004,19,Engineering: Mechanical,,53706,pepperoni,Yes,No,night owl,Yes
-LEC003,27,Computer Science,,53711,mushroom,Yes,Yes,no preference,Yes
-LEC004,19,Business: Actuarial,,53706-1188,sausage,Yes,No,no preference,Yes
-LEC004,21,Other,,53703,pepperoni,Yes,No,night owl,Yes
-LEC001,19,Business: Other,,53703,pepperoni,Yes,No,no preference,Maybe
-LEC004,18,Business: Finance,Data Science,53706,basil/spinach,Yes,No,night owl,Yes
-LEC004,18,Science: Physics,,53706,mushroom,Yes,No,night owl,Yes
-LEC002,19,Mathematics/AMEP,Actuarial Science,53706,sausage,Yes,Yes,night owl,Yes
-LEC004,19,Business: Finance,data science,53706,pepperoni,Yes,Yes,no preference,Maybe
-LEC002,19,Data Science,"Electrical engineering, physics",53703,none (just cheese),Yes,No,night owl,Yes
-LEC004,21,Engineering: Biomedical,History Certificate ,53715,green pepper,Yes,No,no preference,Maybe
-LEC001,19,Business: Finance,,53703,sausage,Yes,Yes,night owl,Maybe
-LEC001,18,Business: Finance,,53703,pepperoni,Yes,No,night owl,Yes
-LEC004,21,Engineering: Mechanical,Mechanical Engineering ,53703,green pepper,No,No,no preference,No
-LEC004,19,Business: Information Systems,,53706,pepperoni,Yes,Yes,no preference,Maybe
-LEC002,18,Computer Science,,53706,pepperoni,Yes,Yes,night owl,Yes
-LEC001,21,Computer Science,,43706,mushroom,Yes,Yes,no preference,Yes
-LEC002,20,Business: Finance,Data Science,53703,pepperoni,No,Yes,no preference,No
-LEC002,20,Engineering: Biomedical,,53703,pineapple,Yes,Yes,early bird,Maybe
-LEC001,19,Business: Actuarial,risk management and insurance,53711,pepperoni,No,No,night owl,Yes
-LEC002,21,Other,"Linguistics, Communication Sciences and Disorders",53715,green pepper,Yes,Yes,night owl,No
-LEC001,19,Engineering: Mechanical,,53706,none (just cheese),Yes,Yes,night owl,Yes
-LEC002,18,Engineering: Mechanical,,53706,macaroni/pasta,Yes,Yes,night owl,Yes
-LEC001,19,Data Science,,53703,pineapple,Yes,No,night owl,Yes
-LEC001,18,Science: Biology/Life,"Either stats, data science, or math (undecided)",53706,macaroni/pasta,Yes,Yes,night owl,Yes
-LEC001,19,Data Science,Mathematics,53703,green pepper,Yes,Yes,night owl,Maybe
-LEC001,23,Business: Other,,53711,pineapple,Yes,No,night owl,Maybe
-LEC001,20,Data Science,economics,53703,none (just cheese),Yes,No,early bird,Yes
-LEC001,18,Computer Science,Planning on Data Sci but unsure,53708,macaroni/pasta,Yes,No,night owl,Yes
-LEC002,18,Science: Other,,53706,pepperoni,Yes,No,early bird,Maybe
-LEC001,18,Computer Science,,53706,green pepper,Yes,Yes,night owl,Yes
-LEC001,19,Statistics,,53703,pineapple,Yes,No,night owl,No
-LEC001,20,Computer Science,Data Science,53703,pepperoni,Yes,Yes,no preference,Yes
-LEC001,19,Business: Information Systems,,53706,basil/spinach,Yes,No,night owl,Yes
-LEC001,19,Data Science,,53703,pineapple,No,Yes,night owl,Maybe
-LEC001,18,Engineering: Mechanical,,53706,macaroni/pasta,Yes,Yes,night owl,No
-LEC001,18,Data Science,,53706,pepperoni,Yes,No,night owl,Yes
-LEC001,19,Engineering: Industrial,Data Science,53706,green pepper,Yes,No,night owl,Yes
-LEC004,21,Other,,53726,sausage,Yes,No,night owl,Yes
-LEC001,19,Engineering: Mechanical,,53704,sausage,Yes,No,no preference,Yes
-LEC001,18,Computer Science,Data Science,53706,pepperoni,No,Yes,no preference,No
-LEC001,19,Other,,53705,pepperoni,No,No,night owl,Yes
-LEC001,21,Computer Science,data science,53706,pineapple,No,No,night owl,Yes
-LEC001,19,Statistics,,53703,sausage,Yes,No,night owl,Maybe
-LEC001,19,Science: Chemistry,,53706,pepperoni,Yes,No,night owl,Yes
-LEC001,20,Other,legal study,53705,sausage,Yes,No,no preference,Maybe
-LEC001,19,Statistics,biochemistry,53703,pineapple,Yes,No,no preference,Yes
-LEC001,22,Engineering: Biomedical,,,basil/spinach,Yes,Yes,night owl,Maybe
-LEC001,19,Engineering: Industrial,,53706,sausage,Yes,No,night owl,Yes
-LEC003,19,Engineering: Mechanical,,53711,sausage,Yes,No,no preference,Yes
-LEC001,19,Engineering: Mechanical,,53703,none (just cheese),Yes,Yes,night owl,Yes
-LEC001,21,Computer Science,Computer Engineering,53703,sausage,No,No,night owl,Yes
-LEC003,20,Engineering: Mechanical,,53703,sausage,No,No,night owl,No
-LEC001,21,Computer Science,Electrical Engineering,53715,pepperoni,Yes,Yes,night owl,Maybe
-LEC001,19,Engineering: Industrial,Business,53706,pepperoni,Yes,Yes,night owl,Maybe
-LEC001,18,Other,,53706,none (just cheese),Yes,No,night owl,Yes
-LEC001,18,Science: Biology/Life,"Data Science Minor, French",53706,pineapple,Yes,No,night owl,Yes
-LEC001,21,Other,,53703,mushroom,Yes,Yes,early bird,Yes
-LEC001,22,Computer Science,DS,53711,Other,Yes,No,no preference,Maybe
-LEC003,19,Other,,53703,pepperoni,No,No,no preference,Yes
-LEC001,19,Data Science,,53706,Other,No,Yes,early bird,Yes
-LEC002,18,Engineering: Mechanical,Minor in Business ,53706,sausage,Yes,No,no preference,Yes
-LEC001,21,Engineering: Other,Civil Engineering,53715,Other,No,Yes,no preference,Yes
-LEC002,19,Statistics,Economics,53703,pepperoni,Yes,No,night owl,Yes
-LEC002,20,Business: Actuarial,,53703,sausage,Yes,No,night owl,No
-LEC001,24,Business: Other,,53703,green pepper,No,No,early bird,Maybe
-LEC004,18,Engineering: Biomedical,,53706,sausage,Yes,No,no preference,No
-LEC001,23,Other,,53703,pineapple,Yes,No,night owl,Yes
-LEC003,19,Statistics,,53706,none (just cheese),Yes,Yes,early bird,Yes
-LEC002,18,Other,,53706,basil/spinach,Yes,No,night owl,Yes
-LEC001,20,Statistics,,53703,mushroom,Yes,Yes,night owl,Yes
-LEC004,18,Computer Science,Data Science,,none (just cheese),Yes,Yes,night owl,Yes
-LEC002,19,Engineering: Mechanical,,53706,Other,Yes,No,no preference,Yes
-LEC002,22,Science: Biology/Life,,53703,pepperoni,Yes,Yes,night owl,Yes
-LEC003,,Computer Science,Possibly Data Science (Definitely a Certificate),53706,Other,No,No,night owl,Yes
-LEC002,19,Engineering: Mechanical,,53562,pepperoni,Yes,Yes,night owl,Yes
-LEC002,19,Other,Data Science,53715,green pepper,Yes,Yes,no preference,Yes
-LEC003,18,Statistics,,53706,Other,No,No,night owl,Yes
-LEC004,19,Engineering: Mechanical,,53715,sausage,Yes,No,night owl,Yes
-LEC003,19,Engineering: Mechanical,,53706,pepperoni,Yes,No,night owl,Maybe
-LEC002,21,Business: Other,,53703,mushroom,No,No,no preference,Yes
-LEC003,19,Business: Information Systems,,53711,pepperoni,Yes,No,night owl,Yes
-LEC002,19,Business: Actuarial,,53706,sausage,No,No,night owl,Yes
-LEC002,21,Data Science,,53703,sausage,Yes,Yes,night owl,Yes
-LEC001,23,Data Science,,53705,mushroom,Yes,No,night owl,Yes
-LEC002,20,Computer Science,Data Science,53726,pineapple,Yes,Yes,night owl,Maybe
-LEC003,18,Engineering: Industrial,,53706,pepperoni,Yes,No,night owl,Yes
-LEC002,27,Data Science,,53705,basil/spinach,Yes,No,night owl,Yes
-LEC002,18,Computer Science,Data Science,53706,mushroom,Yes,No,early bird,Yes
-LEC001,22,Data Science,,53706,sausage,Yes,No,night owl,Yes
-LEC002,20,Computer Science,,53715,pepperoni,No,Yes,night owl,Yes
-LEC002,21,Data Science,,53703,macaroni/pasta,No,No,night owl,No
-LEC002,20,Computer Science,,,mushroom,Yes,No,early bird,Maybe
-LEC001,19,Computer Science,prolly data science,92376,pepperoni,Yes,No,night owl,Yes
-LEC002,19,Engineering: Mechanical,,53706,pepperoni,Yes,No,night owl,Maybe
-LEC002,19,Engineering: Mechanical,,,none (just cheese),Yes,No,night owl,Yes
-LEC002,19,Data Science,,53717,none (just cheese),Yes,No,night owl,Yes
-LEC002,22,Science: Other,,53715,green pepper,Yes,Yes,early bird,Yes
-LEC002,19,Engineering: Biomedical,,53706,sausage,Yes,No,early bird,No
-LEC002,20,Business: Finance,,53703,pepperoni,Yes,No,early bird,No
-LEC002,18,Business: Actuarial,,53706,pepperoni,Yes,No,early bird,No
-LEC002,19,Engineering: Mechanical,,53706,Other,Yes,No,night owl,Yes
-LEC002,20,Data Science,economics,internation student,mushroom,Yes,Yes,early bird,Maybe
-LEC003,19,Engineering: Mechanical,,,Other,No,No,night owl,Yes
-LEC002,19,Engineering: Industrial,,53703,sausage,No,Yes,night owl,Yes
-LEC002,19,Engineering: Mechanical,,53701,pepperoni,Yes,Yes,no preference,Yes
-LEC002,22,Computer Science,,53703,sausage,Yes,No,night owl,Yes
-LEC001,19,Engineering: Industrial,,53715,pepperoni,Yes,No,no preference,Maybe
-LEC002,18,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,night owl,Maybe
-LEC002,23,Mathematics/AMEP,,53719,sausage,No,Yes,early bird,Yes
-LEC002,18,Engineering: Industrial,,53706,pineapple,No,Yes,no preference,Maybe
-LEC002,20,Other,Communication Arts,53711,sausage,Yes,Yes,no preference,Maybe
-LEC002,21,Business: Information Systems,Finance ,53703,pepperoni,Yes,Yes,night owl,Maybe
-LEC002,21,Science: Physics,Astrophysics,,macaroni/pasta,Yes,No,no preference,Maybe
-LEC002,21,Science: Biology/Life,,53703,green pepper,Yes,No,early bird,Maybe
-LEC003,21,Engineering: Other,,53706,none (just cheese),Yes,No,early bird,Maybe
-LEC002,19,Data Science,Economics,53715,pepperoni,Yes,No,night owl,Yes
-LEC001,19,Data Science,,53706,none (just cheese),No,Yes,night owl,Yes
-LEC001,20,Statistics,"economics, social science",53715,pepperoni,No,No,no preference,Yes
-LEC004,19,Business: Other,"Information systems, Data science",53706,sausage,Yes,Yes,night owl,Yes
-LEC004,18,Computer Science,,53706,basil/spinach,Yes,No,no preference,Yes
-LEC003,18,Computer Science,,53703,pepperoni,Yes,No,night owl,Yes
-LEC003,,Mathematics/AMEP,,,mushroom,No,Yes,night owl,Yes
-LEC004,19,Data Science,,53706,mushroom,Yes,No,night owl,Yes
-LEC001,19,Science: Chemistry,Data Science,53706,sausage,Yes,No,night owl,No
-LEC002,19,Mathematics/AMEP,,53703,Other,No,No,night owl,Yes
-LEC003,18,Other,,53703,pineapple,No,No,early bird,No
-LEC004,19,Engineering: Mechanical,,53703,pepperoni,Yes,No,early bird,Yes
-LEC003,19,Statistics,thinking about a data science certificate or switching major to data science,53706,pepperoni,Yes,No,night owl,Yes
-LEC001,19,Other,,53706,pepperoni,Yes,Yes,night owl,Maybe
-LEC003,18,Statistics,data science,53706,pineapple,No,No,night owl,Maybe
-LEC003,21,Computer Science,,53705,mushroom,Yes,No,night owl,Maybe
-LEC002,21,Other,Data Science,53705,sausage,Yes,No,night owl,Yes
-LEC003,20,Science: Biology/Life,,53703,pineapple,No,No,early bird,Maybe
-LEC003,18,Other,,53715,pepperoni,Yes,No,early bird,No
-LEC004,18,Engineering: Biomedical,,53706,pepperoni,Yes,Yes,early bird,Yes
-LEC001,21,Computer Science,,53715,macaroni/pasta,Yes,No,night owl,Yes
-LEC003,21,Science: Other,Data Science,53711,mushroom,Yes,Yes,night owl,Yes
-LEC004,19,Engineering: Mechanical,,,sausage,No,No,early bird,No
-LEC002,20,Engineering: Industrial,,53715,mushroom,No,No,night owl,Yes
-LEC002,19,Engineering: Mechanical,,53706,pepperoni,Yes,No,no preference,No
-LEC002,22,Science: Physics,,53703,sausage,Yes,No,night owl,Yes
-LEC004,19,Engineering: Other,,53706,sausage,Yes,Yes,no preference,Maybe
-LEC001,19,Engineering: Biomedical,,53711,macaroni/pasta,Yes,No,night owl,Yes
-LEC001,23,Data Science,,53703,mushroom,Yes,Yes,night owl,Maybe
-LEC001,20,Engineering: Industrial,,53703,pepperoni,Yes,No,night owl,Yes
-LEC003,18,Science: Other,,53706,pineapple,Yes,Yes,night owl,Yes
-LEC003,25,Computer Science,,53713,sausage,Yes,No,night owl,Yes
-LEC001,31,Data Science,,53575,sausage,Yes,Yes,early bird,Maybe
-LEC001,19,Data Science,,53715,pepperoni,Yes,Yes,night owl,Yes
-LEC002,21,Computer Science,,53703,pepperoni,Yes,No,night owl,Yes
-LEC003,20,Business: Actuarial,Risk Management and Insurance,53715,pepperoni,Yes,No,night owl,No
-LEC004,19,Data Science,,53715,pepperoni,Yes,Yes,night owl,Yes
-LEC001,19,Computer Science,,53706,mushroom,Yes,No,early bird,Maybe
-LEC001,19,Mathematics/AMEP,,,pepperoni,Yes,No,night owl,Maybe
-LEC001,19,Engineering: Mechanical,,53705,sausage,Yes,No,night owl,Yes
-LEC004,19,Engineering: Mechanical,,53706,pineapple,Yes,No,night owl,Yes
-LEC002,19,Science: Physics,,53706,Other,Yes,No,no preference,Yes
-LEC001,21,Computer Science,Data science,53703,basil/spinach,No,Yes,night owl,No
-LEC003,19,Mathematics/AMEP,data science,53706,sausage,Yes,No,night owl,Yes
-LEC002,18,Science: Biology/Life,data science certificate,53706,pineapple,Yes,Yes,night owl,Yes
-LEC004,18,Statistics,,53706,sausage,No,Yes,night owl,Yes
-LEC003,21,Engineering: Industrial,,53562,pepperoni,Yes,No,night owl,Maybe
-LEC001,20,Engineering: Mechanical,,53715,green pepper,Yes,No,early bird,Yes
-LEC003,19,Engineering: Mechanical,,,pineapple,No,No,early bird,No
-LEC003,20,Statistics,,53703,mushroom,Yes,Yes,no preference,No
-LEC002,18,Engineering: Mechanical,"Industrial, Buisness",53701,pepperoni,No,No,night owl,Maybe
-LEC001,18,Other,Legal Studies,53706,mushroom,No,No,night owl,Yes
-LEC001,20,Data Science,,53703,none (just cheese),Yes,Yes,night owl,Yes
-LEC001,21,Other,,53703,Other,Yes,Yes,no preference,Maybe
-LEC001,22,Engineering: Biomedical,pre-med,53715,none (just cheese),Yes,Yes,no preference,Yes
-LEC003,20,Other,"Philosophy, Data Science Certificate, Pre-Med",53703,basil/spinach,No,Yes,early bird,Yes
-LEC001,21,Business: Finance,Economics,53703,basil/spinach,Yes,No,night owl,Yes
-LEC003,19,Statistics,,53705,none (just cheese),Yes,Yes,no preference,Yes
-LEC001,18,Engineering: Industrial,,53703,sausage,Yes,Yes,night owl,Yes
-LEC003,21,Science: Biology/Life,My majors are Environmental Science and Spanish,53703,macaroni/pasta,Yes,No,night owl,Maybe
-LEC001,18,Other,,,pepperoni,Yes,No,no preference,Yes
-LEC004,23,Science: Physics,Astronomy,53703,pepperoni,Yes,Yes,night owl,Yes
-LEC002,21,Computer Science,,53711,sausage,Yes,No,night owl,Maybe
-LEC002,18,Engineering: Mechanical,,53706,sausage,Yes,Yes,early bird,Yes
-LEC003,19,Engineering: Other,Environmental Science,53706,pepperoni,Yes,No,night owl,Yes
-LEC003,19,Science: Other,Life science communications,53706,Other,Yes,No,night owl,Maybe
-LEC004,21,Engineering: Mechanical,,53703,sausage,Yes,Yes,no preference,No
-LEC001,20,Computer Science,,53703,pineapple,Yes,No,night owl,Yes
-LEC001,20,Other,,53703,macaroni/pasta,Yes,Yes,night owl,Yes
-LEC001,22,Other,"psychology, legal studies, certificate in criminal justice ",53711,sausage,Yes,No,night owl,Maybe
-LEC002,21,Data Science,,53711,none (just cheese),Yes,No,night owl,Yes
-LEC003,21,Other,,53703,mushroom,Yes,No,early bird,Yes
-LEC002,20,Engineering: Industrial,,53703,pineapple,Yes,Yes,early bird,Yes
-LEC001,19,Computer Science,data science,53706,pineapple,No,No,night owl,No
-LEC003,19,Statistics,Data Science,53703,pineapple,No,No,night owl,Maybe
-LEC001,20,Computer Science,,53726,none (just cheese),Yes,No,night owl,Yes
-LEC002,,Computer Science,,,pepperoni,Yes,No,night owl,Maybe
-LEC001,18,Computer Science,,53706,pineapple,No,No,no preference,Maybe
-LEC001,19,Computer Science,data science,53706,pepperoni,Yes,Yes,night owl,Yes
-LEC003,19,Other,Undecided in STEM,53706,pepperoni,No,No,night owl,No
-LEC001,18,Computer Science,data science,53590,Other,No,No,night owl,Yes
-LEC004,18,Other,,53706,Other,Yes,No,night owl,Maybe
-LEC003,19,Data Science,,53706,basil/spinach,Yes,No,no preference,Maybe
-LEC001,19,Business: Finance,,53706,pepperoni,Yes,No,night owl,Maybe
-LEC001,19,Engineering: Industrial,,53704,basil/spinach,No,No,no preference,Yes
-LEC004,18,Engineering: Other,,53706,pepperoni,Yes,No,night owl,Maybe
-LEC002,18,Computer Science,,,macaroni/pasta,Yes,Yes,night owl,Yes
-LEC003,20,Engineering: Biomedical,,53715,none (just cheese),Yes,Yes,no preference,Maybe
-LEC001,18,Other,,52816,none (just cheese),Yes,No,night owl,Yes
-LEC002,18,Engineering: Mechanical,Computes Science Certificate Potentially,53706,sausage,Yes,Yes,night owl,Yes
-LEC002,18,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,no preference,No
-LEC003,20,Business: Finance,Business: Risk Management ,53703,sausage,Yes,Yes,night owl,Yes
-LEC001,19,Science: Chemistry,,53706,pineapple,Yes,No,night owl,Yes
-LEC001,20,Engineering: Mechanical,,59301,pepperoni,Yes,Yes,no preference,Maybe
-LEC001,22,Mathematics/AMEP,Economics ,53715,basil/spinach,Yes,Yes,early bird,No
-LEC001,22,Other,,53703,green pepper,Yes,Yes,night owl,Yes
-LEC001,19,Engineering: Other,,53715,none (just cheese),Yes,Yes,night owl,No
-LEC002,18,Engineering: Mechanical,,53706,sausage,Yes,Yes,night owl,Yes
-LEC001,23,Engineering: Other,,53711,green pepper,Yes,Yes,no preference,Maybe
-LEC001,18,Science: Chemistry,,53706,sausage,Yes,Yes,night owl,No
-LEC001,23,Engineering: Mechanical,,53715,pepperoni,Yes,Yes,night owl,Maybe
-LEC002,19,Data Science,Economics,53706,macaroni/pasta,No,No,early bird,Yes
-LEC001,20,Engineering: Industrial,"Science: Other, Economics",53703,sausage,Yes,Yes,early bird,No
-LEC003,21,Data Science,"Economics, Social Science",53703,sausage,Yes,Yes,no preference,Maybe
-LEC002,18,Data Science,,10306,none (just cheese),Yes,No,night owl,Maybe
-LEC002,20,Mathematics/AMEP,Environmental Sciences,53715,pepperoni,No,No,night owl,Maybe
-LEC002,18,Statistics,,53706,pepperoni,Yes,No,night owl,Maybe
-LEC003,21,Engineering: Mechanical,,53715,pepperoni,Yes,Yes,night owl,Yes
-LEC002,20,Engineering: Biomedical,,53703,pepperoni,Yes,No,night owl,Yes
-LEC002,19,Data Science,,53703,pineapple,Yes,No,no preference,Yes
-LEC001,21,Engineering: Other,,53715,mushroom,No,No,early bird,Maybe
-LEC003,18,Data Science,possibly Statistics / Math,53706,mushroom,Yes,No,night owl,Yes
-LEC002,,Business: Other,,,pepperoni,Yes,No,early bird,No
-LEC002,19,Other,,53706,pepperoni,Yes,No,night owl,Yes
-LEC001,19,Engineering: Other,,53706,pineapple,Yes,No,night owl,Maybe
-LEC003,19,Computer Science,data science I havent decided on a major yet but it might be either one of these,53726,none (just cheese),No,No,night owl,Maybe
-LEC003,20,Business: Finance,,53703,Other,Yes,No,night owl,Yes
-LEC001,21,Science: Other,,53703,sausage,No,No,night owl,Yes
-LEC001,20,Other,,53703,pepperoni,No,No,night owl,Yes
-LEC004,20,Engineering: Other,,53703,none (just cheese),Yes,No,night owl,Yes
-LEC001,21,Business: Information Systems,,53703,Other,Yes,Yes,no preference,No
-LEC003,21,Mathematics/AMEP,,,mushroom,No,No,night owl,Yes
-LEC001,18,Other,,53703,mushroom,Yes,No,night owl,Yes
-LEC003,19,Business: Actuarial,,53175,sausage,Yes,Yes,early bird,Yes
-LEC003,20,Engineering: Mechanical,Naval Architecture & Marnie Engineering (self-tutored),53711,green pepper,Yes,No,night owl,Maybe
-LEC002,20,Business: Other,,53703,pineapple,Yes,No,night owl,Maybe
-LEC003,20,Data Science,"computer science, stats ",53711,pineapple,Yes,No,early bird,Yes
-LEC004,19,Statistics,,53706,pepperoni,Yes,No,night owl,Yes
-LEC003,18,Engineering: Industrial,Data science ,53715,pepperoni,No,Yes,early bird,Maybe
-LEC004,20,Other,"Economics, Data Science",53715,mushroom,Yes,No,no preference,Maybe
-LEC001,19,Engineering: Mechanical,,53706,sausage,Yes,Yes,night owl,Yes
-LEC002,21,Engineering: Mechanical,Spanish,53719,none (just cheese),Yes,Yes,night owl,Maybe
-LEC001,24,Engineering: Industrial,Business,53726,mushroom,Yes,No,night owl,Maybe
-LEC002,20,Other,NA,53703,basil/spinach,Yes,Yes,night owl,Yes
-LEC004,18,Engineering: Mechanical,,53706,sausage,Yes,Yes,early bird,Yes
-LEC001,19,Other,"Data Science Certificate, Economics",53703,sausage,No,Yes,night owl,Yes
-LEC001,18,Engineering: Mechanical,,53706,pepperoni,No,No,night owl,Yes
-LEC003,18,Engineering: Mechanical,,53706,pepperoni,Yes,Yes,night owl,Yes
-LEC004,19,Engineering: Biomedical,,53706,none (just cheese),Yes,No,no preference,Yes
-LEC001,20,Computer Science,,53715,sausage,Yes,No,night owl,Yes
-LEC001,17,Engineering: Mechanical,,53706,pineapple,Yes,No,night owl,Yes
-LEC002,20,Data Science,,53703,pepperoni,Yes,Yes,night owl,Yes
-LEC003,18,Engineering: Mechanical,,53715,pineapple,No,No,night owl,Maybe
-LEC003,19,Engineering: Biomedical,,53703,none (just cheese),Yes,Yes,night owl,Yes
-LEC003,20,Other,Data Science,53715,mushroom,Yes,Yes,early bird,Maybe
-LEC003,19,Mathematics/AMEP,,53705,pineapple,No,No,night owl,Yes
-LEC002,19,Engineering: Mechanical,chemical engineering,53711,green pepper,Yes,No,night owl,Maybe
-LEC003,21,Computer Science,Data Science,53715,mushroom,No,No,night owl,Maybe
-LEC003,19,Data Science,,53590,pepperoni,No,No,no preference,Yes
-LEC001,20,Computer Science,,,pepperoni,Yes,No,early bird,Yes
-LEC001,20,Data Science,"Biology, Bioinformatics",53703,sausage,Yes,No,no preference,Yes
-LEC002,21,Engineering: Mechanical,,53705,none (just cheese),Yes,No,no preference,Maybe
-LEC001,19,Computer Science,Data Science,53706,Other,No,Yes,night owl,No
-LEC001,20,Business: Finance,Data Science,53715,sausage,Yes,Yes,night owl,Yes
-LEC001,19,Data Science,Computer science,53706,pineapple,No,Yes,no preference,Yes
-LEC002,23,Science: Other,Computer Science,53711,pineapple,Yes,Yes,early bird,No
-LEC003,18,Engineering: Mechanical,,53706,sausage,No,No,night owl,No
-LEC001,19,Computer Science,Data Science,53703,Other,No,No,no preference,Maybe
-LEC001,19,Science: Other,,53706,macaroni/pasta,Yes,No,night owl,Yes
-LEC003,19,Other,I do not have a secondary major but my major is International Studies. ,53076,pepperoni,Yes,Yes,early bird,Yes
-LEC001,21,Science: Biology/Life,,53715,pepperoni,Yes,No,night owl,Yes
-LEC001,20,Engineering: Mechanical,,53726,pepperoni,Yes,No,night owl,Yes
-LEC002,20,Engineering: Industrial,,53715,pepperoni,Yes,No,no preference,Yes
-LEC003,20,Science: Biology/Life,Life Science Communication,53703,pepperoni,Yes,No,early bird,Maybe
-LEC002,19,Science: Biology/Life,Data Science,,pepperoni,No,No,no preference,Maybe
-LEC002,22,Computer Science,,53703,sausage,Yes,No,night owl,Yes
-LEC001,20,Business: Information Systems,,53706,mushroom,Yes,No,night owl,Yes
-LEC001,19,Business: Other,,53706,pepperoni,Yes,No,early bird,Yes
-LEC001,21,Other,"Economics/Philosophy, Data Science Certificate",53703,pepperoni,Yes,No,no preference,Yes
-LEC003,19,Computer Science,Data science,53706,pineapple,Yes,Yes,night owl,Yes
+Lecture,Age,Major,Zip Code,Latitude,Longitude,Pizza topping,Pet preference,Runner,Sleep habit,Procrastinator
+LEC001,22,Engineering: Biomedical,53703,43.073051,-89.40123,none (just cheese),neither,No,no preference,Maybe
+LEC006,,Undecided,53706,43.073051,-89.40123,none (just cheese),neither,No,no preference,Maybe
+LEC004,18,Engineering: Industrial,53715,43.073051,-89.40123,none (just cheese),neither,No,no preference,Maybe
+LEC005,,Undecided,53706,43.073051,-89.40123,none (just cheese),neither,No,no preference,Maybe
+LEC002,,Undecided,53706,43.073051,-89.40123,none (just cheese),neither,No,no preference,Maybe
+LEC004,18,Engineering: Other|Engineering: Computer,53706,43.073051,-89.40123,none (just cheese),neither,No,no preference,Maybe
+LEC003,,Undecided,53706,43.073051,-89.40123,none (just cheese),neither,No,no preference,Maybe
+LEC003,18,Data Science,53715,43.073051,-89.40123,pineapple,cat,Yes,no preference,Maybe
+LEC006,18,Data Science,53706,35.4,119.11,none (just cheese),dog,No,night owl,Yes
+LEC006,18,Mathematics/AMEP,53706,44,-93,pepperoni,dog,No,night owl,Yes
+LEC002,21,Engineering: Other,53703,24.713552,46.675297,none (just cheese),cat,Yes,night owl,Maybe
+LEC003,19,Data Science,53705,24.6806,46.57936,pineapple,cat,No,early bird,No
+LEC004,24,Economics,53703,43,-89,pineapple,cat,Yes,early bird,Yes
+LEC003,18,Data Science,53706,36.102371,-115.174553,none (just cheese),dog,No,night owl,Yes
+LEC006,22,Psychology,53703,31.78,119.95,mushroom,cat,No,night owl,Yes
+LEC005,20,Data Science,53705,37.8,112.5,pepperoni,cat,Yes,night owl,Yes
+LEC004,24,Science: Biology/Life,53703,46.872131,-113.994019,pepperoni,dog,Yes,early bird,Yes
+LEC004,17,Engineering: Mechanical,53706,46.6242,8.0414,pineapple,dog,No,night owl,Yes
+LEC004,19,Engineering: Mechanical,53726,43.073051,-89.40123,none (just cheese),dog,Yes,early bird,No
+LEC002,19,Engineering: Mechanical,57303,41.878113,-87.629799,pineapple,dog,No,night owl,Yes
+LEC001,,Mathematics/AMEP,53706,31.230391,121.473701,basil/spinach,dog,No,no preference,Maybe
+LEC002,19,Mathematics/AMEP,53558,40.712776,-74.005974,sausage,dog,Yes,night owl,Yes
+LEC001,20,Economics (Mathematical Emphasis),53703,48.86,2.3522,pepperoni,dog,No,early bird,Yes
+LEC001,19,Engineering: Mechanical,53703,24.7,46.7,mushroom,dog,Yes,early bird,Maybe
+LEC005,18,Computer Science,53703,37.338207,-121.88633,green pepper,dog,Yes,night owl,Yes
+LEC003,19,Engineering: Mechanical,53558,43.073051,-89.40123,pepperoni,dog,No,night owl,Yes
+LEC005,20,Engineering: Mechanical,53715,38.9072,-77.0369,Other,cat,No,night owl,Yes
+LEC003,20,Data Science,53703,43.073051,-89.40123,pepperoni,dog,No,night owl,Yes
+LEC002,21,Science: Other|Political Science,53703,31.768318,35.213711,pepperoni,dog,No,no preference,Maybe
+LEC003,19,Mathematics/AMEP,53715,19.075983,72.877655,basil/spinach,cat,No,night owl,Maybe
+LEC001,23,Computer Science,53711,43.073929,-89.385239,sausage,dog,No,night owl,Yes
+LEC006,21,Business: Other,53715,25.761681,-80.191788,pepperoni,dog,No,night owl,Yes
+LEC003,19,Business: Other|Real Estate,53715,117,33,pepperoni,dog,Yes,night owl,No
+LEC004,19,Computer Science,53726,47.037872,-122.900696,tater tots,dog,No,night owl,Yes
+LEC004,24,Economics,53703,23.12911,113.264381,pepperoni,cat,Yes,early bird,Maybe
+LEC005,19,Data Science,53703,64.49796,165.40998,sausage,dog,No,night owl,Yes
+LEC003,19,Data Science,53705,25,47,mushroom,cat,No,early bird,Maybe
+LEC005,20,Engineering: Other|Engineering Physics: Scientific Computing,53715,43.073051,-89.4,none (just cheese),dog,No,night owl,Yes
+LEC005,20,Computer Science,53703,48.856613,2.352222,pepperoni,dog,No,night owl,Yes
+LEC002,19,Business: Finance,53726,43.04156,87.91006,pepperoni,dog,No,night owl,Yes
+LEC002,21,Data Science,53713,29.868336,121.543991,mushroom,dog,No,night owl,No
+LEC004,19,Computer Science,53715,40.712776,-74.005974,pepperoni,dog,No,night owl,Maybe
+LEC003,18,Computer Science,53706,5.93876,80.48433,Other,dog,No,night owl,Maybe
+LEC005,19,Engineering: Mechanical,53704,38.7,-77,pepperoni,cat,Yes,no preference,No
+LEC004,18,Engineering: Mechanical,53726,41.878113,-87.629799,pepperoni,dog,No,night owl,Maybe
+LEC005,19,Engineering: Other,53703,36.169941,-115.139832,pepperoni,dog,No,night owl,Maybe
+LEC005,19,Engineering: Mechanical,53703,43.078104,-89.431698,pepperoni,dog,Yes,night owl,Yes
+LEC006,18,Engineering: Biomedical,53051,33.6846,117.8265,pepperoni,dog,Yes,night owl,Yes
+LEC001,22,Engineering: Mechanical,53719,43.073051,-89.40123,none (just cheese),cat,Yes,night owl,Yes
+LEC001,18,Computer Science,53706,26.2992,87.2625,mushroom,dog,Yes,night owl,No
+LEC001,24,Business: Information Systems,53703,43.073051,-89.40123,macaroni/pasta,cat,No,night owl,No
+LEC006,19,Engineering: Mechanical,53703,43.04049,-87.91732,Other,dog,No,night owl,Yes
+LEC001,,Computer Science,53715,34.052235,-118.243683,green pepper,dog,No,night owl,Yes
+LEC002,20,Statistics,53703,40.7128,74.006,Other,dog,No,night owl,Maybe
+LEC005,23,Computer Science,53703,37.5,126.97,pepperoni,dog,No,night owl,No
+LEC002,21,Statistics,53703,52.370216,4.895168,pepperoni,dog,Yes,early bird,Maybe
+LEC002,18,Undecided,53706,38.56247,-121.70411,pepperoni,dog,Yes,night owl,Yes
+LEC006,18,Statistics,53706,40.712776,40.712776,pepperoni,dog,No,night owl,Yes
+LEC003,21,Economics,53715,43.073051,-89.40123,none (just cheese),dog,No,night owl,Yes
+LEC003,19,Engineering: Mechanical,53715,45,-93,sausage,dog,No,night owl,No
+LEC005,21,Business: Finance,53717,40.6461,-111.498,sausage,dog,No,night owl,Yes
+LEC001,26,Engineering: Mechanical,53703,41.902782,12.496365,pepperoni,dog,No,night owl,Yes
+LEC001,25,Economics,53703,40.712776,-74.005974,pepperoni,dog,No,night owl,Yes
+LEC003,18,Mathematics/AMEP,53706,31.230391,121.473701,mushroom,dog,Yes,early bird,No
+LEC001,19,Computer Science,53706,48.855709,2.29889,pepperoni,cat,Yes,night owl,Yes
+LEC005,17,Science: Biology/Life,53706,-18.766947,46.869106,basil/spinach,dog,Yes,early bird,Maybe
+LEC003,19,Business: Information Systems,53711,38.893452,-77.014709,pepperoni,dog,No,early bird,Yes
+LEC001,21,Computer Science,53715,16.306652,80.436539,Other,dog,No,night owl,Yes
+LEC006,19,Data Science,53703,35.689487,139.691711,sausage,neither,Yes,no preference,Maybe
+LEC004,18,Engineering: Industrial,53706,17.385044,78.486671,mushroom,dog,No,early bird,Yes
+LEC004,19,Computer Science,53715,37.774929,-122.419418,pepperoni,dog,No,night owl,Maybe
+LEC004,19,Data Science,53703,26.2644,20.3052,pepperoni,dog,No,night owl,Yes
+LEC005,18,Data Science,53706,40.712776,-74.005974,pepperoni,dog,Yes,no preference,Yes
+LEC002,18,Data Science,53706,36,117,Other,dog,No,early bird,Maybe
+LEC005,19,Data Science,50703,42.360081,-71.058884,sausage,cat,No,night owl,No
+LEC006,19,Computer Science,53711,36.569666,112.218744,pineapple,neither,Yes,early bird,Maybe
+LEC005,18,Computer Science,53706,37.54443,-121.95269,pepperoni,dog,No,night owl,Maybe
+LEC003,20,Mathematics/AMEP,53715,32.0853,34.781769,mushroom,dog,No,no preference,Yes
+LEC003,19,Data Science,53715,42.701847,-84.48217,tater tots,dog,No,night owl,Yes
+LEC003,18,Mathematics/AMEP,53706,40.179188,44.499104,Other,dog,Yes,no preference,Yes
+LEC002,,Computer Science,53711,2.81375,101.504272,sausage,dog,Yes,no preference,Maybe
+LEC001,18,Engineering: Industrial,53715,30.733315,76.779419,green pepper,cat,No,no preference,Yes
+LEC003,21,Data Science,53590,7.9519,98.3381,Other,dog,Yes,early bird,Yes
+LEC004,19,Data Science,53715,35.69,139.69,mushroom,dog,No,no preference,Maybe
+LEC002,19,Data Science,53704,26.473308,50.048218,Other,cat,Yes,night owl,Yes
+LEC002,22,Economics,53703,34.052235,-118.243683,pineapple,dog,No,night owl,Yes
+LEC006,18,Data Science,53706,19.075983,72.877655,mushroom,dog,Yes,night owl,Yes
+LEC003,,Business: Actuarial,53705,39.6336,118.16,basil/spinach,dog,Yes,early bird,Yes
+LEC003,18,Data Science,53706,52.370216,4.895168,mushroom,cat,Yes,no preference,No
+LEC003,18,Engineering: Mechanical,53706,52.368944,4.891663,pepperoni,cat,No,night owl,No
+LEC002,18,Science: Physics,53703,32,118,sausage,neither,No,night owl,No
+LEC005,18,Data Science,53706,17.384716,78.409424,mushroom,dog,Yes,night owl,Maybe
+LEC003,19,Data Science,53715,3.1569,101.7123,mushroom,cat,No,early bird,No
+LEC005,18,Computer Science,53706,43.769562,11.255814,Other,neither,No,night owl,Yes
+LEC006,18,Business: Actuarial,53706,48.856613,2.352222,mushroom,cat,No,no preference,Yes
+LEC004,20,Business: Actuarial,53711,40.7128,74.006,pepperoni,dog,Yes,early bird,No
+LEC005,20,Science: Biology/Life,53703,44.67082,-93.24432,mushroom,dog,No,no preference,Maybe
+LEC004,18,Mathematics/AMEP,53706,46.786671,-92.100487,pepperoni,cat,No,early bird,Yes
+LEC005,20,Economics,53703,48.856613,2.352222,pepperoni,neither,No,night owl,Maybe
+LEC006,18,Business: Finance,53706,40.409264,49.867092,Other,neither,No,early bird,No
+LEC004,21,Computer Science,53715,27.993828,120.699364,green pepper,dog,Yes,no preference,No
+LEC002,,Computer Science,53706,43.073051,-89.40123,Other,neither,Yes,no preference,Maybe
+LEC002,20,Engineering: Mechanical,53706,35.6762,139.6503,sausage,cat,Yes,night owl,Yes
+LEC001,20,Economics (Mathematical Emphasis),53703,43.073929,-89.385239,macaroni/pasta,cat,No,night owl,No
+LEC002,21,Business: Information Systems,53713,43.03638,-89.40292,pineapple,neither,Yes,night owl,Yes
+LEC004,18,Data Science,53706,45.31625,-92.59181,pepperoni,dog,No,night owl,Yes
+LEC001,21,Business: Finance,53711,43.073929,-89.385239,pepperoni,dog,No,no preference,Maybe
+LEC005,19,Engineering: Mechanical,53715,35.689487,139.691711,pepperoni,dog,No,night owl,Yes
+LEC003,18,Computer Science,53706,51.500153,-0.1262362,pepperoni,dog,No,night owl,Yes
+LEC002,22,Science: Biology/Life,53711,43.073051,-89.40123,mushroom,cat,No,no preference,No
+LEC004,18,Data Science,53706,42.360081,-71.058884,green pepper,dog,No,night owl,Yes
+LEC005,19,Engineering: Mechanical,53703,32.8328,117.2713,sausage,neither,Yes,night owl,Yes
+LEC003,20,Engineering: Mechanical,53715,44.834,-87.376,none (just cheese),dog,Yes,night owl,No
+LEC006,21,Economics,53703,41.902782,12.496365,none (just cheese),dog,No,no preference,Yes
+LEC003,25,Data Science,53703,34.693737,135.502167,pineapple,dog,No,early bird,Maybe
+LEC003,17,Computer Science,53703,19.075983,72.877655,Other,neither,Yes,no preference,No
+LEC002,19,Psychology,53715,30.5928,114.3052,sausage,cat,No,night owl,Yes
+LEC001,19,Computer Science,53703,51.507351,-0.127758,sausage,cat,Yes,no preference,Yes
+LEC006,17,Engineering: Industrial,53706,55.953251,-3.188267,Other,dog,No,night owl,Yes
+LEC005,,Computer Science,53703,43.073051,-89.40123,pineapple,dog,Yes,night owl,No
+LEC002,21,Engineering: Mechanical,53705,37.566536,126.977966,mushroom,cat,Yes,no preference,Maybe
+LEC002,18,Undecided,53715,48.775845,9.182932,Other,dog,No,night owl,Yes
+LEC004,19,Data Science,53703,43,-89,sausage,cat,No,early bird,Maybe
+LEC001,21,Science: Biology/Life,53703,36,117,macaroni/pasta,dog,No,night owl,Maybe
+LEC002,19,Business: Information Systems,53703,42.360081,-71.058884,pepperoni,dog,No,no preference,Yes
+LEC005,19,Computer Science,53706,-8.340539,115.091949,pineapple,dog,Yes,night owl,Maybe
+LEC003,20,Business: Information Systems,53726,43.073051,-89.40123,sausage,dog,Yes,night owl,No
+LEC003,,Science: Other,53715,39.904202,116.407394,mushroom,cat,No,night owl,Maybe
+LEC004,20,Engineering: Biomedical,53715,43.0707,12.6196,tater tots,dog,No,night owl,Maybe
+LEC004,19,Engineering: Biomedical,53715,41.878113,-87.629799,mushroom,dog,Yes,night owl,Yes
+LEC002,21,Business: Other|Accounting,53703,41.8781,87.6298,pepperoni,cat,No,night owl,No
+LEC002,17,Undecided,53706,33.742185,-84.386124,Other,dog,No,no preference,Yes
+LEC006,18,Data Science,53558,40.73061,-73.935242,pepperoni,dog,Yes,night owl,No
+LEC003,25,Data Science,53705,43.073051,-89.385239,sausage,cat,No,night owl,Maybe
+LEC002,18,Data Science,53706,37.34163,-122.05411,sausage,dog,No,night owl,Yes
+LEC006,18,Science: Biology/Life,53706,19.21833,72.978088,green pepper,neither,No,no preference,Maybe
+LEC002,,Business: Other|business analytics,53703,31.230391,121.473701,none (just cheese),cat,Yes,night owl,Maybe
+LEC003,,Data Science,53706,35.719312,139.784546,none (just cheese),neither,Yes,night owl,Yes
+LEC002,19,Engineering: Mechanical,53726,47.141041,9.52145,mushroom,dog,No,night owl,Yes
+LEC002,,Computer Science,53715,41.8781,87.6298,pepperoni,dog,No,no preference,Maybe
+LEC002,26,Science: Other|animal sciences,53705,25.204849,55.270782,pepperoni,dog,No,no preference,Maybe
+LEC003,21,Mathematics,53704,61.218056,-149.900284,green pepper,cat,Yes,early bird,Maybe
+LEC003,22,Engineering: Other,53703,49.28273,-123.120735,macaroni/pasta,cat,No,early bird,Maybe
+LEC001,18,Engineering: Other,53706,41.902782,12.496365,pepperoni,dog,No,night owl,Yes
+LEC003,20,Engineering: Mechanical,53726,39.81059,-74.71795,basil/spinach,dog,No,early bird,Yes
+LEC003,21,Health Promotion and Health Equity,53711,37.2982,113.0263,pepperoni,dog,No,early bird,No
+LEC003,20,Engineering: Mechanical,53703,38.722252,-9.139337,mushroom,dog,No,night owl,Yes
+LEC003,19,Engineering: Mechanical,53714,43,-89.4,none (just cheese),dog,No,night owl,Yes
+LEC002,19,Engineering: Industrial,53703,41.878,-87.63,pepperoni,dog,Yes,night owl,Yes
+LEC003,18,Computer Science,53706,43.073051,-89.40123,mushroom,neither,No,night owl,Yes
+LEC001,18,Engineering: Industrial,53706,19.655041,-101.169891,pepperoni,dog,Yes,no preference,Maybe
+LEC005,20,Engineering: Mechanical,53703,26.147,-81.795,pepperoni,dog,Yes,early bird,Yes
+LEC006,18,Business: Other,53706,51.507,-0.128,sausage,dog,No,no preference,No
+LEC005,19,Business: Other,53706,43,-89,pepperoni,dog,Yes,no preference,Yes
+LEC004,19,Engineering: Mechanical,53705,34.869709,-111.760902,pepperoni,cat,No,no preference,Maybe
+LEC005,21,Business: Finance,53703,3.15443,101.715103,pepperoni,cat,No,night owl,Yes
+LEC005,18,Engineering: Mechanical,53706,44.655991,-93.242752,none (just cheese),dog,Yes,night owl,Yes
+LEC003,18,Art,53706,36.25,138.25,macaroni/pasta,dog,No,night owl,Yes
+LEC005,19,Data Science,53715,41.94288,-87.68667,pepperoni,dog,Yes,night owl,Yes
+LEC005,18,Data Science,53703,44.2795,73.9799,pepperoni,dog,Yes,night owl,No
+LEC002,19,Mathematics/AMEP,53715,37.80718,23.734864,pineapple,cat,No,night owl,Yes
+LEC004,18,Computer Science,53706,35.689487,139.691711,pepperoni,cat,No,night owl,Yes
+LEC006,18,Engineering: Mechanical,53706,43.0826,-97.16051,pepperoni,dog,No,no preference,Yes
+LEC006,18,Engineering: Other,53715,37.441883,-122.143021,mushroom,dog,Yes,night owl,Maybe
+LEC006,18,Engineering: Mechanical,53706,44.883,-87.86291,pepperoni,dog,No,early bird,Yes
+LEC004,19,Engineering: Mechanical,53706,40.73598,-74.37531,none (just cheese),dog,Yes,early bird,No
+LEC001,20,Business: Actuarial,53703,42.28,-83.74,mushroom,dog,No,night owl,Yes
+LEC003,17,Engineering: Mechanical,53706,37.98381,23.727539,pineapple,dog,Yes,night owl,No
+LEC004,18,Computer Science,53706,40.27385,-74.75972,sausage,dog,Yes,night owl,Yes
+LEC002,19,Economics,53703,90.1994,38.627,none (just cheese),dog,No,early bird,Yes
+LEC002,21,"Mathematics, Data Science",53703,30.572815,104.066803,sausage,dog,No,night owl,Maybe
+LEC002,,Computer Science,53717,36,139,mushroom,dog,Yes,early bird,Yes
+LEC006,19,Science: Biology/Life,53715,45.289143,-87.021847,none (just cheese),cat,No,night owl,Maybe
+LEC002,21,Mathematics/AMEP,53703,20.878332,-156.682495,pepperoni,cat,No,night owl,Yes
+LEC003,22,Mathematics/AMEP,53715,44.481586,-88.005981,pepperoni,neither,No,night owl,Yes
+LEC006,18,Data Science,53706,43.073051,-89.40123,pepperoni,dog,No,night owl,Yes
+LEC005,18,Computer Science,53706,30.733315,76.779419,none (just cheese),dog,No,night owl,Yes
+LEC005,20,Mathematics/AMEP,53703,38.837702,-238.449497,pepperoni,dog,No,night owl,Yes
+LEC005,,Computer Science,53593,50.116322,-122.957359,sausage,dog,No,night owl,Yes
+LEC005,18,Computer Science,53715,43.059023,-89.296875,pepperoni,cat,No,night owl,Maybe
+LEC005,19,Engineering: Industrial,53703,22.2255,-159.4835,pepperoni,cat,Yes,night owl,Yes
+LEC005,18,Engineering: Biomedical,53593,43.073051,-89.40123,green pepper,cat,No,night owl,Maybe
+LEC005,20,Engineering: Mechanical,53715,41.283211,-70.099228,sausage,dog,No,no preference,Maybe
+LEC005,18,Data Science,53715,25.26741,55.292679,basil/spinach,cat,Yes,early bird,Yes
+LEC005,19,Business: Other,53726,43.038902,-87.906471,pepperoni,dog,No,night owl,Yes
+LEC002,,Undecided,53703,30.5723,104.0665,sausage,dog,No,night owl,Yes
+LEC006,18,Engineering: Mechanical,53706,30.2672,97.7431,pepperoni,dog,No,night owl,No
+LEC006,20,Data Science,53703,36.731651,-119.785858,Other,dog,Yes,night owl,Yes
+LEC005,18,Computer Science,53706,43.038902,-87.906471,pepperoni,dog,No,night owl,Yes
+LEC004,,Business: Finance,53703,33.8688,151.2093,green pepper,dog,Yes,night owl,Yes
+LEC005,18,Science: Other|Science: Genetics and Genomics,53715,43.073051,-89.40123,mushroom,dog,No,no preference,Yes
+LEC003,19,Engineering: Mechanical,53715,44.90767,-93.183594,basil/spinach,dog,No,night owl,Maybe
+LEC006,18,Business: Finance,53706,-33.448891,-70.669266,macaroni/pasta,dog,No,night owl,Yes
+LEC006,17,Business: Finance,53706,43.296482,5.36978,pineapple,dog,No,night owl,Yes
+LEC006,21,Mathematics/AMEP,53703,30.572815,104.066803,green pepper,dog,No,no preference,Maybe
+LEC005,20,Engineering: Mechanical,53703,41.99884,-87.68828,Other,dog,No,no preference,No
+LEC001,19,Business: Information Systems,53703,39.481655,-106.038353,macaroni/pasta,dog,Yes,night owl,Yes
+LEC004,19,Engineering: Mechanical,53703,41.883228,-87.632401,pepperoni,dog,No,no preference,Maybe
+LEC004,18,Engineering: Industrial,53706,41.878113,41.878113,pepperoni,dog,No,night owl,No
+LEC004,19,Engineering: Mechanical,53703,28.228209,112.938812,none (just cheese),neither,Yes,early bird,Yes
+LEC003,18,Data Science,89451,34.42083,-119.698189,green pepper,dog,No,early bird,No
+LEC003,19,Computer Science,53703,41.3874,2.1686,pepperoni,cat,No,early bird,No
+LEC005,20,Science: Biology/Life,53703,32.05196,118.77803,sausage,neither,No,night owl,Yes
+LEC004,19,Engineering: Mechanical,53706,50.075539,14.4378,none (just cheese),neither,No,night owl,Yes
+LEC003,20,Statistics (actuarial route),53715,43.134315,-88.220062,sausage,dog,No,early bird,No
+LEC004,19,Computer Science,53706,17.385044,78.486671,pepperoni,neither,Yes,night owl,Yes
+LEC002,18,Engineering: Mechanical,53706,53707,-88.415382,Other,dog,No,night owl,Yes
+LEC004,19,Computer Science,53706,45.440845,12.315515,sausage,dog,No,night owl,Yes
+LEC004,18,Computer Science,53706,55.953251,-3.188267,Other,dog,No,night owl,Maybe
+LEC004,18,Engineering: Mechanical,53706,33.8902,-118.39848,sausage,dog,Yes,night owl,Yes
+LEC001,20,Business: Other|Business: Accounting,53703,31.230391,121.473701,pepperoni,cat,Yes,no preference,No
+LEC004,18,Data Science,53706,39.512611,116.677063,pepperoni,dog,No,night owl,Maybe
+LEC003,18,Undecided,53706,41.256538,95.934502,Other,dog,No,no preference,Yes
+LEC003,18,Data Science,53706,19.075983,72.877655,pepperoni,dog,No,night owl,No
+LEC003,22,Economics,53703,40.753685,-73.999161,green pepper,dog,No,night owl,Maybe
+LEC003,18,Data Science,53706,51.507351,-0.127758,pepperoni,cat,No,night owl,Yes
+LEC003,,Engineering: Mechanical,53706,42.44817,-71.224716,pepperoni,cat,Yes,night owl,Maybe
+LEC003,17,Engineering: Other|Computer Engineering,53706,42.36,-71.059,basil/spinach,neither,No,early bird,Maybe
+LEC003,21,Business: Actuarial,53706,32.715736,-117.161087,green pepper,dog,Yes,night owl,No
+LEC003,,Engineering: Other|Computer engineering,53706,35.689487,139.691711,Other,cat,No,night owl,Yes
+LEC003,18,Mathematics/AMEP,53715,41.385063,2.173404,pepperoni,cat,Yes,no preference,Maybe
+LEC003,20,Computer Science,53705,30.274084,120.155067,mushroom,cat,No,night owl,Yes
+LEC005,,Computer Science,53705,51.507351,-0.127758,basil/spinach,dog,No,night owl,Yes
+LEC003,18,Computer Science,53706,45.45676,15.29662,sausage,dog,Yes,early bird,Yes
+LEC003,18,Engineering: Industrial,53706,18.92421,-99.221565,green pepper,dog,Yes,night owl,Yes
+LEC004,18,Engineering: Other|Material Science Engineering,53703,38.941631,-119.977219,pepperoni,dog,Yes,night owl,Yes
+LEC002,21,Economics,53705,25.03841,121.5637,pepperoni,cat,No,night owl,Maybe
+LEC005,,Civil engineering - hydropower engineering,53705,34,113,pineapple,neither,No,night owl,Maybe
+LEC005,18,Computer Science,53706,40.7,-74.005,pepperoni,cat,No,early bird,No
+LEC001,19,Engineering: Mechanical,53706,35.142441,-223.154297,green pepper,neither,Yes,night owl,Yes
+LEC006,18,Data Science,53706,43.05891,-88.007462,pepperoni,dog,Yes,night owl,Yes
+LEC006,,Engineering: Mechanical,53706,37.566536,126.977966,pepperoni,dog,Yes,night owl,No
+LEC005,18,Data Science,53706,36.393154,25.46151,none (just cheese),dog,No,night owl,No
+LEC001,,Engineering: Mechanical,53715,19.8968,155.5828,pepperoni,dog,No,night owl,No
+LEC002,19,Engineering: Biomedical,53706,48.494904,-113.979034,macaroni/pasta,cat,No,night owl,Yes
+LEC005,18,Engineering: Mechanical,53706,41.88998,12.49426,pineapple,dog,Yes,night owl,Yes
+LEC003,17,Data Science,53706,-7.257472,112.75209,pineapple,dog,Yes,early bird,Yes
+LEC005,19,Economics,53703,40.592331,-111.820152,none (just cheese),dog,Yes,night owl,Maybe
+LEC005,19,Data Science,53704,38.722252,-9.139337,pepperoni,dog,No,night owl,Yes
+LEC003,,Computer Science,53703,64.963051,-19.020836,pineapple,dog,No,no preference,Maybe
+LEC002,20,Economics,53703,43.769562,11.255814,mushroom,dog,No,night owl,Yes
+LEC004,20,Business: Actuarial,53715,44.834209,-87.376266,sausage,dog,No,no preference,Yes
+LEC005,21,Economics,53703,37.751824,-122.420105,green pepper,cat,No,night owl,Yes
+LEC004,22,Economics,53703,56.490669,4.202646,mushroom,dog,No,no preference,Yes
+LEC004,18,Engineering: Mechanical,53706,44.9058,-93.28535,pepperoni,cat,Yes,night owl,Maybe
+LEC004,19,Data Science,53703,41.878113,-87.629799,sausage,dog,No,night owl,Yes
+LEC001,21,Computer Science,53703,43.21518,-87.94241,pepperoni,dog,No,no preference,Maybe
+LEC004,24,Science: Chemistry,53703,32.715736,-117.161087,mushroom,dog,Yes,night owl,Maybe
+LEC005,19,Engineering: Mechanical,53715,39.412327,-77.425461,pepperoni,cat,Yes,early bird,Yes
+LEC004,20,Statistics,53703,43.07391,-89.39356,pepperoni,dog,No,early bird,Maybe
+LEC005,21,Business: Finance,53703,38.178127,-92.781052,mushroom,dog,No,night owl,Yes
+LEC004,18,Engineering: Mechanical,53706,35.689487,139.691711,pepperoni,dog,No,no preference,Yes
+LEC005,18,Data Science,60521,41.9,87.6,pepperoni,dog,Yes,night owl,Yes
+LEC005,23,Business: Information Systems,53558,43.073051,-89.40123,pepperoni,dog,Yes,early bird,No
+LEC004,18,Engineering: Mechanical,53706,43.739507,7.426706,pepperoni,dog,No,night owl,Yes
+LEC005,21,Data Science,53703,25,121,pepperoni,dog,No,night owl,Yes
+LEC005,20,Business: Information Systems,53703,43.073051,-89.40123,pepperoni,dog,Yes,night owl,Yes
+LEC004,,Engineering: Biomedical,53715,41.385063,2.173404,pepperoni,dog,Yes,no preference,No
+LEC004,18,Communication arts,53715,22.543097,114.057861,mushroom,cat,Yes,early bird,Yes
+LEC001,22,Engineering: Mechanical,53703,47.497913,19.040236,pepperoni,dog,No,no preference,No
+LEC005,19,Computer Science,54706,34.05,-118.24,sausage,cat,Yes,night owl,Yes
+LEC005,18,Engineering: Biomedical,53706,46.818188,8.227512,pineapple,dog,Yes,no preference,Yes
+LEC004,19,Engineering: Mechanical,53715,42.36,-71.058884,pepperoni,dog,Yes,no preference,Yes
+LEC005,21,Data Science,53703,36.4,117,pineapple,dog,Yes,night owl,Yes
+LEC005,19,Engineering: Mechanical,53704,35.6762,139.6503,sausage,dog,No,night owl,Maybe
+LEC004,20,Economics,53703,44.885,-93.147,pepperoni,dog,No,early bird,Yes
+LEC004,20,Health Promotion and Health Equity,53704,48.8566,2.349014,pepperoni,dog,No,night owl,Yes
+LEC004,19,Engineering: Mechanical,53715,43.073051,-89.40123,sausage,dog,Yes,no preference,Yes
+LEC001,20,Business andministration,53703,37.389091,-5.984459,pineapple,dog,Yes,night owl,Maybe
+LEC003,23,Mathematics/AMEP,53715,24.88,102.8,pineapple,dog,Yes,early bird,Yes
+LEC002,20,Engineering: Industrial,53703,44.389,12.9908,sausage,dog,No,early bird,Maybe
+LEC005,20,Education,53703,41.878113,-87.629799,basil/spinach,cat,Yes,early bird,No
+LEC003,19,Science: Biology/Life,53703,41.38,2.17,pepperoni,dog,Yes,no preference,Maybe
+LEC006,18,Pre-business,53706,41.8781,87.6298,pepperoni,dog,Yes,night owl,Yes
+LEC004,20,Business: Finance,53706,41.10475,-80.64916,basil/spinach,dog,Yes,night owl,Yes
+LEC004,20,Statistics,53703,42.360081,-71.058884,pepperoni,dog,No,night owl,Yes
+LEC003,18,Engineering: Mechanical,53706,24.5554,81.7842,pepperoni,dog,No,early bird,Maybe
+LEC004,19,Data Science,53703,38.72,75.07,none (just cheese),dog,Yes,early bird,Yes
+LEC006,20,Engineering: Mechanical,53705,30.572815,104.066803,mushroom,cat,Yes,no preference,Maybe
+LEC003,20,Mathematics/AMEP,53726,43.07199,-89.42629,mushroom,dog,No,night owl,Yes
+LEC004,20,Engineering: Mechanical,53705,48,7.85,pepperoni,dog,Yes,night owl,No
+LEC001,20,Computer Science,53703,40.7128,74.006,pepperoni,dog,Yes,night owl,Maybe
+LEC003,18,Business: Actuarial,53719,14.599512,120.984222,pineapple,cat,Yes,no preference,Maybe
+LEC003,17,Computer Science,53715,37.38522,-122.114128,Other,dog,No,night owl,No
+LEC003,18,Computer Science,53706,37.386051,-122.083855,sausage,dog,Yes,no preference,Maybe
+LEC004,23,Business: Finance,53703,31.230391,121.473701,mushroom,neither,No,night owl,No
+LEC004,21,Engineering: Industrial,53703,37.94048,-78.63664,Other,dog,Yes,night owl,Yes
+LEC002,21,Mathematics/AMEP,53715,42.360081,-71.058884,mushroom,neither,Yes,early bird,Yes
+LEC002,18,Engineering: Industrial,53715,40.712776,-74.005974,pineapple,dog,Yes,night owl,Yes
+LEC001,22,Engineering: Mechanical,53726,36.97447,122.02899,pepperoni,dog,No,no preference,Yes
+LEC005,,Mathematics/AMEP,53715,36.651199,117.120094,mushroom,neither,No,night owl,Yes
+LEC005,18,Mathematics/AMEP,53706,46.482525,30.723309,basil/spinach,dog,No,early bird,Yes
+LEC006,20,Engineering: Industrial,53703,42.102901,-88.368896,pepperoni,dog,No,night owl,Maybe
+LEC006,18,Computer Science,53706,-31.959153,-244.161255,green pepper,dog,No,night owl,Yes
+LEC002,24,Computer Science,53715,30.704852,104.003904,mushroom,neither,Yes,no preference,Maybe
+LEC005,19,Engineering: Mechanical,53705,40.712776,-74.005974,pepperoni,dog,No,early bird,No
+LEC004,22,Science: Biology/Life,53705,39.758161,39.758161,pepperoni,cat,No,early bird,Yes
+LEC005,20,Statistics,53703,43.073051,-89.40123,sausage,dog,Yes,night owl,Yes
+LEC001,19,Data Science,53703,41,87,sausage,dog,No,no preference,No
+LEC004,20,Engineering: Mechanical,53726,58.2996,14.4444,sausage,cat,No,night owl,Maybe
+LEC005,18,Engineering: Mechanical,53562,1.3521,103.8198,green pepper,cat,No,early bird,Maybe
+LEC002,19,Engineering: Mechanical,53703,44.46534,-72.684303,green pepper,cat,Yes,night owl,Yes
+LEC002,20,Engineering: Industrial,53726,43.038902,-87.906471,pepperoni,dog,No,night owl,Yes
+LEC006,18,Business: Actuarial,53706,45.464203,9.189982,pepperoni,cat,Yes,night owl,Yes
+LEC006,18,Computer Science,53715,30.58198,114.268066,sausage,cat,Yes,early bird,Maybe
+LEC004,19,Business: Finance,53706,41.878113,-87.629799,pepperoni,dog,No,early bird,No
+LEC005,18,Business: Finance,53706,40.416775,-3.70379,pepperoni,dog,Yes,early bird,No
+LEC001,20,Science: Other|Environmental Science,53715,41.878113,-87.629799,green pepper,cat,No,early bird,No
+LEC002,22,Computer Science,53715,42,-71,mushroom,cat,No,night owl,Maybe
+LEC001,24,Economics,53703,40,-90,pineapple,dog,No,night owl,Yes
+LEC006,19,Business: Information Systems,53715,40.712776,-74.005974,basil/spinach,dog,No,night owl,Yes
+LEC002,19,Data Science,53703,33.4942,89.4959,sausage,dog,No,night owl,Maybe
+LEC003,20,Engineering: Mechanical,53715,43.02833,-87.971467,pepperoni,neither,Yes,night owl,Maybe
+LEC001,,Data Science,53706,40.416775,-3.70379,none (just cheese),dog,Yes,no preference,Yes
+LEC003,19,Engineering: Mechanical,53715,43.07,-89.4,pepperoni,dog,No,no preference,Maybe
+LEC006,18,Data Science,53706,46.683334,7.85,mushroom,dog,Yes,no preference,No
+LEC003,19,Engineering: Biomedical,53703,31.046051,34.851612,Other,dog,No,night owl,Maybe
+LEC003,18,Data Science,53705,31.23,121.47,mushroom,dog,Yes,night owl,Maybe
+LEC005,19,Engineering: Mechanical,53703,42.00741,-87.69384,mushroom,dog,No,night owl,Yes
+LEC001,37,Data Science,53718,43.073051,-89.40123,green pepper,dog,No,no preference,Maybe
+LEC003,20,History,53703,31.62,74.8765,Other,cat,Yes,early bird,No
+LEC002,20,Economics,53703,38.627003,-90.199402,mushroom,dog,Yes,night owl,Yes
+LEC005,20,Engineering: Mechanical,53703,40,-74,none (just cheese),dog,Yes,early bird,No
+LEC005,18,Data Science,53706,23.7275,37.9838,pepperoni,dog,Yes,early bird,Yes
+LEC004,20,Mathematics/AMEP,53703,34.746613,113.625328,sausage,neither,Yes,early bird,Maybe
+LEC001,21,Data Science,53703,30.572351,121.776761,pepperoni,cat,No,night owl,Maybe
+LEC005,,Data Science,53715,35.72,-78.89,pepperoni,dog,No,night owl,Yes
+LEC005,20,Information science,53590,44.92556,-89.51539,pepperoni,dog,No,night owl,Yes
+LEC002,22,Mathematics/AMEP,53704,40.76078,-111.891045,pineapple,dog,Yes,night owl,No
+LEC001,22,consumer behavior and marketplace studies,53715,43.653225,-79.383186,mushroom,cat,Yes,night owl,No
+LEC004,22,Computer Science,53703,10.315699,123.885437,sausage,dog,Yes,early bird,No
+LEC002,20,Conservation Biology,53703,40.16573,-105.101189,pineapple,dog,No,night owl,Yes
+LEC005,20,Computer Science,53726,39.4817,106.0384,Other,neither,Yes,early bird,Yes
+LEC005,19,Mathematics/AMEP,53715,48.85,2.35,sausage,cat,No,night owl,Maybe
+LEC005,19,Data Science,53706,30.572815,104.066803,mushroom,neither,No,early bird,Yes
+LEC004,24,Business: Information Systems,53703,37.566536,126.977966,tater tots,dog,No,early bird,No
+LEC004,19,Economics,53703,52.877491,-118.08239,pepperoni,dog,No,night owl,Yes
+LEC004,21,Computer Science,53703,28.538336,-81.379234,pepperoni,dog,No,night owl,Yes
+LEC006,18,Data Science,53706,41.4,-81.9,sausage,dog,Yes,night owl,Maybe
+LEC002,21,Science: Biology/Life,53703,43.038902,-87.906471,none (just cheese),neither,No,no preference,Yes
+LEC004,21,Data Science,53703,3.86,-54.2,macaroni/pasta,dog,No,early bird,No
+LEC004,19,Engineering: Mechanical,53715,39.952583,-75.165222,macaroni/pasta,dog,Yes,no preference,Yes
+LEC004,20,Science: Other,53715,21.3099,157.8581,pineapple,dog,No,early bird,Yes
+LEC005,21,Data Science,48823,11.451419,19.81,mushroom,neither,No,night owl,Maybe
+LEC001,20,Computer Science,53715,41,-87,Other,dog,No,night owl,Yes
+LEC005,21,Data Science,53705,42.3601,71.0589,pepperoni,dog,Yes,no preference,Yes
+LEC005,19,Computer Science,53706,48.856613,2.352222,pepperoni,dog,Yes,night owl,Maybe
+LEC001,17,Statistics,53715,43.0722,89.4008,pineapple,dog,No,early bird,Maybe
+LEC001,20,Economics,53715,27.99942,120.66682,pepperoni,dog,Yes,early bird,No
+LEC001,19,Mathematics/AMEP,53711,45.85038,-84.616989,pineapple,cat,No,night owl,Yes
+LEC004,20,Computer Science,53711,40.842358,111.749992,pineapple,cat,No,night owl,Maybe
+LEC003,18,Engineering: Mechanical,53706,39.738449,-104.984848,pepperoni,dog,No,early bird,Yes
+LEC003,21,Statistics,53705,41.878113,-87.629799,macaroni/pasta,dog,No,night owl,Yes
+LEC006,19,Engineering: Industrial,60540,41.878113,-87.629799,none (just cheese),dog,No,night owl,No
+LEC004,19,Engineering: Mechanical,53703,40.6263,14.3758,mushroom,dog,No,early bird,No
+LEC004,22,Engineering: Other|Chemical Engineering,53703,48.13913,11.58022,macaroni/pasta,dog,Yes,night owl,Yes
+LEC004,21,Economics (Mathematical Emphasis),53703,52.520008,13.404954,pepperoni,dog,No,night owl,No
+LEC004,25,Science: Other|Biophysics PhD,53705,30.21161,-97.80999,pineapple,dog,No,night owl,Yes
+LEC003,19,Computer Science,53716,25.49443,-103.59581,pepperoni,cat,No,no preference,Yes
+LEC003,19,Data Science,53706,64.963051,-19.020836,pineapple,dog,No,no preference,No
+LEC006,19,Computer Science,53706,41.878113,-87.629799,pepperoni,cat,No,night owl,Maybe
+LEC001,23,Economics,53703,43.07348,-89.38089,pepperoni,dog,No,night owl,Yes
+LEC001,29,Business: Other|Technology Strategy/ Product Management,53705,37.386051,-122.083855,Other,cat,No,no preference,Maybe
+LEC002,,Engineering: Mechanical,53706,14.34836,100.576271,pepperoni,neither,No,no preference,Maybe
+LEC004,20,Undecided,53715,37.566536,126.977966,none (just cheese),neither,No,night owl,Yes
+LEC006,19,Engineering: Mechanical,53703,27.993828,120.699364,sausage,neither,No,no preference,Yes
+LEC002,,Computer Science,53705,25.032969,121.565414,pineapple,dog,No,night owl,Yes
+LEC005,20,Mathematics/AMEP,53703,32.060253,118.796875,pineapple,cat,Yes,night owl,Maybe
+LEC003,,Business: Other,53706,50.07553,14.4378,pepperoni,dog,Yes,night owl,Maybe
+LEC006,21,Data Science,57303,32.715736,-117.161087,macaroni/pasta,cat,Yes,no preference,Yes
+LEC006,18,Engineering: Mechanical,53706,45.5579,94.1632,sausage,dog,No,night owl,Yes
+LEC001,18,Engineering: Biomedical,53715,43.073051,-89.40123,sausage,dog,No,early bird,Yes
+LEC005,19,Engineering: Mechanical,53706,38.571739,-109.550797,pepperoni,cat,No,night owl,Yes
+LEC003,18,Engineering: Mechanical,53706,41.902782,12.496365,pepperoni,dog,Yes,night owl,No
+LEC002,21,Data Science,53711,120,30,sausage,dog,Yes,night owl,Maybe
+LEC004,18,Engineering: Biomedical,53706,40.014984,-105.270546,green pepper,dog,No,night owl,Yes
+LEC004,20,Engineering: Mechanical,53715,53.2779,6.1058,sausage,dog,Yes,no preference,Yes
+LEC003,17,Science: Physics,53706,50.088153,14.399437,Other,cat,No,night owl,Yes
+LEC002,19,Engineering: Industrial,53705,35.084385,-106.650421,pineapple,cat,No,night owl,Yes
+LEC003,20,Engineering: Mechanical,53703,44.501343,-88.06221,pepperoni,dog,No,night owl,Yes
+LEC003,18,Engineering: Mechanical,53703,45.659302,-92.466164,macaroni/pasta,dog,No,no preference,Maybe
+LEC003,19,Data Science,53703,16.896721,42.5536,none (just cheese),neither,No,early bird,Maybe
+LEC001,18,Data Science,53703,23.885942,45.079163,mushroom,neither,No,early bird,Maybe
+LEC006,19,Engineering: Mechanical,53703,55.953251,-3.188267,mushroom,cat,Yes,night owl,Yes
+LEC001,30,Business: Other,53705,43.07175,-89.46498,pineapple,cat,No,early bird,No
+LEC006,18,Political Science,53706,39.640263,-106.374191,green pepper,dog,No,early bird,No
+LEC005,23,Business: Information Systems,53705,27.99,120.69,green pepper,dog,No,night owl,No
+LEC003,18,Graphic Design,53706,40.713051,-74.007233,Other,dog,Yes,early bird,Yes
+LEC002,21,Economics,53715,37.369171,-122.112473,mushroom,dog,No,night owl,No
+LEC005,18,Computer Science,53706,21.3099,157.8581,pepperoni,cat,No,night owl,Yes
+LEC002,19,Business: Other|Marketing,53706,59.913868,10.752245,macaroni/pasta,dog,No,night owl,Maybe
+LEC003,20,Cartography and GIS,53726,43.0722,89.4008,sausage,cat,No,early bird,Maybe
+LEC005,21,Economics,53705,25.032969,120.960518,sausage,dog,Yes,night owl,Maybe
+LEC005,19,Engineering: Industrial,53703,42.03992,87.67732,sausage,dog,Yes,night owl,Yes
+LEC003,,Computer Science,53706,35.443081,139.362488,sausage,dog,Yes,night owl,Yes
+LEC002,22,Sociology,53703,53.483959,-2.244644,pepperoni,dog,No,night owl,Yes
+LEC002,18,Undecided,53706,43.073051,-89.40123,pineapple,dog,Yes,night owl,Yes
+LEC004,19,Engineering: Biomedical,53706,-37.81,144.96,sausage,dog,Yes,night owl,Yes
+LEC005,21,Mathematics/AMEP,53703,22.542883,114.062996,pepperoni,cat,No,no preference,Maybe
+LEC002,20,Statistics,53715,23,113,pineapple,dog,No,night owl,Maybe
+LEC001,20,Business: Other|Consumer Behavior and Marketplace Studies,53703,40.76078,-111.891045,green pepper,dog,Yes,early bird,Maybe
+LEC001,21,Data Science,53705,40.712776,-74.005974,pepperoni,cat,No,night owl,Maybe
+LEC002,19,Engineering: Mechanical,53703,26.345631,-81.779083,pepperoni,dog,Yes,night owl,Yes
+LEC004,19,Engineering: Mechanical,53715,40.62632,14.37574,pepperoni,dog,No,no preference,Maybe
+LEC003,18,Engineering: Other,53706,40.73061,-73.9808,mushroom,dog,No,night owl,No
+LEC006,18,Atmospheric Sciences,53706,39.74,-104.99,sausage,dog,Yes,night owl,Maybe
+LEC002,20,Data Science,53703,43.073051,-89.40123,macaroni/pasta,dog,Yes,early bird,Yes
+LEC006,18,Engineering: Mechanical,53706,32.7157,117.1611,pineapple,dog,Yes,night owl,Yes
+LEC004,18,Computer Science,53706,51.507351,-0.127758,green pepper,dog,No,night owl,Yes
+LEC004,19,Education,53715,32.715736,-117.161087,pepperoni,dog,No,night owl,Yes
+LEC004,26,Languages,53703,50.11,8.68,sausage,dog,No,no preference,Yes
+LEC005,21,Economics (Mathematical Emphasis),53715,55.676098,12.568337,pepperoni,cat,No,night owl,Maybe
+LEC004,53,Mathematics/AMEP,53555,47.6,-122.3,mushroom,dog,No,night owl,Yes
+LEC004,17,Computer Science,53706,43.073051,-89.40123,Other,dog,No,night owl,Yes
+LEC006,18,Engineering Mechanics (Aerospace Engineering),53706,43.038902,-87.906471,pepperoni,cat,No,night owl,No
+LEC002,20,Engineering: Mechanical,53715,23.7157,117.1611,none (just cheese),cat,Yes,night owl,Maybe
+LEC002,22,Science: Other|Psychology,53703,37.82034,-122.47872,mushroom,dog,No,early bird,No
+LEC002,22,Computer Science,53705,34.052235,-118.243683,basil/spinach,dog,No,night owl,Yes
+LEC004,26,Science: Biology/Life,53715,33.962425,-83.378622,pineapple,neither,Yes,no preference,Yes
+LEC002,18,Economics,53715,41.878113,-87.629799,basil/spinach,cat,No,night owl,Maybe
+LEC004,24,Engineering: Other|Civil and Environmental Engineering,53703,47.5,19.04,pepperoni,dog,Yes,early bird,Maybe
+LEC004,19,Engineering: Biomedical,53711,40.712776,74.005974,pineapple,dog,No,early bird,No
+LEC001,19,Engineering: Mechanical,53715,43,-90,sausage,dog,No,no preference,Maybe
+LEC006,18,Data Science,94707,37.566536,126.977966,pineapple,dog,Yes,night owl,Yes
+LEC006,20,Undecided,53719,62.2001,58.9638,Other,cat,Yes,night owl,Maybe
+LEC002,18,Engineering: Mechanical,53706,44.977753,-93.265015,none (just cheese),cat,Yes,night owl,Yes
+LEC001,20,Business: Information Systems,53711,34.385204,132.455292,pepperoni,dog,No,early bird,Yes
+LEC005,19,Engineering: Biomedical,53703,41.8781,87.6298,macaroni/pasta,dog,No,night owl,No
+LEC002,19,Engineering: Biomedical,53703,37.98381,23.727539,macaroni/pasta,dog,No,night owl,Maybe
+LEC005,18,Data Science,53706,40,74,pepperoni,dog,No,no preference,Yes
+LEC002,19,Engineering: Mechanical,53711,41.95881,-85.32536,Other,dog,No,no preference,No
+LEC005,18,Data Science,53706,32.715736,-117.161087,sausage,dog,No,night owl,Maybe
+LEC002,18,Undecided,53706,43.060791,-88.119217,Other,neither,No,early bird,Yes
+LEC004,21,Science: Other,53715,27.963989,-82.799957,pineapple,dog,No,night owl,Yes
+LEC006,18,Data Science,53706,1.352083,103.819839,sausage,dog,No,night owl,Yes
+LEC005,19,Data Science,53703,-33.92487,18.424055,none (just cheese),dog,No,night owl,Yes
+LEC001,22,International Studies,53703,48.13913,11.58022,none (just cheese),cat,No,night owl,Yes
+LEC001,19,Engineering: Other,53715,38.331581,-75.086159,macaroni/pasta,dog,No,no preference,Yes
+LEC002,19,Business: Information Systems,53715,44.5,-88,pepperoni,dog,No,night owl,Yes
+LEC002,19,Data Science,53705,21.59143,-158.01743,Other,dog,Yes,night owl,Yes
+LEC002,,Business: Finance,53593,45.813042,9.080931,Other,dog,No,early bird,Yes
+LEC003,21,Business: Information Systems,53703,43.612255,-110.705429,sausage,dog,Yes,no preference,No
+LEC001,21,Data Science,53703,41.00824,28.978359,pepperoni,cat,Yes,early bird,No
+LEC002,18,Engineering: Biomedical,53706,17.385044,78.486671,green pepper,dog,No,night owl,Yes
+LEC006,21,Political Science,53703,45.512,-122.658,sausage,dog,No,night owl,Yes
+LEC003,18,Engineering: Mechanical,53706,41.902782,12.496365,pepperoni,dog,No,early bird,Maybe
+LEC005,19,Engineering: Mechanical,53703,-36.848461,174.763336,none (just cheese),dog,Yes,no preference,No
+LEC002,,Data Science,53713,30.316496,78.032188,mushroom,cat,Yes,night owl,Yes
+LEC002,,Business: Information Systems,53703,35.689487,139.691711,sausage,dog,Yes,night owl,Maybe
+LEC005,18,Data Science,53706,52.520008,13.404954,pineapple,dog,Yes,early bird,No
+LEC005,19,Computer Science,53706,41.3784,2.1686,sausage,cat,No,no preference,Yes
+LEC003,20,Engineering: Mechanical,53715,41.878113,-87.629799,Other,cat,No,night owl,Yes
+LEC004,20,Computer Science,53703,43.073051,-89.40123,none (just cheese),cat,Yes,night owl,Yes
+LEC006,23,Data Science,53703,17.05423,-96.713226,basil/spinach,dog,No,night owl,Maybe
+LEC001,19,Engineering: Mechanical,53706,43.77195,-88.43383,pepperoni,dog,No,early bird,Maybe
+LEC001,20,Economics,53726,42.92,-87.96,pepperoni,dog,Yes,early bird,No
+LEC001,19,Engineering: Mechanical,53715,29.424122,-98.493629,mushroom,dog,Yes,early bird,Maybe
+LEC004,18,Computer Science,53706,30.267153,-97.743057,pepperoni,dog,No,night owl,Yes
+LEC005,,Computer Science,53715,44.9778,93.265,sausage,cat,Yes,night owl,Yes
+LEC003,19,Science: Other,53715,41.9028,12.4964,pepperoni,dog,No,night owl,Yes
+LEC004,19,Data Science,53715,61.2176,149.8997,pineapple,cat,Yes,night owl,Maybe
+LEC001,20,Agricultural and Applied Economics,53703,-22.932924,-47.073845,pineapple,cat,Yes,early bird,Maybe
+LEC003,18,Computer Science,53706,52.370216,4.895168,basil/spinach,cat,No,night owl,Maybe
+LEC003,19,Engineering: Industrial,53703,5.838715,3.603516,pepperoni,dog,Yes,early bird,No
+LEC005,19,Engineering: Mechanical,53715,48.502281,-113.988533,sausage,dog,No,night owl,Yes
+LEC004,41,Languages,53705,29.654839,91.140549,pepperoni,cat,No,night owl,Yes
+LEC002,21,Business: Other|MHR,53703,44,125,Other,neither,No,night owl,Maybe
+LEC005,24,Business: Other,53703,43.073051,-89.40123,pineapple,dog,No,night owl,Yes
+LEC002,18,Undecided,53706,46.786671,-92.100487,none (just cheese),cat,No,no preference,Yes
+LEC004,18,Engineering: Biomedical,53705,35.689487,139.691711,basil/spinach,dog,No,night owl,Yes
+LEC001,25,Medicine,53703,48.38203,-123.537827,basil/spinach,dog,Yes,early bird,No
+LEC004,19,Science: Biology/Life,53705,46.009991,-91.482094,pineapple,dog,No,early bird,No
+LEC005,21,Science: Other|Personal Finance,53703,28.228209,112.938812,pepperoni,cat,Yes,night owl,Yes
+LEC004,18,Data Science,53706,35.689487,139.691711,pepperoni,dog,No,night owl,Maybe
+LEC006,21,Mathematics/AMEP,53703,41.878113,-87.629799,pineapple,cat,Yes,night owl,Maybe
+LEC005,18,Environmental science,53706,31.224361,121.46917,mushroom,dog,No,night owl,Yes
+LEC005,18,Engineering: Industrial,53706,40.712776,-74.005974,pepperoni,dog,Yes,night owl,Yes
+LEC001,20,Business: Other|Real Estate,53703,51.5,0.128,mushroom,dog,Yes,no preference,Maybe
+LEC001,19,Computer Science,53706,40,-74,pepperoni,cat,No,night owl,Yes
+LEC003,19,Engineering: Mechanical,53715,44,-94,pineapple,dog,No,early bird,No
+LEC001,19,Data Science,53715,40.712776,-74.005974,pepperoni,dog,No,early bird,No
+LEC005,18,Engineering: Industrial,53703,41.385063,2.173404,pepperoni,dog,Yes,no preference,Yes
+LEC002,20,Engineering: Industrial,53715,22.3,91.8,sausage,cat,Yes,early bird,Maybe
+LEC001,24,Engineering: Industrial,53705,13.100485,77.594009,none (just cheese),dog,Yes,no preference,Maybe
+LEC004,19,Statistics,53706,36.778259,-119.417931,pineapple,cat,No,night owl,Yes
+LEC005,21,Economics,53703,40.016869,-105.279617,pepperoni,cat,Yes,night owl,Yes
+LEC003,19,Economics (Mathematical Emphasis),53705,31.230391,121.473701,sausage,neither,Yes,no preference,Maybe
+LEC003,19,Business: Finance,53706,22.270979,113.576675,pepperoni,dog,Yes,night owl,Yes
+LEC003,21,Computer Science,53705,43.073051,-89.40123,green pepper,cat,No,no preference,Maybe
+LEC001,28,Science: Biology/Life,53703,7.190708,125.455338,sausage,dog,No,night owl,Yes
+LEC004,18,Statistics,53703,60.472023,8.468946,none (just cheese),dog,No,early bird,No
+LEC002,19,Computer Science,53715,41.73993,-88.09423,mushroom,cat,Yes,no preference,Yes
+LEC002,21,Economics,53703,26.074301,119.296539,mushroom,cat,No,no preference,Maybe
+LEC002,20,Engineering: Industrial,53715,2.188477,41.379179,sausage,dog,No,night owl,Yes
+LEC003,21,Science: Other|Environmental Science,53703,20.8,-156.3,basil/spinach,cat,No,early bird,Maybe
+LEC006,18,Engineering: Mechanical,53706,25.204849,55.270782,pepperoni,dog,No,night owl,Yes
+LEC002,18,Data Science,53706,42.360081,-71.058884,sausage,dog,Yes,night owl,Yes
+LEC004,23,Engineering: Mechanical,53703,38.82097,-104.78163,sausage,dog,No,night owl,No
+LEC001,19,Engineering: Industrial,53715,47.606209,-122.332069,pepperoni,cat,No,night owl,No
+LEC006,19,Sociology,53703,43.05977,-87.88491,basil/spinach,dog,No,night owl,Maybe
+LEC005,19,Engineering: Mechanical,53711,38.8951,-77.0364,pepperoni,dog,Yes,night owl,No
+LEC005,19,Engineering: Mechanical,53703,41.881832,87.6298,pepperoni,dog,No,no preference,Yes
+LEC002,20,Engineering: Mechanical,53703,46.453825,7.436478,pineapple,dog,Yes,night owl,Yes
+LEC002,20,Economics,53703,30.49996,117.050003,Other,dog,No,early bird,Maybe
+LEC004,21,Science: Other|Psychology,53715,23.12911,113.264381,none (just cheese),cat,No,night owl,Maybe
+LEC002,18,Science: Biology/Life,53706,40.7831,73.9712,basil/spinach,dog,Yes,night owl,Yes
+LEC002,,Business: Information Systems,53706,18.52043,73.856743,green pepper,dog,No,night owl,Yes
+LEC002,,Computer Science,53706,29.424122,-98.493629,none (just cheese),dog,No,no preference,Yes
+LEC002,20,Engineering: Mechanical,53703,41.05995,-80.32312,basil/spinach,dog,Yes,night owl,Maybe
+LEC006,19,Statistics,53715,3.139003,101.686852,mushroom,cat,No,no preference,Maybe
+LEC005,18,Data Science,53706,52.370216,4.895168,basil/spinach,dog,No,night owl,Yes
+LEC006,19,Engineering: Industrial,53706,41.878113,-87.629799,pepperoni,dog,No,no preference,Maybe
+LEC006,18,Business: Information Systems,53706,25.032969,121.565414,mushroom,dog,Yes,night owl,Yes
+LEC001,17,Computer Science,53726,21.027763,105.83416,pepperoni,dog,No,early bird,Yes
+LEC001,20,Business: Information Systems,53711,45.046799,-87.298149,sausage,cat,No,night owl,Yes
+LEC005,25,Engineering: Other,53705,32.7157,-117.1611,mushroom,dog,No,no preference,Yes
+LEC004,18,Engineering: Industrial,53706,19.896767,-155.582779,pepperoni,dog,Yes,night owl,Maybe
+LEC005,18,Computer Science,53706,1.28217,103.865196,sausage,dog,No,night owl,Yes
+LEC003,18,Engineering: Mechanical,53706,44.977753,-93.265015,pepperoni,dog,No,night owl,Yes
+LEC004,20,Engineering: Mechanical,53715,23,90,green pepper,cat,No,no preference,Yes
+LEC005,20,Data Science,53703,45.259546,-84.938476,mushroom,dog,Yes,night owl,Yes
+LEC002,21,Science: Other,53703,41.878113,-87.629799,pineapple,dog,Yes,early bird,No
+LEC004,19,Information science,53703,40.712776,-74.005974,pineapple,cat,Yes,early bird,Maybe
+LEC001,19,Engineering: Mechanical,53715,64.126518,-21.817438,pepperoni,dog,No,night owl,Yes
+LEC003,,Business: Other,53706,42.360081,-71.058884,sausage,cat,Yes,night owl,No
+LEC002,31,Geoscience,53703,-41.126621,-73.059303,pepperoni,cat,No,night owl,Yes
+LEC003,18,Engineering: Biomedical,53706,45.17099,-87.16494,Other,dog,No,night owl,Maybe
+LEC002,18,Engineering: Mechanical,53706,37.774929,-122.419418,Other,dog,Yes,no preference,Yes
+LEC004,,Computer Science,53715,39.70698,-86.0862,mushroom,cat,No,night owl,Yes
+LEC005,20,Science: Biology/Life,53703,44.276402,-88.26989,macaroni/pasta,cat,No,no preference,Maybe
+LEC002,19,Science: Biology/Life,53703,51.492519,-0.25852,sausage,dog,Yes,no preference,Yes
+LEC002,19,Data Science,53703,37.6,14.0154,none (just cheese),dog,No,night owl,Yes
+LEC002,20,Engineering: Industrial,53715,46.685631,7.8562,Other,cat,No,night owl,Maybe
+LEC002,22,Economics,53706,41.385063,2.173404,pineapple,cat,No,night owl,Maybe
+LEC004,21,Engineering: Industrial,53703,41.878113,-87.629799,pepperoni,neither,Yes,early bird,No
+LEC004,19,Engineering: Mechanical,53703,51.507351,-0.127758,none (just cheese),neither,No,no preference,Maybe
+LEC006,18,Engineering: Mechanical,53706,41.077747,1.131593,sausage,dog,No,no preference,Maybe
+LEC006,18,Engineering: Mechanical,53706,43.526,5.445,basil/spinach,dog,Yes,no preference,Yes
+LEC003,22,Economics,53715,43.073051,-89.40123,pepperoni,dog,Yes,early bird,Yes
+LEC005,18,Engineering: Industrial,53706,43.085369,-88.912086,sausage,dog,No,night owl,Maybe
+LEC002,19,Statistics,53703,43.769562,11.255814,basil/spinach,dog,No,no preference,Yes
+LEC001,20,Computer Science,53715,20.880947,-156.681862,sausage,dog,No,night owl,Yes
+LEC003,19,Mathematics/AMEP,53703,64.963051,-19.020836,basil/spinach,dog,No,no preference,Yes
+LEC005,18,Undecided,53706,43.073929,-89.385239,sausage,dog,Yes,early bird,Yes
+LEC003,18,Business: Information Systems,53706,25.204849,55.270782,none (just cheese),dog,No,night owl,No
+LEC003,21,Economics,53703,39.904,116.407,pepperoni,cat,No,night owl,No
+LEC004,18,Engineering: Mechanical,53706,39.739235,-104.99025,pepperoni,cat,Yes,no preference,Maybe
+LEC004,21,Science: Biology/Life,53726,43,89,pepperoni,dog,Yes,night owl,Yes
+LEC003,19,Data Science,53715,43.073051,-89.40123,none (just cheese),dog,No,early bird,Maybe
+LEC002,19,Business: Other|accounting,53703,43.38,-87.9,sausage,neither,No,night owl,Yes
+LEC002,18,Science: Biology/Life,53706,40.122,25.4988,sausage,dog,No,early bird,No
+LEC005,20,Engineering: Mechanical,53715,39.904202,116.407394,sausage,dog,No,night owl,Yes
+LEC001,19,Engineering: Mechanical,53703,-37.813629,144.963058,sausage,dog,Yes,night owl,Yes
+LEC005,21,Economics,53715,46.81,-71.21,pepperoni,cat,No,night owl,Yes
+LEC004,19,Engineering: Mechanical,53715,52.370216,4.895168,mushroom,dog,Yes,night owl,Yes
+LEC001,21,Mathematics/AMEP,53703,34.29006,108.932941,basil/spinach,dog,No,early bird,Yes
+LEC005,21,Engineering: Mechanical,53726,43.804801,-91.226075,pepperoni,dog,Yes,night owl,Yes
+LEC002,18,Data Science,53703,32.715736,-117.161087,none (just cheese),cat,Yes,night owl,Maybe
+LEC004,18,Engineering: Mechanical,53706,20.92674,-156.69386,pepperoni,dog,No,night owl,Maybe
+LEC003,18,Data Science,53706,47.606209,-122.332069,pepperoni,dog,No,early bird,Yes
+LEC005,21,Computer Science,53703,43.07515,-89.3958,sausage,neither,Yes,night owl,Yes
+LEC001,19,Engineering: Mechanical,53562,43.096851,-89.511528,sausage,dog,No,night owl,No
+LEC003,19,Engineering: Mechanical,53715,20.924325,-156.690102,sausage,cat,Yes,night owl,No
+LEC005,20,Data Science,53703,25.0838,77.3212,pepperoni,dog,No,night owl,Maybe
+LEC003,21,Business: Actuarial,53715,43.073051,-89.40123,pineapple,cat,Yes,night owl,Yes
+LEC001,,Computer Science,53715,31.469279,119.765621,pepperoni,dog,No,night owl,Maybe
+LEC005,19,Engineering: Mechanical,53715,43.769562,11.255814,basil/spinach,neither,No,early bird,No
+LEC001,21,Science: Chemistry,53715,38.892059,-77.019913,pepperoni,neither,No,night owl,Yes
+LEC002,19,Business: Finance,53715,42.360081,-71.058884,mushroom,dog,Yes,night owl,Yes
+LEC001,18,Data Science,53703,24.713552,46.675297,none (just cheese),neither,No,night owl,Yes
+LEC003,19,Business: Actuarial,53715,60.391262,5.322054,pepperoni,dog,No,early bird,No
+LEC003,19,Data Science,53715,23.697809,120.960518,pepperoni,cat,No,night owl,Yes
+LEC003,18,Data Science,53706,40.712776,74.005974,pineapple,dog,Yes,early bird,No
+LEC004,19,Engineering: Mechanical,53703,45.126887,-94.528067,sausage,dog,No,night owl,Maybe
+LEC002,21,Science: Biology/Life,53715,48.208176,16.373819,Other,dog,Yes,night owl,No
+LEC006,18,Engineering: Mechanical,53706,44.0628,-121.30451,pepperoni,dog,No,night owl,Yes
+LEC003,21,Statistics,53703,31.230391,121.473701,pineapple,cat,Yes,night owl,Yes
+LEC005,21,Economics,53703,47.62772,-122.51368,macaroni/pasta,cat,No,no preference,No
+LEC003,19,Engineering: Mechanical,53715,65.68204,-18.090534,sausage,cat,No,no preference,No
+LEC004,21,Economics,53715,48.856613,2.352222,basil/spinach,dog,Yes,night owl,No
+LEC001,18,Engineering: Biomedical,53706,33.501324,-111.925278,pineapple,dog,Yes,early bird,No
+LEC005,18,Data Science,53706,14.77046,-91.183189,mushroom,cat,No,night owl,Maybe
+LEC002,18,Engineering: Industrial,53706,10.480594,-66.903603,mushroom,neither,No,night owl,Maybe
+LEC004,21,Engineering: Mechanical,53715,48.856613,2.352222,mushroom,cat,Yes,night owl,Yes
+LEC001,19,Science: Biology/Life,53706,20.788602,-156.003662,green pepper,dog,Yes,no preference,No
+LEC006,18,Data Science,53706,36.59239,-121.86875,pepperoni,cat,No,night owl,Maybe
+LEC002,,Engineering: Industrial,53705,47.6,-122.33,sausage,dog,No,early bird,No
+LEC001,18,Engineering: Mechanical,53703,23.885942,45.079163,Other,cat,No,night owl,Maybe
+LEC002,18,Engineering: Industrial,53532,47.606209,-122.332069,mushroom,dog,No,night owl,Maybe
+LEC002,17,Engineering: Biomedical,53706,39.5755,-106.100403,pepperoni,dog,Yes,night owl,Maybe
+LEC002,20,Data Science,53711,39.904202,116.407394,pepperoni,dog,No,night owl,Yes
+LEC001,19,Engineering: Industrial,53705,41.878113,-87.629799,tater tots,cat,No,night owl,No
+LEC004,19,Political Science,53703,55.679626,12.581921,pepperoni,dog,Yes,no preference,Maybe
+LEC005,18,Computer Science,53715,28.538336,-81.379234,pepperoni,dog,No,night owl,Maybe
+LEC004,29,Engineering: Mechanical,53704,50.064651,19.944981,sausage,dog,No,early bird,Maybe
+LEC005,18,Engineering: Other,53706,41.385063,2.173404,mushroom,cat,No,night owl,Yes
+LEC001,19,Engineering: Mechanical,53703,44.977753,-93.265015,Other,cat,Yes,early bird,No
+LEC001,32,Design Studies,53705,48.856613,2.352222,mushroom,dog,No,early bird,Yes
+LEC002,20,Engineering: Mechanical,53703,41.28347,-70.099449,pepperoni,dog,Yes,night owl,Yes
+LEC003,19,Engineering: Industrial,53715,41.73849,-71.30418,pepperoni,dog,No,night owl,Yes
+LEC001,18,Data Science,53706,43.073051,-89.40123,sausage,dog,No,early bird,Yes
+LEC001,19,Computer Science,53715,31.230391,121.473701,pineapple,cat,No,night owl,Yes
+LEC001,19,Data Science,53703,37.9838,23.7275,sausage,dog,Yes,no preference,Yes
+LEC005,20,Engineering: Biomedical,53703,47.497913,19.040236,Other,cat,Yes,night owl,No
+LEC004,18,Economics,53711,13.756331,100.501762,Other,dog,No,night owl,Maybe
+LEC002,18,Data Science,53706,3.864255,73.388672,pepperoni,dog,Yes,night owl,Maybe
+LEC006,18,Engineering: Mechanical,53706,32.715736,-117.161087,macaroni/pasta,dog,Yes,night owl,Yes
+LEC001,19,Business: Actuarial,53715,18.32431,64.941612,pepperoni,dog,No,no preference,Yes
+LEC001,22,Psychology,53711,43.055333,-89.425946,pineapple,dog,Yes,early bird,No
+LEC003,18,Computer Science,53706,40.744678,-73.758072,mushroom,cat,No,night owl,Maybe
+LEC006,18,Data Science,53715,38.9784,76.4922,mushroom,cat,No,early bird,Yes
+LEC004,20,Science: Other,53726,55.675758,12.56902,none (just cheese),cat,Yes,night owl,Yes
+LEC001,20,Science: Biology/Life,53715,40.713051,-74.007233,pineapple,cat,No,night owl,Maybe
+LEC004,18,Engineering: Industrial,53706,51.507351,-0.127758,pepperoni,dog,Yes,no preference,No
+LEC004,25,Computer Science,53703,38.736946,-9.142685,pepperoni,dog,No,night owl,Yes
+LEC002,18,Computer Science,53706,22.543097,114.057861,pepperoni,cat,No,no preference,Yes
+LEC004,25,Science: Chemistry,53703,37.566536,126.977966,Other,cat,Yes,night owl,Maybe
+LEC002,19,Engineering: Mechanical,53715,26.338,-81.775,pepperoni,dog,Yes,no preference,Maybe
+LEC005,19,Engineering: Mechanical,53715,33.448376,-112.074036,pepperoni,neither,Yes,early bird,No
+LEC005,19,Engineering: Mechanical,53703,43.073051,-89.40123,pepperoni,cat,No,no preference,Yes
+LEC001,19,Engineering: Mechanical,53705,26.647661,106.63015,mushroom,cat,No,night owl,No
+LEC003,18,Undecided,53706,43.2967,87.9876,pepperoni,dog,No,night owl,No
+LEC005,19,Science: Physics,53703,78.225,15.626,sausage,cat,No,early bird,No
+LEC002,,Science: Other|Environmetal Science,53703,52.973558,-9.425102,none (just cheese),dog,Yes,night owl,Maybe
+LEC006,19,Economics (Mathematical Emphasis),53715,37.774929,-122.419418,sausage,cat,Yes,night owl,Yes
+LEC002,20,Business: Finance,53703,40.7128,74.006,pineapple,dog,No,night owl,Yes
+LEC001,21,Science: Biology/Life,53703,44.794,-93.148,pepperoni,dog,No,night owl,No
+LEC002,19,Engineering: Mechanical,53706,36.17,-115.14,pepperoni,cat,No,night owl,Maybe
+LEC001,18,Engineering: Biomedical,53706,21.161907,-86.851524,none (just cheese),dog,No,early bird,Maybe
+LEC001,18,Computer Science,53715,48.856613,2.352222,pineapple,neither,Yes,no preference,No
+LEC004,19,Engineering: Mechanical,53715,48.137,11.576,green pepper,dog,No,early bird,No
+LEC001,20,Engineering: Biomedical,53703,43.07393,-89.38524,sausage,dog,No,night owl,Maybe
+LEC002,18,Science: Other,53706,35.6762,139.6503,Other,dog,No,no preference,Yes
+LEC004,19,Computer Science,53703,41.902782,12.496365,none (just cheese),neither,Yes,night owl,No
+LEC001,20,Science: Other|Atmospheric and Oceanic Sciences (AOS),53711,49.299171,19.94902,pepperoni,dog,No,night owl,Maybe
+LEC002,18,Data Science,53706,41.380898,2.12282,pepperoni,dog,No,night owl,Maybe
+LEC006,18,Data Science,53706,48.257919,4.03073,mushroom,cat,Yes,early bird,No
+LEC005,19,Engineering: Mechanical,53715,35.0844,106.6504,pineapple,dog,Yes,early bird,Yes
+LEC002,23,Economics,53703,121,5,pepperoni,neither,No,no preference,Maybe
+LEC004,18,Business: Actuarial,53706,21.306944,-157.858337,pineapple,dog,Yes,night owl,Maybe
+LEC005,18,Economics,53706,43,-87.9,pepperoni,dog,Yes,early bird,Maybe
+LEC005,23,Business: Other|Business Analytics,53703,31.230391,121.473701,pineapple,cat,Yes,night owl,Maybe
+LEC002,22,Psychology,53703,25.032969,121.565414,mushroom,dog,No,no preference,Yes
+LEC005,18,Computer Science,53706,43.0722,89.4008,sausage,cat,No,night owl,Yes
+LEC006,18,Data Science,53706,52.370216,4.895168,mushroom,dog,Yes,night owl,Maybe
+LEC004,20,Data Science,53703,35.726212,-83.491226,pepperoni,cat,No,early bird,Yes
+LEC001,18,Computer Science,53703,27,153,mushroom,cat,No,early bird,Yes
+LEC005,18,Data Science,53706,56.117017,-3.879547,pineapple,dog,Yes,night owl,Yes
+LEC001,20,Engineering: Biomedical,53715,45.983964,9.262161,sausage,dog,No,night owl,No
+LEC005,21,Psychology,53703,43.038902,-87.906471,macaroni/pasta,dog,Yes,night owl,Yes
+LEC002,18,Engineering: Mechanical,53706,41.38879,2.15084,sausage,dog,Yes,no preference,Maybe
+LEC003,18,Data Science,53706,47.48,-122.28,basil/spinach,dog,No,no preference,Maybe
+LEC004,21,Data Science,53703,34.746613,113.625328,green pepper,neither,Yes,no preference,No
+LEC005,21,Data Science,53703,38.240946,-85.757571,pepperoni,dog,No,no preference,Yes
+LEC005,19,Engineering: Mechanical,53703,43.07291,-89.39439,sausage,dog,No,night owl,Maybe
+LEC005,19,Engineering: Mechanical,53715,56.373482,-3.84306,none (just cheese),dog,No,early bird,Yes
+LEC005,19,Data Science,53703,41.381717,2.177925,pepperoni,dog,Yes,night owl,Yes
+LEC005,19,Engineering: Mechanical,53714,43.089199,87.8876,pepperoni,dog,No,night owl,Yes
+LEC005,19,Engineering: Other,53590,38.4,11.2,pepperoni,dog,Yes,early bird,No
+LEC005,19,Engineering: Mechanical,53715,25.761681,-80.191788,pepperoni,dog,Yes,night owl,No
+LEC005,19,Engineering: Mechanical,53703,44.5133,88.0133,mushroom,dog,Yes,night owl,Maybe
+LEC002,,Computer Science,53706,41.8781,87.6298,pepperoni,dog,No,night owl,Maybe
+LEC005,19,Business: Finance,53703,38.98378,-77.20871,none (just cheese),dog,Yes,night owl,Yes
+LEC005,18,Business: Finance,53703,22.9068,43.1729,pepperoni,dog,No,night owl,Yes
+LEC005,19,Engineering: Mechanical,53715,43.073051,-89.40123,pepperoni,dog,No,early bird,No
+LEC004,23,Economics,53703,43.083321,-89.372475,mushroom,dog,Yes,early bird,No
+LEC002,17,Business: Actuarial,53715,34.746613,113.625328,sausage,neither,Yes,night owl,Maybe
+LEC005,18,Engineering: Biomedical,53715,46.58276,7.08058,pepperoni,dog,No,early bird,No
+LEC001,20,Statistics,53715,39.904202,116.407394,mushroom,dog,Yes,early bird,No
+LEC002,18,Computer Science,53706,35.96691,-75.627823,sausage,dog,No,early bird,Yes
+LEC005,21,Mathematics/AMEP,53703,13.756331,100.501762,pepperoni,dog,No,night owl,Yes
+LEC005,20,Engineering: Biomedical,53715,28.538336,-81.379234,sausage,cat,No,night owl,Maybe
+LEC002,19,Engineering: Mechanical,53703,44.822783,-93.370743,sausage,dog,Yes,early bird,No
+LEC005,19,Engineering: Mechanical,53715,42.15,-87.96,pepperoni,dog,No,night owl,Yes
+LEC005,20,Journalism,53715,41.3874,2.1686,basil/spinach,dog,Yes,early bird,Maybe
+LEC001,19,Engineering: Mechanical,53703,42.864552,-88.333199,pepperoni,dog,No,early bird,Maybe
+LEC005,17,Data Science,53706,40.7128,74.006,macaroni/pasta,dog,No,night owl,Yes
+LEC005,19,Science: Other|Politcal Science,53703,41.878113,-87.629799,pepperoni,dog,Yes,night owl,No
+LEC002,20,Business: Finance,53703,40.7831,73.9712,sausage,dog,Yes,night owl,No
+LEC004,20,Data Science,53703,43,87.9,none (just cheese),dog,No,night owl,Yes
+LEC001,18,Data Science,53706,38.900497,-77.007507,pineapple,dog,No,night owl,Maybe
+LEC005,18,Engineering: Industrial,53706,45.440845,12.315515,sausage,dog,No,night owl,Maybe
+LEC002,19,Data Science,53715,25.73403,-80.24697,pepperoni,dog,Yes,night owl,Yes
+LEC005,18,Political Science,53706,42.360081,-71.058884,macaroni/pasta,dog,Yes,night owl,Yes
+LEC002,20,Economics,53703,41.878113,-87.629799,pepperoni,dog,Yes,no preference,Maybe
+LEC004,18,Engineering: Mechanical,55088,48.135124,11.581981,pepperoni,dog,Yes,no preference,No
+LEC002,23,Business: Information Systems,53703,37.566536,126.977966,sausage,dog,No,night owl,Maybe
+LEC005,17,Data Science,53703,49.2827,123.1207,sausage,dog,Yes,night owl,Yes
+LEC005,,Statistics,53726,40.712776,-74.005974,Other,dog,Yes,no preference,Yes
+LEC001,18,Science: Biology/Life,53706,48.856613,2.352222,pepperoni,cat,Yes,early bird,No
+LEC005,32,Communication Sciences and Disorder,53705,37.566536,126.977966,pineapple,dog,Yes,no preference,Yes
+LEC001,18,Data Science,53706,41.878113,-87.629799,macaroni/pasta,dog,No,night owl,Yes
+LEC002,17,Business: Information Systems,53706,-6.17511,106.865036,sausage,neither,No,no preference,Maybe
+LEC002,25,Science: Other|Geoscience,53711,46.947975,7.447447,mushroom,cat,No,no preference,Yes
+LEC002,20,Economics,53703,46.7867,92.1005,macaroni/pasta,neither,Yes,early bird,No
+LEC002,21,Business: Other|Marketing,53703,20.878332,-156.682495,basil/spinach,dog,No,night owl,Yes
+LEC001,19,Statistics,53703,52.370216,4.895168,sausage,dog,No,night owl,Maybe
+LEC005,20,Engineering: Biomedical,53711,35.689487,139.691711,basil/spinach,dog,No,night owl,Yes
+LEC005,22,Science: Other|Atmospheric and oceanic science,53703,26.1224,80.1373,pepperoni,dog,No,early bird,No
+LEC001,18,Engineering: Mechanical,53726,21.306944,-157.858337,sausage,dog,No,night owl,Yes
+LEC005,21,Business: Finance,53703,43.11339,-89.37726,sausage,dog,No,night owl,Yes
+LEC001,,Business: Other,53703,22.396427,114.109497,Other,dog,No,early bird,Maybe
+LEC004,19,Science: Biology/Life,53706,41.2,96,pepperoni,cat,No,early bird,No
+LEC004,18,Engineering: Industrial,53706,49.74609,7.4609,pepperoni,cat,No,early bird,Yes
+LEC004,20,Science: Other|Environmental Science,53715,43,-89,mushroom,dog,Yes,night owl,Maybe
+LEC001,18,Business: Finance,53706,39.7392,104.9903,pepperoni,dog,No,early bird,No
+LEC002,,Computer Science,53706,41.67566,-86.28645,pineapple,cat,No,no preference,Maybe
+LEC002,18,Business: Other,53706,33.88509,-118.409714,green pepper,dog,Yes,night owl,No
+LEC001,20,Engineering: Biomedical,53711,41.8781,87.6298,pepperoni,dog,No,night owl,Yes
+LEC002,20,Data Science,53715,10.97285,106.477707,mushroom,dog,No,no preference,Maybe
+LEC002,20,Computer Science,53703,36.16156,-75.752441,pepperoni,dog,Yes,no preference,Yes
+LEC002,20,Business: Other|Marketing,53703,35.689487,139.691711,pepperoni,dog,Yes,night owl,Yes
+LEC002,18,Engineering: Other|Engineering Mechanics,53706,35.689487,139.691711,mushroom,cat,No,night owl,Maybe
+LEC002,21,Economics (Mathematical Emphasis),53703,46.25872,-91.745583,sausage,dog,Yes,no preference,Yes
+LEC002,19,Mathematics,53703,39.904202,116.407394,tater tots,cat,No,night owl,Yes
+LEC002,18,Data Science,53703,40.706067,-74.030063,pepperoni,dog,No,night owl,Yes
+LEC002,19,Pre-Business,53703,39.60502,-106.51641,pepperoni,dog,Yes,early bird,No
+LEC002,20,Mathematics/AMEP,53703,35.106766,-106.629181,green pepper,cat,No,night owl,Yes
+LEC003,20,Science: Physics,53715,64.963051,-19.020836,mushroom,dog,No,night owl,Yes
+LEC002,20,Business: Finance,53703,31.298973,120.585289,pineapple,cat,Yes,night owl,No
+LEC002,18,Economics,53706,48.856613,2.352222,basil/spinach,dog,No,night owl,Maybe
+LEC001,21,Data Science,53703,40.712776,-74.005974,sausage,dog,No,night owl,Yes
+LEC002,19,Engineering: Industrial,53715,45.914,-89.255,sausage,dog,Yes,early bird,Yes
+LEC002,19,Computer Science,53703,20,110,pineapple,cat,No,night owl,Maybe
+LEC002,19,Engineering: Mechanical,53726,41.878113,-87.629799,basil/spinach,dog,No,early bird,Yes
+LEC005,19,Computer Science,53715,48.8566,2.3522,sausage,dog,No,night owl,Maybe
+LEC002,19,Industrial Engineering,53703,48.856613,2.352222,basil/spinach,dog,No,early bird,Yes
+LEC002,18,Data Science,53706,43.073051,-89.40123,pepperoni,dog,Yes,night owl,Yes
+LEC002,20,Statistics,53703,31.224361,121.46917,mushroom,dog,No,no preference,Maybe
+LEC002,18,Computer Science,53706,35.689487,139.691711,green pepper,dog,No,night owl,Yes
+LEC002,18,Computer Science,53706,25.03841,121.563698,pineapple,dog,No,night owl,Yes
+LEC002,19,Engineering: Mechanical,53715,43.06827,-89.40263,sausage,dog,No,night owl,No
+LEC002,18,Engineering: Mechanical,53703,43,89.4,pepperoni,cat,No,no preference,Maybe
+LEC002,,Mechanical Engineering,53703,41.8781,87.6298,Other,dog,Yes,night owl,Yes
+LEC002,26,Science: Other,57075,42.76093,-89.9589,Other,dog,Yes,early bird,No
+LEC002,21,Science: Other|Environmental science,53714,47.606209,-122.332069,pepperoni,dog,Yes,early bird,Yes
+LEC002,18,Data Science,53706,35.69,139.69,pineapple,cat,No,night owl,Yes
+LEC002,18,Computer Science,53706,42.807091,-86.01886,none (just cheese),cat,Yes,early bird,Yes
+LEC002,19,Engineering: Mechanical,53703,45.892099,8.997803,green pepper,dog,No,night owl,Yes
+LEC002,20,Computer Science,53715,40.755645,-74.034119,sausage,dog,Yes,night owl,Yes
+LEC001,18,Engineering: Mechanical,53066,43.073051,-89.40123,pepperoni,dog,No,night owl,Yes
+LEC002,18,Data Science,53706,21.306944,-157.858337,pineapple,dog,No,night owl,No
+LEC002,18,Engineering: Industrial,53706,32.0853,34.781769,pepperoni,dog,No,night owl,Maybe
+LEC002,19,Engineering: Mechanical,53703,46.786671,-92.100487,sausage,dog,No,early bird,No
+LEC002,19,Engineering: Mechanical,53715,42.590519,-88.435287,pepperoni,dog,No,early bird,No
+LEC002,23,Data Science,53703,37,127,pineapple,dog,No,night owl,Yes
+LEC002,20,Data Science,53703,43.06875,-89.39434,pepperoni,dog,Yes,no preference,Maybe
+LEC002,20,Engineering: Mechanical,53703,41.499321,-81.694359,pepperoni,dog,Yes,night owl,Maybe
+LEC002,21,Economics,53703,38.969021,-0.18516,sausage,dog,Yes,no preference,No
+LEC002,20,Economics,53703,50.85,4.35,pepperoni,dog,No,no preference,Yes
+LEC002,19,Data Science,53715,36.39619,10.61412,none (just cheese),cat,No,no preference,Yes
+LEC002,20,Engineering: Mechanical,53711,43.073051,-89.40123,green pepper,dog,Yes,night owl,No
+LEC002,30,Life Sciences Communication,53562,52.399448,0.25979,basil/spinach,cat,Yes,night owl,Yes
+LEC002,20,Business: Finance,53703,41.878,-87.629799,pepperoni,dog,No,no preference,Yes
+LEC002,18,Computer Science,53706,31.2304,121.4737,pepperoni,cat,No,night owl,Maybe
+LEC005,22,Economics,53711,48.135124,11.581981,pepperoni,cat,Yes,no preference,Yes
+LEC002,19,Engineering: Mechanical,53711,51.5,0.1276,pepperoni,dog,No,night owl,No
+LEC001,18,Computer Science,53703,31.298973,120.585289,pineapple,neither,No,night owl,No
+LEC001,19,Computer Science,53703,37,-97,macaroni/pasta,cat,No,no preference,Maybe
+LEC002,19,International Studies,53703,8.25115,34.588348,none (just cheese),dog,Yes,early bird,Maybe
+LEC001,19,Engineering: Mechanical,53703,43.038902,-87.906471,pineapple,cat,No,night owl,Yes
+LEC001,19,Science: Other|Atmospheric and Oceanic Sciences,53703,48.856613,2.352222,pepperoni,dog,Yes,night owl,Yes
+LEC004,20,Data Science,53703,41.878113,-87.629799,green pepper,dog,No,early bird,Yes
+LEC004,18,Undecided,53706,39.3823,87.2971,sausage,dog,Yes,early bird,No
+LEC004,21,Data Science,53703,31.230391,121.473701,mushroom,cat,No,night owl,Maybe
+LEC001,18,Data Science,53706,32.776474,-79.931053,none (just cheese),dog,No,early bird,Yes
+LEC006,18,Science: Physics,53706,43.073051,-89.40123,sausage,dog,No,night owl,Yes
+LEC001,19,Economics,53703,35.689487,139.691711,pineapple,dog,Yes,night owl,Yes
+LEC004,18,Data Science,53715,50.8,-1.085,Other,dog,No,night owl,Maybe
+LEC002,21,Languages,53703,37.389091,-5.984459,mushroom,cat,No,early bird,No
+LEC001,19,Rehabilitation Psychology,53706,36.204823,138.25293,pineapple,cat,No,no preference,Maybe
+LEC006,18,Data Science,53705,37.5741,122.3794,pepperoni,dog,Yes,night owl,Yes
+LEC004,18,Undecided,53706,26.452,-81.9481,pepperoni,dog,Yes,night owl,Yes
+LEC002,19,Business: Actuarial,53703,37.774929,-122.419418,pineapple,dog,No,early bird,No
+LEC005,18,Undecided,53706,55.676098,12.568337,pepperoni,dog,Yes,night owl,No
+LEC001,19,Engineering: Mechanical,53703,43.073051,-89.40123,pepperoni,dog,Yes,night owl,Yes
+LEC002,18,Statistics,53706,40.713051,-74.007233,none (just cheese),dog,No,night owl,Maybe
+LEC003,21,Languages,53511,39.952583,-75.165222,pepperoni,dog,No,night owl,Yes
+LEC002,18,Computer Science,53706,12.523579,-70.03355,pineapple,dog,No,night owl,Yes
+LEC004,,Engineering: Biomedical,53715,41.878113,-87.629799,pepperoni,dog,Yes,night owl,No
+LEC001,,Data Science,53701,40.37336,88.231483,pepperoni,dog,Yes,night owl,No
+LEC001,19,Data Science,53703,51.5072,0.1276,pepperoni,dog,Yes,no preference,No
+LEC002,18,Data Science,53706,47.987289,0.22367,none (just cheese),dog,Yes,night owl,Maybe
+LEC002,19,Business: Actuarial,53715,45.17963,-87.150009,sausage,dog,Yes,no preference,No
+LEC005,21,Science: Biology/Life,53703,21.23556,-86.73142,pepperoni,dog,Yes,night owl,Yes
+LEC004,18,Engineering: Industrial,53706,43.073051,-89.40123,sausage,dog,No,night owl,Yes
+LEC001,21,Science: Biology/Life,53715,41.878113,-87.629799,green pepper,cat,No,night owl,Yes
+LEC001,20,Engineering: Biomedical,53703,48.8566,2.3522,mushroom,cat,Yes,night owl,Maybe
+LEC005,19,Engineering: Mechanical,53703,49.28273,-123.120735,basil/spinach,dog,No,night owl,Yes
+LEC001,19,Data Science,53706,37.23082,-107.59529,basil/spinach,dog,No,no preference,Maybe
+LEC001,19,Business: Finance,53703,26.20047,127.728577,mushroom,dog,No,night owl,Maybe
+LEC006,18,Statistics,53706,32.060253,118.796875,pineapple,cat,Yes,early bird,Maybe
+LEC002,20,Business: Information Systems,53706,52.520008,13.404954,none (just cheese),dog,No,early bird,Yes
+LEC006,18,Undecided,53706,43.038902,-87.906471,sausage,dog,No,night owl,Yes
+LEC002,20,Accounting,53703,32.79649,-117.192123,mushroom,dog,No,no preference,Yes
+LEC006,19,Statistics,53715,21.315603,-157.858093,pepperoni,cat,No,night owl,No
+LEC004,20,Science: Biology/Life,53706,13.756331,100.501762,pineapple,neither,No,night owl,Yes
+LEC004,20,Business: Other,53715,42.818878,-89.494115,pepperoni,dog,No,night owl,Yes
+LEC001,19,Engineering: Mechanical,53703,44.9778,93.265,pepperoni,dog,Yes,night owl,Maybe
+LEC004,18,Engineering: Industrial,53706,41.3874,2.1686,none (just cheese),dog,No,night owl,Maybe
+LEC001,37,Engineering: Other|Civil- Intelligent Transportation System,53705,23.810331,90.412521,pineapple,neither,Yes,early bird,Yes
+LEC001,19,Science: Physics,53703,42.696842,-89.026932,sausage,cat,No,night owl,Yes
+LEC006,19,Data Science,53715,53.266479,-9.052602,macaroni/pasta,dog,No,no preference,Yes
+LEC001,19,Data Science,53703,45.19356,-87.118767,pepperoni,dog,Yes,early bird,Maybe
+LEC005,18,Engineering: Industrial,53715,21.306944,-157.858337,none (just cheese),dog,Yes,night owl,Maybe
+LEC004,19,Computer Science,53703,40.678177,-73.94416,Other,cat,No,night owl,Maybe
+LEC005,18,Science: Biology/Life,53706,44.513317,-88.013298,pepperoni,dog,Yes,night owl,No
+LEC001,19,Engineering: Mechanical,53703,40.712776,-74.005974,none (just cheese),dog,Yes,early bird,Maybe
+LEC002,22,Economics,53703,37.6,127,pineapple,neither,Yes,night owl,Maybe
+LEC004,20,Engineering: Industrial,53703,39.359772,-111.584167,pepperoni,dog,Yes,early bird,Maybe
+LEC001,19,Data Science,53706,31.298973,120.585289,mushroom,cat,No,night owl,Yes
+LEC001,20,Computer Science,53715,43.073051,-89.40123,none (just cheese),dog,No,night owl,Maybe
+LEC001,25,Data Science,53703,37.566536,126.977966,pineapple,dog,Yes,night owl,No
+LEC005,19,Data Science,53706,36.169941,-115.139832,pepperoni,dog,Yes,night owl,Yes
+LEC001,19,Engineering: Mechanical,53703,44.834209,87.376266,sausage,dog,Yes,no preference,Yes
+LEC005,20,Engineering: Mechanical,53703,43.17854,-89.163391,sausage,dog,Yes,night owl,Maybe
+LEC004,19,Engineering: Industrial,53703,41.93101,-87.64987,pepperoni,neither,No,early bird,No
+LEC003,19,Engineering: Industrial,53703,11.89,-85,pepperoni,dog,Yes,night owl,Maybe
+LEC003,19,Engineering: Mechanical,53715,33.873417,-115.900993,pepperoni,dog,No,early bird,No
+LEC001,22,Economics,53703,42.360081,-71.058884,pepperoni,dog,No,no preference,Maybe
+LEC001,18,Data Science,53706,34.04018,-118.48849,pepperoni,dog,Yes,night owl,Yes
+LEC002,42069,Data Science,53704,43,-89,none (just cheese),neither,No,no preference,No
+LEC004,20,Business: Finance,53715,38.71049,-75.07657,sausage,dog,No,early bird,No
+LEC004,21,Engineering: Mechanical,53715,43.073051,-89.40123,Other,dog,Yes,early bird,No
+LEC004,18,Engineering: Industrial,53706,44.261799,-88.407249,sausage,dog,Yes,night owl,No
+LEC004,26,Science: Other|Animal and Dairy Science,53705,53.270668,-9.05679,pepperoni,dog,No,early bird,Yes
+LEC005,20,Data Science,53715,43.355099,11.02956,sausage,dog,No,early bird,Maybe
+LEC003,19,Engineering: Mechanical,53715,45.40857,-91.73542,sausage,dog,Yes,no preference,No
+LEC004,22,Engineering: Mechanical,53726,55.864239,-4.251806,pepperoni,dog,Yes,night owl,Yes
+LEC001,18,Engineering: Mechanical,53706,50.808712,-0.1604,pepperoni,dog,Yes,night owl,Maybe
+LEC004,19,Engineering: Mechanical,53703,13.35433,103.77549,none (just cheese),dog,No,no preference,Maybe
+LEC005,24,Mathematics/AMEP,53705,40.7,-74,pineapple,cat,No,early bird,Maybe
+LEC001,19,Interior Architecture,53532,27.683536,-82.736092,mushroom,cat,Yes,no preference,Yes
+LEC001,19,Science: Chemistry,53715,40.7,-74,sausage,dog,No,night owl,Maybe
+LEC001,20,Engineering: Biomedical,53703,-33.86882,151.20929,pepperoni,dog,No,no preference,Maybe
+LEC001,20,Engineering: Industrial,53715,26.614149,-81.825768,pepperoni,dog,No,night owl,No
+LEC001,19,Engineering: Biomedical,53706,45.440845,12.315515,none (just cheese),dog,Yes,night owl,Yes
+LEC001,19,Data Science,53726,43.0766,89.4125,none (just cheese),cat,No,night owl,No
+LEC001,20,Engineering: Biomedical,53711,33.684566,-117.826508,pineapple,dog,Yes,early bird,Maybe
+LEC001,21,Statistics,26617,22.396427,114.109497,pineapple,dog,Yes,night owl,Maybe
+LEC001,18,Data Science,53706,-33.86882,151.20929,pepperoni,dog,Yes,night owl,No
+LEC001,21,Economics,53703,1.53897,103.58007,pineapple,neither,Yes,night owl,Yes
+LEC001,18,Data Science,53558,41.877541,-88.066727,mushroom,dog,No,night owl,Maybe
+LEC001,17,Computer Science,53703,25.204849,55.270782,pepperoni,dog,Yes,night owl,Yes
+LEC001,19,Engineering: Mechanical,53715,19.7,-155,pineapple,dog,Yes,early bird,Yes
+LEC001,19,Data Science,53703,41.878113,-87.629799,none (just cheese),cat,Yes,night owl,Yes
+LEC001,18,Science: Biology/Life,53715,39.904202,116.407394,basil/spinach,dog,Yes,night owl,Maybe
+LEC001,20,Science: Physics,53711,43.038902,-87.906471,pepperoni,dog,No,no preference,Yes
+LEC001,18,Engineering: Mechanical,53706,41.902782,12.496366,pepperoni,neither,Yes,night owl,Yes
+LEC001,18,Data Science,53706,47.60323,-122.330276,Other,dog,No,night owl,Yes
+LEC001,19,Economics,53706,40.7,74,none (just cheese),dog,Yes,night owl,Yes
+LEC001,19,Business: Finance,53703,34.052235,-118.243683,mushroom,dog,Yes,early bird,Maybe
+LEC001,20,Science: Other|Atmospheric & Oceanic Sciences,53711,40.412776,-74.005974,pepperoni,neither,No,early bird,Yes
+LEC001,19,Computer Science,53706,37.774929,-122.419418,none (just cheese),cat,No,early bird,Yes
+LEC001,20,Engineering: Mechanical,53703,44.78441,-93.17308,pepperoni,dog,Yes,no preference,Yes
+LEC001,22,Engineering: Other,53726,39.48214,-106.048691,pineapple,cat,No,no preference,Maybe
+LEC001,21,Computer Science,53703,33.68,-117.82,basil/spinach,cat,No,early bird,No
+LEC001,17,Computer Science,53706,25.204849,55.270782,pepperoni,neither,Yes,no preference,Maybe
+LEC001,18,Engineering: Industrial,53706,41.917519,-87.694771,basil/spinach,dog,Yes,night owl,Yes
+LEC001,18,Engineering: Biomedical,53706,42.361145,-71.057083,macaroni/pasta,dog,No,night owl,Yes
+LEC001,,Engineering: Biomedical,53703,43.073929,-89.385239,basil/spinach,dog,No,early bird,No
+LEC001,18,Economics,53706,30.20241,120.226822,Other,neither,Yes,early bird,No
+LEC001,20,Engineering: Biomedical,53703,41.198496,0.773436,pepperoni,dog,No,night owl,Yes
+LEC001,19,Engineering: Mechanical,53703,39.739235,-104.99025,pepperoni,dog,Yes,no preference,Maybe
+LEC001,20,Science: Chemistry,53703,32.16761,120.012444,pepperoni,neither,No,night owl,Maybe
+LEC001,19,Data Science,53703,43.0722,89.4008,pineapple,dog,Yes,night owl,Yes
+LEC001,18,Science: Biology/Life,53715,41.878113,-87.629799,sausage,dog,Yes,early bird,No
+LEC004,,Business: Information Systems,53715,42.360081,-71.058884,Other,dog,No,no preference,Maybe
+LEC001,21,Engineering: Biomedical,53703,44.513317,-88.013298,pepperoni,dog,No,night owl,No
+LEC001,20,Data Science,53132,43.073051,-89.40123,Other,cat,No,night owl,Maybe
+LEC001,18,Business: Actuarial,53706,48.856613,2.352222,sausage,dog,No,no preference,Maybe
+LEC001,20,Political Science,53715,48.135124,11.581981,sausage,cat,Yes,night owl,Yes
+LEC001,19,Engineering: Industrial,53703,41,-74,sausage,dog,Yes,no preference,No
+LEC001,20,Psychology,53703,43.083321,-89.372475,Other,neither,No,night owl,Yes
+LEC001,18,Computer Science and Statistics,53706,36.162663,-86.781601,mushroom,dog,Yes,early bird,Maybe
+LEC001,19,Engineering: Mechanical,53703,25.88,-80.16,pepperoni,dog,No,night owl,Yes
+LEC001,18,Computer Science,53703,46.947975,7.447447,sausage,cat,Yes,night owl,No
+LEC001,19,Business: Information Systems,53703,41.17555,73.64731,pepperoni,dog,No,night owl,Maybe
+LEC001,20,Political Science,53703,45.018269,-93.473892,sausage,dog,No,night owl,Maybe
+LEC001,,Business analytics,53705,45.50169,-73.567253,pineapple,cat,No,no preference,No
+LEC001,21,Science: Biology/Life,53726,32.060253,118.796875,mushroom,cat,No,night owl,No
+LEC001,19,Engineering: Mechanical,53706,35.806,-78.68483,none (just cheese),dog,No,night owl,Yes
+LEC005,20,Data Science,53726,31.230391,121.473701,none (just cheese),dog,Yes,no preference,Maybe
+LEC005,18,Engineering: Mechanical,53706,41.878113,-87.629799,Other,cat,No,night owl,Maybe
+LEC004,18,Statistics,53706,27.35741,-82.615471,none (just cheese),dog,Yes,early bird,No
+LEC002,20,Business: Finance,53715,35.726212,-83.491226,pepperoni,dog,Yes,no preference,Yes
+LEC002,18,Undecided,53706,43.769562,11.255814,pepperoni,dog,No,night owl,Yes
+LEC004,19,Business: Actuarial,53703,43.040433,-87.897423,sausage,cat,No,night owl,No
+LEC004,19,Engineering: Mechanical,5,25.034281,-77.396278,sausage,dog,Yes,no preference,Yes
+LEC001,,Engineering: Mechanical,53706,34.052235,-118.243683,Other,dog,Yes,night owl,Yes
+LEC003,18,Engineering: Industrial,53706,20.798363,-156.331924,none (just cheese),dog,Yes,early bird,No
+LEC002,19,Engineering: Biomedical,53703,51.1784,115.5708,pineapple,dog,Yes,night owl,No
+LEC005,19,Statistics,53703,43.05367,-88.44062,pepperoni,dog,Yes,night owl,No
+LEC004,18,Engineering: Industrial,53706,36.110168,-97.058571,none (just cheese),dog,No,early bird,Maybe
+LEC004,21,Computer Science,53703,43.07016,-89.39386,mushroom,cat,Yes,early bird,No
+LEC005,19,Data Science,53726,43.073051,-89.40123,pepperoni,dog,No,early bird,Yes
+LEC004,18,Data Science,53706,41.878113,-87.629799,macaroni/pasta,dog,Yes,early bird,Maybe
+LEC001,20,Business: Finance,53726,43.073051,-89.40123,pepperoni,dog,No,night owl,Maybe
+LEC001,18,Data Science,53706,43.038902,-87.906471,pineapple,dog,No,night owl,Maybe
+LEC001,24,Engineering: Other,53718,46.77954,-90.78511,pineapple,dog,Yes,night owl,No
+LEC001,18,Statistics,53706,22.57,88.36,pineapple,dog,Yes,night owl,Maybe
+LEC004,20,Computer Science,53715,35.016956,-224.24911,pepperoni,dog,No,night owl,Yes
+LEC001,20,Science: Biology/Life,53715,47.606209,-122.332069,none (just cheese),dog,Yes,night owl,Maybe
+LEC004,18,Engineering: Industrial,53706,21.28482,-157.83245,pineapple,dog,No,night owl,Yes
+LEC001,20,Engineering: Biomedical,53715,40.63,14.6,none (just cheese),dog,No,early bird,Maybe
+LEC004,20,Legal Studies,53703,20.798363,-156.331924,green pepper,dog,No,early bird,No
+LEC002,18,Computer Science,53706,32.060253,118.796875,sausage,dog,Yes,early bird,Maybe
+LEC002,18,Journalism,53706,31,103,none (just cheese),cat,No,night owl,Yes
+LEC004,,Computer Science,53706,147,32.5,pineapple,cat,No,early bird,Maybe
+LEC004,18,Engineering: Biomedical,53701,43.038902,-87.906471,pepperoni,dog,No,night owl,No
+LEC004,18,Engineering: Mechanical,20815,39.640259,-106.370872,sausage,dog,No,night owl,No
+LEC004,19,Engineering: Mechanical,53715,41,12,pepperoni,dog,No,no preference,Maybe
+LEC004,20,Journalism: Strategic Comm./Advertising,53703,43.073051,-89.40123,Other,dog,Yes,night owl,Yes
+LEC004,,Engineering: Mechanical,53715,43,-87.9,pepperoni,cat,Yes,early bird,Maybe
+LEC004,19,Engineering: Biomedical,53706,32.715736,117.161087,pepperoni,dog,Yes,no preference,Yes
+LEC004,18,Data Science,53706,43.073051,-89.40123,pepperoni,dog,No,night owl,Yes
+LEC004,18,History,53706,42.19381,-73.362877,none (just cheese),cat,Yes,night owl,Yes
+LEC002,19,Engineering: Mechanical,53703,39.290386,-76.61219,mushroom,dog,No,no preference,No
+LEC002,19,Engineering: Mechanical,53726,40.416775,-3.70379,macaroni/pasta,dog,No,early bird,Maybe
+LEC005,19,Engineering: Mechanical,53726,46.870899,-89.313789,sausage,dog,Yes,night owl,Maybe
+LEC004,19,Science: Biology/Life,53151,41.878113,-87.629799,sausage,dog,No,night owl,Yes
+LEC005,18,Data Science,53711,35.1796,129.0756,pepperoni,cat,Yes,night owl,Yes
+LEC004,18,Data Science,53706,37.568291,126.99778,pepperoni,dog,No,no preference,Maybe
+LEC005,17,Statistics,53706,31.23,121.47,sausage,cat,No,night owl,Maybe
+LEC003,19,Undecided,53715,43.041069,-87.909416,mushroom,dog,No,no preference,Maybe
+LEC005,19,Economics,53703,47.606209,-122.332069,pineapple,neither,No,no preference,Maybe
+LEC005,21,Science: Biology/Life,53726,40.76078,-111.891045,mushroom,dog,No,no preference,Yes
+LEC003,19,Engineering: Mechanical,53706,43,-88.27,Other,dog,No,night owl,Yes
+LEC003,20,Business: Other|Accounting,53726,43,-89,pepperoni,dog,Yes,early bird,Yes
+LEC005,18,Engineering: Other,53706,64.147209,-21.9424,pepperoni,dog,No,night owl,Yes
+LEC003,18,Data Science,53562,42.66544,21.165319,pepperoni,dog,No,night owl,Yes
+LEC005,22,Data Science,53711,39.738449,-104.984848,none (just cheese),dog,No,night owl,Yes
+LEC003,18,Engineering: Mechanical,53706,33.748997,-84.387985,mushroom,dog,No,night owl,Yes
+LEC004,19,Engineering: Mechanical,53717,41.2224,86.413,Other,dog,Yes,early bird,Maybe
+LEC003,19,Business: Actuarial,53706,39.299236,-76.609383,pineapple,dog,Yes,night owl,No
+LEC001,,Engineering: Mechanical,53703,32.776665,-96.796989,sausage,dog,No,night owl,Maybe
+LEC004,19,Engineering: Biomedical,53703,41.878113,-87.629799,pepperoni,dog,Yes,no preference,Yes
+LEC004,26,Master of Public Affairs,53715,48.118145,-123.43074,basil/spinach,dog,Yes,early bird,Yes
+LEC004,19,Engineering: Mechanical,53703,-12.12168,-45.013481,basil/spinach,dog,No,night owl,Yes
+LEC004,18,Data Science,53706,31.230391,121.473701,sausage,cat,No,night owl,No
+LEC005,21,Engineering: Industrial,53715,1.352083,103.819839,none (just cheese),neither,No,night owl,Yes
+LEC004,19,Engineering: Mechanical,53703,40.712776,-74.005974,sausage,dog,No,early bird,No
+LEC004,19,Engineering: Mechanical,53715,37.98381,23.727539,basil/spinach,dog,Yes,early bird,No
+LEC005,20,Business: Actuarial,53703,45.003288,-90.329788,sausage,dog,No,early bird,Maybe
+LEC005,20,Engineering: Mechanical,53703,43.073051,-89.40123,pepperoni,dog,Yes,early bird,No
+LEC001,21,Economics,53703,41.902782,12.496365,basil/spinach,dog,No,no preference,No
+LEC004,18,Engineering: Biomedical,53706,45.4894,93.2476,mushroom,cat,No,night owl,No
+LEC005,19,Data Science,53703,43.2708,89.7221,sausage,dog,Yes,night owl,No
+LEC003,,Engineering: Mechanical,53706,45.87128,-89.711632,pepperoni,neither,Yes,no preference,Yes
+LEC004,19,Engineering: Mechanical,53715,42.360081,-71.058884,pepperoni,dog,Yes,night owl,Maybe
+LEC004,18,Engineering: Mechanical,53706,45.056389,-92.960793,pepperoni,dog,No,night owl,Yes
+LEC003,,Computer Science,53703,43.07,-89.4,pepperoni,dog,Yes,no preference,Maybe
+LEC001,20,Business: Finance,53703,22.20315,-159.495651,Other,dog,Yes,no preference,No
+LEC005,19,Engineering: Mechanical,53703,44.74931,-92.80088,pineapple,dog,No,early bird,No
+LEC004,21,Business: Actuarial,53726,38.874341,-77.032013,pepperoni,dog,No,no preference,Yes
+LEC005,19,Engineering: Mechanical,53703,18.34791,-64.71424,basil/spinach,dog,No,night owl,No
+LEC004,18,Engineering: Mechanical,53703,27.5041,82.7145,sausage,dog,No,night owl,Maybe
+LEC005,19,Engineering: Biomedical,53706,36.462,25.375465,basil/spinach,dog,No,night owl,No
+LEC004,27,Environment & Resources,53703,37.389091,-5.984459,mushroom,dog,No,night owl,Maybe
+LEC004,19,Business: Actuarial,53726,32,-117,pepperoni,neither,Yes,night owl,Yes
+LEC005,20,Science: Physics,53703,46.2833,-89.73,pepperoni,dog,No,early bird,Maybe
+LEC003,19,Engineering: Industrial,53703,40.712776,-74.005974,basil/spinach,dog,Yes,night owl,No
+LEC003,18,Data Science,53706,40.712776,-74.005974,Other,dog,Yes,early bird,No
+LEC005,,Data Science,53703,43.073051,-89.40123,pepperoni,dog,No,night owl,No
+LEC004,21,Business: Actuarial,53703,39.19067,-106.819199,macaroni/pasta,cat,No,no preference,Maybe
+LEC006,18,Engineering: Industrial,53706,37.743042,-122.415642,green pepper,dog,Yes,no preference,No
+LEC003,20,Economics,53703,22.54,114.05,pineapple,dog,No,night owl,Yes
+LEC006,18,Data Science,53706,59.93428,30.335098,pineapple,dog,Yes,night owl,Maybe
+LEC004,19,Engineering: Mechanical,53715,45.10994,-87.209793,pepperoni,dog,Yes,early bird,No
+LEC002,20,Science: Biology/Life,53703,51.507351,-0.127758,pepperoni,dog,Yes,no preference,Yes
+LEC004,18,Environmental Studies,53703,42.360081,-71.058884,pineapple,cat,No,no preference,Maybe
+LEC004,19,Engineering: Mechanical,53715,45,-87,sausage,cat,Yes,no preference,Maybe
+LEC004,19,Engineering: Mechanical,53703,48.137,11.575,pepperoni,dog,Yes,night owl,Maybe
+LEC004,20,Engineering: Industrial,53711,48.856613,2.352222,sausage,cat,No,no preference,No
+LEC004,18,Science: Other,53706,48.410648,-114.338188,none (just cheese),dog,No,no preference,Maybe
+LEC004,18,Mathematics/AMEP,53706,24.585445,73.712479,pineapple,dog,Yes,night owl,Maybe
+LEC003,18,Data Science,53706,36.974117,-122.030792,pepperoni,cat,Yes,night owl,Yes
+LEC004,19,Computer Science,53715,40.79254,-98.70807,pepperoni,dog,Yes,night owl,No
+LEC005,19,Engineering: Mechanical,53711,30.572815,104.066803,pineapple,dog,No,night owl,Yes
+LEC001,21,Science: Chemistry,53715,3.139003,101.686852,pepperoni,neither,No,no preference,Maybe
+LEC006,18,Data Science,53706,40.46,-90.67,sausage,dog,No,night owl,No
+LEC004,20,Science: Other|Environmental Science,53715,43.073051,-89.40123,sausage,dog,No,night owl,Yes
+LEC004,20,Engineering: Biomedical,53715,30.328227,-86.136975,pepperoni,dog,Yes,no preference,Maybe
+LEC004,21,Science: Biology/Life,53703,41.385063,2.173404,macaroni/pasta,dog,No,night owl,Yes
+LEC003,18,Mathematics/AMEP,53706,42.99571,-90,sausage,dog,Yes,night owl,Yes
+LEC004,19,Engineering: Mechanical,53703,41.385063,2.173404,sausage,dog,Yes,night owl,Yes
+LEC001,,Engineering: Industrial,53706,40.7128,74.006,pepperoni,dog,No,early bird,Yes
+LEC005,18,Psychology,53706,9.167414,77.876747,mushroom,cat,No,early bird,No
+LEC003,19,Engineering: Industrial,53715,24.713552,46.675297,basil/spinach,neither,Yes,early bird,Maybe
+LEC001,18,Undecided,53706,44.8341,87.377,basil/spinach,dog,No,no preference,Yes
+LEC003,19,Engineering: Mechanical,53705,46.589146,-112.039108,none (just cheese),cat,No,night owl,Yes
+LEC001,20,Economics,53703,39.631506,118.143239,pineapple,dog,No,night owl,Maybe
\ No newline at end of file
diff --git a/f22/meena_lec_notes/lec-14/lec_14_lists.ipynb b/f22/meena_lec_notes/lec-14/lec_14_lists.ipynb
index 39feb84f270e81c03729b52ccc651dab8bcafeeb..488b76286a97c80971b2edeec5cfb37c6122f03b 100644
--- a/f22/meena_lec_notes/lec-14/lec_14_lists.ipynb
+++ b/f22/meena_lec_notes/lec-14/lec_14_lists.ipynb
@@ -32,20 +32,6 @@
     "- `for` loop"
    ]
   },
-  {
-   "attachments": {
-    "Strings-2.png": {
-     "image/png": 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nE8842sx1xRyUBlx6kze4VOzVvfmcZx+3GQ/cbgtcwC3T1HmdjazTciv9sk/uxsXauxsBd7OSa1KpucbZM62yb39r1z67n1Nl9BsnTzJzwa/2vfq45aTXVli282mf1QV3w5RJbrsHxAZRU41049c4c7pV9u5n7aqqUkcHfs5mnsAFFXGgbiAruvewChcwzjTl4pvpujKdPh/nbKbrzHT6UvbLdF+YPj2BOS89bT9ffJotdA9twtJUN6Kje9jR69ATrXrtDcImCx2eyfUseSG6Pk+5+kKb99aryYN972c9eo9rn6nC+p/9D+u6+Z8s3fUVOt9SqtfPBGCxv+91X3zyS0DJ5S0th3xAw9TJ3jUwEURM7E/qa66/uele6/O1X6nbn/hcCtfxhimTramu1joMWsz3oDSxnbm+5rKfxT6Xc93XqPnztS855aWyzB9rv/K1/VFGjGspkN1dUMtl8AmBshAYf9ReoUGUxA7Uu6dX44/c05Z48MUWQQcFryZfcbbNfuLBxKR5e1WVvslXnmfmuvCOTe4HdvYz/7Had1+3wSPu9UpuKZgx4PxrbewBO1vTjGmBi5h6y9VWvcEw7ynvwoYGm3TByaEWNfsfZV02yq3EVepG5GKvAMa4w/5qDS5jn0tSxmzSmcfa3P9zx9YFCmoOOtZ6uhJcmaa6T973AosKzOlJupdcIKjD4CWs5+77WjfX1ldcYEil3abfcZPN+/Adr8Tbwrku0KXkllO11LLWbcsdrOsfd3CBm5al0rKdT4uW47Rbr7W6T993T9pdYM4FGs2V0tP6VDKt10HHtDjnNU8iKVOsgOpMd/43TZvyy2AXBFMJOj2Z77HT31xwd8XE5N5rNvO0WEAaH5Sprx39gs13x6L+u69dJmK+tXOlETsuvbxVub+uf9g6tITagvFjbMLfD3M5j19W1OvAo62DCyZPH3mDzXPHWCURrEMHUzC6y6ZbWs9d9ozcolx8wxasgOX4I9x6fy2NJ+9BV90WOLkyUOOP+Js11f5yU17hgs5DbrrPmzYf52zqSlP9+hxzqis5uknqZDbHfd+mjfg10N/ObNCVt3nnTeqEhfBLXQefS1NgyogrbObdt6S1cfNdQGDee29kFVRKawUpE815+VmbdO6JodfLlMm972rTnFm+wdkOyOXaqXWW2vUz4ZDJ932Bu85OOPHgxKzea8+9Drbu2+zcYljig4ICE045whrd9SGROq+xrvU96RyvlPqEEw70Sph749wDqzF7/ikxmffaaaVVrd/pl3jvxx+9t1diXB+6DtvKeh18nNW+96ZN/sc51jDme28aXWtq3PWjq7tOJFKuv7mZXutV+j6T/UpsZ9xrptfxfF8XtH0LnPPEs4+zeW+/Zk2zf/luedf55Va2HrvuaV032yZuN2LHZ7qfyQvM5FxOni/1vfKUte63rf7H79w+f+eu5XNtYV1d6mTW9+RzrfPq63jD8+2dzb6kbkOuealMz/1koGy2P3l+3ucmQFApNz/mLieBkFI5qbugm+ZZ/7nPBQj2ax6lEkiFCCipZNJk93TWV3Kqec3Bbxqn/GwTTz3CBt90vxcg0c2mSlhNOOGA5hvQFnO6fZ90wXAbcvMDNu2266zetSUQlKpdMKnmgKOCRuU2LEv7JlelT5nDXANK2vh577xmc90NgpKeIE+75Srrvu2uXpVIb2DMP1Wzm37nTTb9tuv9pclc0FGZgMmXu8Cjqxo56OrbQ0sA1X36gXcsGsaN8a/RLUfHZqr7a5g22focdUrzNNnOpwUoE/zz+SdZo3vK1yK5wFK9q26iv9o3X7UBF1zrVeNMnkZPuZWx1jQtkgvSNUyaYLMfu9/7G3jtHV71FE2TzTwtlh3zQQFCfR+n3niZdyxTJ69z+6s03Z3rfU8+z6pd4Cs1NbrShsml3qbffqNXNdaSq5G687bu3Te8v0ZXcqn3Ye7mMiDl4huwuOZBFV1dacSFTbbgx19K5+m11p3H1a7kXWqa/dJTphvuRKre4Pde1dB8nLOJZSa/pvo1uN+koKRSeInt13jvhtv9XiWnQvklr4P3pSlQP/b7tANKxd6DeR+9a5POOcEF4BuKverf1pfltVMLKKXr5287lPn1qMOAwdZp5dVstnsAl0iTLz3DBacHWvVa6ycGea+6TisIWPf+L9cAb6ArUdvvtIut7pP37CcXnFrobtaTU/Lvk4armYREUlXMxEMflVib4x5i6OFU8jlR/+1XNum0o6zOlQbXNSLX39xMr/XZ7Fdi/6Jes7mO5/O6kNi2oNoHKtFY99E7v/y5PFXvI4dnXVo8m/1MbFs+rl0KaCk/OvMRV9Lx1wdIieUHvSYHS/Ppne2+pG5DLnmpTM/9ZJ9stz95GbzPTaAit9mZG4G2KTDz0bubd0zFbRWIyXdSYGPSOe4m1d0gB6VOq61j3V3pCL0GpfpvvnLVwX6rbqfqACp9E5ZUCmvC8MNthqu+F5QqXSmN/mde7mphueIErZiS7ec8/ajNd6VGApNrK6qiZ6/AUYmB1RsOMwXKKnv1tQZVMUtKyijqYp5u0hOQ6bdc4w8opSygzpU+mu5K9QSl+V9/4ZWECwwoBc3w67Bs59PsdS4YpLYjfAGllPUtcO1rKSi5sL6+xZgZrkqoL6DUYopfP7i2zxIpm3kS88a9qtTghJMOtsmXnRkYUEqeX0EvTTvlhkuTBwe+r//uf9YioJQylb43s/5zb8rQ3H19C0waoO9icnBbo2bcf3vSFL+9nfXwXb99cO967LavV0oh13O2xUIL8CHX87MAm8Qiiygw95XnQ9em3/fOajdxhVW8amWhExZoxFRXgio5eFCg1eRtscnXTi20lK6fiZ3M9vved/j51sm1qdWcVOL6tCO99q2ah7k3U13zB7Wuvcjk1P/Ui6yiazf76YSDfAGl5Oni3i9wQaVJ554Ufk64dj9zzSdkeq1XqZZc9ytsvwt5HQ9bZzbD9dBXJYyzTdnuZ7bncvJ26mHMmD239tqNTSeglDxvPt/nY18S25NtXirTcz+xPr3mc/uTl8v7zAQoqZSZF1O3AQEFaTqutIrN//wT7ylH0C41TBjvGqlu9KoxzXlhVGQ7D91cEezu2//Fa/Bx9rOPubZ/HgsNFCWvS8ttmuUa+gxIvY85zXq6m8JEUrWl6bf7L5oqrVGz96HNgSC9n++KQadmqhLLCWsTop1rxHrgxTd6Ga/EtIV4zdS+7pMPAjejo3tqOeCSEVZZ09tq33/Lplx5botSJ4mZeuy+f/OTzK7D/mhTrr2w+amjblYq+/RLTJrZq6s21tllcPWnIsqqIpEoCq8FzXnmMeu1z2EtlqnSNSoyn9pmVtctt7NOq67lPWVTw/Gzn2t5XmQ7n1aueadcdX6Lp18dXdH+XgccbZWDhliDa9h+6s1XNpdcUxBm5kN3uva3Dmze9rqPWwb1euy2n6uat70XpFLpplmjXJXQlKfp2czTvMKYN9PvGOHaNhndYqrKIUuYqjdUdOzoBQ9r33m9xc3DzHtvc6Wo1ndVQH/fYr7UD7qJ7X34SV5JoIWurbJpLojofZ9/nXDmo/dad1fVL5Hy4ZtYVthrV9eG2tR/XtVctXWeM693peKqFl+qeZa6Lz9xv2cfN3/uMHRpbx8aVIUvkbI4ZxOzFuq1GH6F2naWmx+BOlcaKCwtdvvjzR1T6Fye5a53M0MC9mHLyHa4fkPmuxIQUUm/pR0WW9I9nJjtOtf4xjJ9WBC17NRxmV47NX+pXT9z+b6rA5UBF15n4w7dvflaq4dCemgw+JYH3YOjPjbr6f/4zo+afQ+3rltubzp/eh14jMeqa1ZyKdXeSSWCNYGujUGp3j0UUqpw61IpZ+URledrctXsdO3Q8ptcYKk5ZfibK59M8whq9y/X/Wre3pQ3hbyOp6wq9mN7125l9x13t6ohQ12J4h+8IExycw/T3TVe1+Zs8nTZ7Gcu53LyzqodudQHfnrA22nl1a19166uSYQOtsCV5qx9/eXk2fL6Pl/7krxR2eSlMj33E+srxPYnls1rZgIElTLzYuoyF+jliibX7HWItxfqmWXcQbs231C32DWXWVAVM/U6M3f0iy1GJX9QQClR917Dq9fZ0DoMGOQCQDcmTxb4fpYLPAQlBUySA0qaRhmjmY/f/1t7Nr/O2DBhnFflRW0AKKlkQ78zLnP7tYsXMPh1stiXfmdcalXuRrSQKRv7eZ9/FLhJvQ45wQsoaaR6BOp3yoU23rW7lJrm/veZ5qBSRZeurq2sl2z2C096GY9s241S5mbAxTdYJz09/zXpnPp+O1cM/9dSPgt+8ldtm/3c4+4m5cPELF7bPwPOv8ZXNavXISe6YtB3WQfXm6BStvNp3rlqbyippJeCV4Ouu7O5zScFJvT0d+w+2zWfLyq638NV/Uy0C7XQNYqZnFTyq9PyvzNb3ry2t7xz0wWiOrjATiJlM09i3qhXBU9afLfc+V6z35He9yO510YFx36+7KwWDetOcl1HL37Xk809M6Wup73rVXHQNXe0qP6n70Xdx++ZvmdKquagIGKiJ8F8+KZuR+rnCvXe6DLLyUHlmQ/c4bUPkph2lusdMzn1/Ms+yR8t23O2xUIK8KEYfgXYbBaZR4H2EYH9CScd6H2/u2yyhfd7r0B9j+13c3f1hS9Nq9/gsKQbJlUVTrRrkpiuYdJPXlXj1CpZifHZvmZz7dS6Su36mev3XQ1iD7r8Zht3yG7W5EoOK8l84vDDTEaTLzvDG5b418U9SEqU3tYDqJ5/3d8bVe96Dm4OKrmGuhPDE/NFvVa6HogHXXeHy+cN9iar+duBXiBID61UGspri8+NyeY3N5trfb72K2ifC3UdD1pX1LDqTTb3StEnrruatvs2u7iqjAf+dhxdNX2VJu5zXMtzIGq5iXHZ7Geu57LWrSBoiwdkrg3Hvn+/wOuMJ7nGwLwP3i5oUCkf+5Kw1Gs2ealszv3EOvO9/Ynl8pq5ANXfMjdjjjIV0FOMREBJu6AGrjuvvm7o3qh3LCWVHglLapzRl9yFIZ2kxgeD0oKfxrmSCVe2+FP1u0RmJXUelapKTuoVbsAFrt0fdzOaTurpMurJDUymM0+m02Rr39wodPIKXSBBpVKSU+WvGbzkYXo/32Uek1P77j29Bpe1v5n21lbRsbN13WoHG/KvR1oElLR8ZXaqXcmn5uSK5uvpSXJStbjk1Ms1iB7U1k9FdbV3nnZ1N1JK2c7nzZtS0qvPCWc3B4u8hbt/6gUv+XuhhjAVlEmkqqWWS7z1XtWW16zHH2gepieDakeig8tsJ1I28yTmjXqd4wKCySW9euy6l3tKe7Sv/SoFgwdeOsKqll2heXF6mjz39ZebP6e+6bn7AS0CShqvjJ0a6U5Oqt6QSKklAbLxTSwr6rX7Lnt4jYYnppnlGutXI95Kja5xfrWnlEh6cq3STUq5nrOJZRbqtVh+hdp+lpu7QKdV1gxdiKp4TzrjGFc9ZBt3A/aoKxnSYO1reln7HjWh8+RrhFeFI2Rh/c+8zBdQ0qSV/QdZ9z/t4r2GzJrx4GyvnVpRKV0/tT35+L53GLy4DbzEldpOymfNdw8bJhy3X4sSs1XLr+wesF3aXIpb689H6n30Kc0BJS1P56MCjF232NZbfC6/ublc6/Oxb6nLKNR1PHU9cZ/18DY5oKTpdY3vc/xZLWat+/LTFp/T/ZDNfubjXK598+UWm9jbNQLffeud8n7OtlhJwId87EvyYrPKS2WZP9Z68739yfvC+8wEKjObnKkRKF+BHgG9N1Wl9FjVYu9caSW1L5PobaLFOPehwvXMlXhalTou7nOT6+ktrOqbgkcz7vxn3CKaxyeCX80D3JuO7mZaPURMvvCU5MG+9173zBHtMPlmyHJANvZaVQdX1FkZxhbJBWvmvvaSJYIuGjfzkd/awEqetn2Pnskfc3qvYE//sy73LUM39WoAvEWQ0DUM6tWPd725JVL9D780tqzPeqLZw/UUl07Kdj4tW42HJydV/wtKLbbdTbBg/I+uy95fgkRqm0fVTrze4tw4NXKq9oxU7F+Zuo7LuCJLKSmbeVIWEfgxuYqXqmyqxFpYUsmlvieda+NddYlE0hNq+zXgkhjW/OoCSEEptTi92kJLpHz4JpYV9aqqHd1cQHP2kw//Mpn7/VBgr2bPg131w4eaS8hppHofVO+GSrmes95CCvivWH4F3AUWnaNAN3cTNeux+1y17eBSqVp8w7gfvWvZ9JHXuyf5FzaXPs1x1aGz67rf4B7uBKV2XfQAYZOgUQUZlu21UxtTStdPbU++vu+dVlnL+ruGt732jbTglKSSEgNd9fjE72DK6Kw/arlxD+By+c3N5Vqf9U5FzFio63jEKjMapRKBVS7/oeCz0gL3O5FIqlam9lDDUmW//tbPlQpSymY/83Euz3ftnCaSSrapaYHWSPnYlxbbnUVeKpdzP+/b32Jn+JCJAEGlTLSYts0JVLiSK1GpqXZO6OiKzr/cuIVOEDFiYXIPUxHTpTMqueRE8vTd1BbL9Zc2FxNPHpd4ry7Z1RuTSvAUO8XZa3s6/W51f1DJDZ909vFW95d9vZIl6tVtjutxLSh1dPXSC5FUCmnuS0/bLHeTr+6tk0vPeOtTNbiUkkoLXIOaidRh6DJpl5TKdj6tqz6lNFyda38qndQw3lXf+7WHsarFhnqlfia6Hm+Se81RWyiqPtrr4GOtp6sC0K7it4Kv2cwTt10yT34SqW6clYGPSl4Dvwrw/VotUQ1BZpoqXMm/5LQwqSeofPgmLzvqfU+X4WwOKrkJZ7qGuXu678CsR+/5bTZ3DHq6LpaDUjbnbNBy8jmsmH753G6WlT8B/W4Muup2m3Ldxa5Hx99KQAat4f/ZOw/4KIr2jz8hhVASEmpooUhVqoKIghQbAlbsFRU7KvpX9LWDBbFhfxUbSrG99gKCCCgqSJGiICK991ACAVL+82zYvZm93bvbu73L5fY3fMJO35nvzu3OPvvMMyzo2TT0Rqr3/NtUqX0nqyyuxBUfPOB3/9YrTqIkTQtVXp6ip8XqGMqzk9sSb89PN3/vbCfp0JpVyrJgnb9mb1G8pLvtUnOdmQhwes+N5Fnvdl+5vmg8x91uJ5sJ0IVKbGOJ7WyxqYP8mT8GnPvyElY6IlQKp5+RjuXi/fsVG2wVW7Xx07h2m5VdfZH2xa5ec3yguVQkYz9W7Tf3B2F/AhAq+TNBDAgYBCqINfzEL8sW23wWbt0S9uRSE+JIL7vGCcPwJInlS1Zu51svBnyochneJn3L8HuorrBTUJaTZKv2c1z2NbdqNpBkg4xaXiEk2D3+TbtiWjxPGjL7DgiYJ5zE/cJI9I7/PmNMZLQ6WBXfZKzaXDdrp+lOFsDocXbHcMtp9Qlj07JjrYBQnFkdnL/M13/tA9r6xFDVBlnhYdopdkg6vH6t+Or3mFJ1OGWUCswB/g2K8+kulK/QbBeKbRIVHxEqyVvx6vUEPdp8ddPKucQ3aBtEhrSjWlAlYbPtgDAgzE777T5xr7JUkZfq8RIcswt3zJrrcT0cQ36utx0VukaAhcN8/6jSrbewhSZ2dRQfO2ydsJ3CS3AbfzNLEWTb5g8jgW33aPZxJK1EvRp+aWXhdHqLo/WouD3G3fPT5d97sc3HOTvt8kgvVHJW6Msuw7nnRvSsj7RzNuVdf47bnCf8aJOGsfRxy0mdjvsZ4VguKfLNZbiddvN4rQ9+cxBTn5101CpvhH2xqtIyzq8fvlwRjf1Ytd/XXPhsCECoZAMG0SDABPilNFksPWGj3X5OTGjyhY0X3r0rHJdSu66m1u9XVizbYYPSKRF8adv38w+U9/7rflVbRfBuUrvEcjvzbmVWeWMdx7Yz6j47mrY8cJvy8hy0HUKQUOeR54ydg4LmDzHDnu8+o21P/sfIzYIrNvKZefZFxNvSBmKe1qiJIZCRVX2Nymw84Zbj6lJq5hgGuEmMq5pDh2tCFptTBYzmZW4N3vpM05BhgaWstcQaBumt22oc5ErCKSOXl/38W0zNbWIY5jy0xrecUM4n+1n9XV6uZiVwkfM79bvJN5RzZ4ndDHWhEufPn+qzpcRhs4F/jotkzHJ5W2eavLMBc6cu1vyctg/5Y0uAN09ozJspTP6Sdo1/iwrXrbZsQPGe3cLW4XLLpbeWBcKI5HuNvNxWrmLXmy9QHbHJgp1gmzVU4uEjTbw9P938vbNdObudADc/eBs1eO1DTRAvX7dY+cO950byrI9m3xw9x114Ljjpi7x0n5/vFSpVLi0umR6wqk/e2ENPd9LPSMeyJrgW80f9g+lhm3ud1jaT1rtQo9SbXPrR2xfSNhKRgiF5I+1LSCcJkimSsR8P7Q/SPc8k+9YreKbL6CgIOCOQ1qS5bYFtLz1JvDMDO55I8tep3R+9Z5tfTqhywsly0OcXy2s2Db2Bivbk+eJMPv5aytvibhbLwIoP7FdSD4ntR7c+PlSJCxbYJYQE++fNCpatTNJ5l7UG735BVUPUsqnS+0xq9IHY9U1odbjp2DDy9hcfN6pMES8duWO/1Yxch7J8ME0sedMd29PaE2Sph5433HJcPrVhI70aoeVTSHs+k5ZK+VJC9rFghwUXuRO+p0qm8cvj0cqFU8aqHo6rKGkHsKYO7xgSyO0a+18l2bxbk5IYRsBtvsGaUElojKXa7NLIhml5dz/ZRTpm5brMfl5iILsiYQvOqYs1P6ftQ/7oE9gvPmpsefxe4ucWuyShwZsp7ILlvv9NwHv+4c0botq4yif2tK1//28zaOPgK2nfT1PosNgZko1675s6kbaOfIjWDOhF20Y634HK9mQRJsTL85O74dbvveCvBQEZl+Tn08a7BwmbOhYfA7khsuBDaL/aaTxxVqcukntuJM96rZ1R7Feoz3E3nguhMue59yFpSXtaU99cvdGESdToq19s/3LHqR9k9HOG2k83xrLcXu5HgWRjSW9PsKMbvN3oS7B2BkuPZOzHQ/uD9c8r6RAqeeVKo59hE+DdXOwcG9XeeNuVtPq8k2l1n0606f8G2RrgNteR0e8Cc5QRPrT8b1p72Znia+2bVLBkERX8s4R48p336Xja/PAQWnVWV9r21IOapoIsVOJ12pv/cyvxpMqRE0uLtjx6V0DDho7qczlz4ZbNlluqsqZQlR6na9sJ1x31LjX+bjblDH/BcgkQN4m1KfYLG0yFYbwA81drmSuPC975JVRXscUxSla2d1WweL4SJwf0iW645biuqqf0laukHaOftxUelojle3n/G6u9FB3esM4ot+meGyhvwlua0Xo9MoUNoT75Km+PpkcJ21d/it2ZSpfbhVPGqCiAx2xHZfuox6jAxsAvf8neI34vsnNbqOQGX7l9wfys/cC2laxctQuu8ouOdMz6VShFJAtj87LTbIvJEcLPL1h7hXafnYs1P7t2IL7sCBwSmwnsE7/VdZf3pc3iGcRaHgVLF4v7ySKxSUbpDodWrQuUZpXfaVyW+D3xEjg7xxtIbLl/MK298BRad9VZws7fEM0mFG9xL2tH2pWPZXw8PD+5v2783nln0k333aIsN68obC/yhyfZZkvRti206Z7rxTNf/eimcU8VdvZ0J55ZbB9QdiViPsR/4bhI7rmRPOu1trrcr3Ce4248F0LhXig+Km179lElK48D3fFvlze4sPuTf9vh9NONsVyxdTu9uZqJDd4ARZ7P+xLtfW7wdqMv9i0MLSWSsR8P7Q+tl4mfKyXxu4gegkBkBFhokVw7R7NhYlcTT2CcOt6hLeOsi2yNk7JaLNurceK2jviPsTzIXC5bbL3Ou91t4QmZhWMBGRvArvfSmJCNSFtUE5Uo3t3Narc8XnqWdem1IbWXhQ8bhwykEtbsSkmlOg885WjpIi+5kJ280whPBPwmpuILKE98UurkaO3LPO9SbZe6QvFlmx1rm224+VLKEMIpXs+fUreB1scC8bKyb7IwPC60gnLHfkPhluNzVDquK7GxamMHPWFbaNMdV2saAFXEOSuISVeh+OLPy/Hyp03S/FyuhA3VHnEHxY5p/GV+t9ByqnbJtVS5U1exJLSGEBZ8zup5ejaNKX/lYxdOGV9F9j7e2Yy3Fj/45wItE9vO2HDTxZQhlh9WFobFU8SOjKw5sE8sS93/63Sloipiy+f0Nh2VuEgDbvB12oaqfYQB/tGjDLV5Ll8huwZlHNnSWq4vkjEr12PlTxYCXd6xRr/38e5deR+PoWrCeDgJGwcHhWBg2zOP0KEVpTvzWNVRFvys2oG4OCAgXuJ5OTn/heIqtYueoW4+P7908ljmHefKu4uH5yczjPT3znZXNt13M/FcRXc8N8sRHzhYeJAz4jXaeOc1hsCJP87xBhN1n35dM2Wgl0kR90vZ7XxHXGPxLGOTBAULfqddYik726erecs9craQ/JHccyN51nPj3O5XOM9xN54LZtD7Jn1JbA+RdzPkedEh8ZF1lzDvIM8Jef7Ey8PDceH0M9KxzO3MvuJ62ivmM8U7t2vNPiQ0ldZdc47YufkxqiS0jpOErU7eiOdAgA1W3ODtRl/C4S6XiWTsx0P75b542Q+hkpevPvoeEgFWx88R9hM23HqFYig4pMJBMtW880FNfdd46Q+SP1Aya5OwYMDK8dKY7Ktu0oQb+888T3uQWeUrWDiHdrwxKqzJlFV9bsUdmC92WLNwO19/jna+8bwmHEmt15BYhTZNLA+qKl6wWcAgO962WhMocaQQ+OR9NMaRUClF7DIiu71iK/fDG9dp52QBBgtnZMc7o/F6f9ag4q1v2f5GraGP0Sae9EqONTmstDlS6tTVcoVbjguzQfCcZ97QBC+FkvYRawbwnxPH/dvxwmPkm86rpatYLBcJp4xaqxpioVXtB5+mdQPPIdINn4uXgb1ffqT9qbl9oZT6Dan2PcN9ES753OQbapPY8Hi1cy9Vdj3iME9AzS6SMcv2JYK5qr37iuW+7xrZdrw0Qrt/aMJGGyO6RmbhKQt+8vnhL58E0jt0plTxm462y7ryBjqwaC4VxOnS8FD7Hw/PT25rJL93Ni+w9THeKGKpr9tikxJtpzchUGLHmqh1HhipaV3rmQ7M/om2Pfco1RbPXt2lH9uFaMyrepAOCo3hTXddZ4Q1z6ECNRxiKJJ7Ls8Twpkj6E2LVr+cPscjfS7o/dGP+WKZKf8FcszNzsZZoHJympN+RjKW9XOyXaVadz5EW4TgU3eFYtMT/vDHNjBTatSmwm2bNS0mPd3qGClvN/pi1S4ncfEyz3XSZuT1J4Dlb/5MEAMCfgTSxdb0dR5/iSpkVvNLiySCXxDrvTaeMs+/PKxq0jVhRWVtSdMOIWCxdOJlkydaScmlMuSaQx4U2jOlAgur/Gz8ct/MqVZJZRZnVo1VGiImm7xbEE8M2WD0DrE19dpLTqed771GxWKnIMPJ9gaMyNA9FYWWV3r7zkqBAvEFaY/QouLJiNkdFto/5l0D2c5TrYeeFuMoy5w9YDjcclwpf72s+9zbpG2hG/AspYmpwoZYBWEgXXcVKlfVvbZH1pSpcYvPjlc4ZWwrNyWkNWhE9V8dJ7TuWplSrIOVhfHf+i+N1bYZts4RWWykfMM5e+b5lwkDJUeESELrjr/yWTk3xqxVvXpcjZvvpspde+jB0iP/5iSBUpJuOFXNZYTKgp9xcnjKHQE2xltn2KiYtJufz3Wf+i9l9L8gJueL1kni4fmp9y3c3/uut1+m/BmT9Wq0Y50HR/rtwscflKqL+5Ls9n71Me0aN9qIqtTxeKrUxcampZErPE+k99xInvVu9yvc57gbz4VQ6bO2Nc/NI7GhGW4/wx3Lct+q9upDte57nJIqV5GjNRuYvJTWPIdUM5WG3ODtRl+s2uYkLpKxHw/td9LXRM0LoVKiXtkE6leSeGliqb2VM3+ZqCC+XNk5qy07zeWVsqa6qortjhuO+Uq8wF2mrN3Xy7DBvOyBt2r2ffQ45Sj6oPVFiRRq9mLiWuuuh6n+W/+jzAGXB375F4IR3u49++qbKffjqVT/xfeIt2PeLjRI7B4+1QfdIco0N87K7az1nxFG2MqzQxggZxcP7NlOT8VWbayaaRvHGkm73nyRNgubF7qrNuAKgy2/6PJXaCeO7dnUGT7Kz0A1TwYyzrlEu36yMIaEhlu1ywaJXdGkdfPihJlnnEO54ydSRr8BtrafeJki1ym7cMtxHZog5vUPtWViZBrXnM59SG/fieqMeJUavv+1ouVV/5VxQmB0D6UIYY6fE+MxQxhQbyjGbmq9BkZyOGWMwiF40lu2ETvRfar91vj3wMsZZZdUpQpVFEvd6jz5CtUd+bqlENV8r6hQqZJcheGvkF7Z8LPHXI7jIuHL5Z06XuqRcdpZWjG2J8BhKxfJmDX/9q2EQ7yDTp0nXtbuiYqgWmiU8bLLus++STXFvU12VvfhWPOT2wN/2RKodt7lVPf5t7UPK4F2Z2ShePWb/o8ajv9OuT9x681jVe6R/IwPNZ9SXjwrat/3BNX/7weUIbR8Zbs9cj7281KsjLMu1JZkczjU81ndU7g8O6vfi9yn0lzS/6b7e7w8P6UWOr5flggh9S5Js4jryr52MPELuZXLvvx6yhTam7JjrWZeGs2O74s5I16h7EG3i90f/OeMvCFC1VP6leaV7v+BrpOW+Ujdkc4Twn3WO+mX3t5Ax3Cf45E+F/gjbo0hD5V+xLO4Pmxonecj/DGW51JVe54RqBtB08LtJ1fsxrOLNyZo+N5Xwj7oacYc1Wi0GKuKYXkjweeJlLdeU7h9Mf8uIplLhTv2uQ/htl/vP46RE0gSKqUlkVeDGkDAWwTYqPHhDWuFzZxNPEPRNDsqipdbq21KnZLhn2SRsKdUJHYuKTqy1rqCeOlnYVBK/VzLl1qn5ygv+Q8KVXc2PG6lCRRqH+q+MEazA8T5+brxzjG8ixgzDddp12ffXqHOnyxsIdU3to8uKSoU9ov+4jNRWpMWmsAv2DnYHtOhNSs0g6KaUUlhp8a8o4dVHeGWYwOkPK6KD+RrtieSa9amUHav4zYUCRtGhZs3ajsT8vJCXnLIy0MDuXDKBKrPKq1E7Gx3WBj8LczbRWniN6IIOKwKRDEuEr5OmsXG5g+t+EeMs2Z+L9lW9bg5Zq3q5zjewat4107NdpuxtbNdZpv4WPGzOT2iy5gAa5fys4937ioRGytU4PtMTr2Q71HRbj7f49lWXtHOHaU2XcRHIRY0pdbKcbRxQ7TbyfXH6/NT7ntZ/975empzuW1bhVZvdUrJqR/R3EDum1v33HCe9W73K5LneKTPBd7woUhcH37m8VwlTZgiCDbvkK+DE38k/XRrLBfu2KaZTqgglsel5jYmtlfIGwLpjjU1zcap9TQ+Rsqb63CrL1xXJC6csc/ni5f2R9L38lgWQqXyeNXQZhDwAIGiPXm07uqzDUPAcpfZdgAbMqxQNVMTcLDx6/2zZyqGG/X8NW691/hyrMfhCAIgAAIgAAKJSgDPz0S9suiX1wgc+ON3R0Ilr/FBf+OHgPWaovhpH1oCAiDgUQIH5v5mKVDKEgbHa9xwpx8V/iq4un9Xv/hCEQ8HAiAAAiAAAl4hgOenV640+gkCIAAC8UEANpXi4zqgFSAAAiYCxULl2crxNvJW7rCFsWzOV5ZLoazaiTgQAAEQAAEQiCYBPD+jSRd1gwAIgAAImAlAU8lMBGEQAIG4IJAudmixcns+n0AFi+ZRJd75rmqGZuPn4Iplwr7MMv/swqBj5c4n+ccjBgRAAARAAAQSlACenwl6YdEtEAABEIhTAhAqxemFQbNAwOsE0nKbUmWx497+mT/6oWABkqUQyZSz2oVXU1rDxqZYBEEABEAABEAgcQng+Zm41xY9AwEQAIF4JIDlb/F4VdAmEAABjUDOke3KSWxd7sQliZ3dsq8fQjVvu89JMeQFARAAARAAgYQggOdnQlxGdAIEQAAEygUB7P5WLi4TGgkC3ibAW8rm/zyV9v86Xdtqmne2KRbbxxfn76WkiulUoUpVShbbr6Y1b02V2h9HVXqeETdbUHv7yqH3IAACIAACZUkAz8+ypI9zg0BkBA6tXUlbH7+XqKREq6jm7fdTettjI6sUpUEgCgQgVIoCVOReYGwAAEAASURBVFQJAiAAAiAAAiAAAiAAAiAAAiAAAiAAAolOAMvfEv0Ko38gAAIgAAIgAAIgAAIgAAIgAAIgAAIgEAUCECpFASqqBAEQAAEQAAEQAAEQAAEQAAEQAAEQAIFEJ+DM+m2i00D/QAAEQMAlAjvff52o8DCVFBZSdWE0PCkpyaWaUQ0IgAAIgAAIgIDXCGBe4bUrjv6CQPkhAJtK5edaoaUgAALliMCKnscIoVKh1uKm0/+iJIc72JWjrqKpIAACIAACIAACUSaAeUWUAaN6EACBsAlg+VvY6FAQBEAABAIQSPYpgpYIjSU4EAABEAABEAABEAibAOYVYaNDQRAAgegSgFApunxROwiAgEcJVJA1k45oLHkUBboNAiAAAiAAAiAQIQHMKyIEiOIgAAJRIwChUtTQomIQAAFPE8AXRU9ffnQeBEAABEAABFwlgHmFqzhRGQiAgHsEIFRyjyVqAgEQAAEfAUlTqaSoyBcPHwiAAAiAAAiAAAg4JYB5hVNiyA8CIBAjAhAqxQg0TgMCIOAtAophbix/89bFR29BAARAAARAwGUCmFe4DBTVgQAIuEYAQiXXUKIiEAABEPARkCd/JRAq+cDABwIgAAIgAAIg4JgA5hWOkaEACIBAjAhAqBQj0DgNCICAxwikpBodLinC7m8GDHhAAARAAARAAAScE8C8wjkzlAABEIgJAQiVYoIZJwEBEPAagaTkZF+XoankYwEfCIAACIAACICAYwKYVzhGhgIgAAIxIgChUoxA4zQgAALeIqCoqcNQt7cuPnoLAiAAAiAAAi4TwLzCZaCoDgRAwDUCECq5hhIVgQAIgICPQFKytPwNmko+MPCBAAiAAAiAAAg4JoB5hWNkKAACIBAjAhAqxQg0TgMCIOAxAtLWv1QIm0oeu/roLgiAAAiAAAi4SwDzCnd5ojYQAAHXCECo5BpKVAQCIAACPgKKmjo0lXxg4AMBEAABEAABEHBMAPMKx8hQAARAIEYEIFSKEWicBgRAwGMEpC+KJRAqeezio7sgAAIgAAIg4DIBzCtcBorqQAAE3CIAoZJbJFEPCIAACEgEkpJTfKGiQp8fPhAAARAAARAAARBwSADzCofAkB0EQCBmBCBUihlqnAgEQMBLBGQ19WJoKnnp0qOvIAACIAACIOA6AcwrXEeKCkEABFwiAKGSSyBRDQiAAAjIBOTJH0FTSUYDPwiAAAiAAAiAgEMCmFc4BIbsIAACMSMAoVLMUONEIAACniIg2T4gaCp56tKjsyAAAiAAAiDgOgHMK1xHigpBAATcIQChkjscUQsIgAAIKASSklONcHHhYcMPDwiAAAiAAAiAAAg4JYB5hVNiyA8CIBArAhAqxYo0zgMCIOApAknJyb7+QlPJxwI+EAABEAABEAABxwQwr3CMDAVAAARiRABCpRiBxmlAAAQ8RiDFp6lERUUe6zy6CwIgAAIgAAIg4CoBzCtcxYnKQAAE3CMAoZJ7LFETCIAACBgEZIOaWP5mYIEHBEAABEAABEAgDAKYV4QBDUVAAARiQgBCpZhgxklAAAS8RkCe/MFQt9euPvoLAiAAAiAAAu4SwLzCXZ6oDQRAwD0CECq5xxI1gQAIgICPAHZp8bGADwRAAARAAARAIDICmFdExg+lQQAEokYAQqWooUXFIAACXiaQlJxidB/L3wwU8IAACIAACIAACIRBAPOKMKChCAiAQEwIQKgUE8w4CQiAgNcIKGrqxTDU7bXrj/6CAAiAAAiAgJsEMK9wkybqAgEQcJMAhEpu0kRdIAACIKATgJq6TgJHEAABEAABEACBSAlgXhEpQZQHARCIEgEIlaIEFtWCAAh4m0CStPVvSWGht2Gg9yAAAiAAAiAAAhERwLwiInwoDAIgEEUCECpFES6qBgEQ8C4B2fZBSeFh74JAz0EABEAABEAABCImgHlFxAhRAQiAQJQIQKgUJbCoFgRAwOMEoKbu8QGA7oMACIAACICAiwQwr3ARJqoCARBwkwCESm7SRF0gAAIgoBNITtZ9hOVvBgp4QAAEQAAEQAAEwiGAeUU41FAGBEAgBgQgVIoBZJwCBEDAewQqyDaVirD7m/dGAHoMAiAAAiAAAu4RwLzCPZaoCQRAwF0CECq5yxO1gQAIgEApAUVNHTaVMCxAAARAAARAAAQiIIB5RQTwUBQEQCCaBCBUiiZd1A0CIOBZAknS5K+kCLu/eXYgoOMgAAIgAAIg4AIBzCtcgIgqQAAEokIAQqWoYEWlIAACXieQlJxqIIBNJQMFPCAAAiAAAiAAAmEQwLwiDGgoAgIgEBMCECrFBDNOAgIg4DkCKT5D3VQITSXPXX90GARAAARAAATcJIB5hZs0URcIgICLBCBUchEmqgIBEAABg0ByiuHF8jcDBTwgAAIgAAIgAALhEMC8IhxqKAMCIBADAhAqxQAyTgECIOA9AhVkm0rQVPLeAECPQQAEQAAEQMBFAphXuAgTVYEACLhKAEIlV3GiMhAAARA4QiBFtqmE3d8wLkAABEAABEAABCIggHlFBPBQFARAIJoEIFSKJl3UDQIg4FkC8i4tVFjkWQ7oOAiAAAiAAAiAQOQEMK+InCFqAAEQiA4BCJWiwxW1ggAIeJxAUrLPUHdJETSVPD4c0H0QAAEQAAEQiIgA5hUR4UNhEACBKBKAUCmKcFE1CICAhwlIaurQVPLwOEDXQQAEQAAEQMANAphXuEERdYAACESBAIRKUYCKKkEABEBAVlOHphLGAwiAAAiAAAiAQCQEMK+IhB7KggAIRJOAb8/raJ4FdYMACICABwiUHDpEu7/6mKiokAq3bDJ6XLhtK21/7RkisQtcWuOjKPPsi4w0eEAABEAABEAABEDAigDmFVZUEAcCIBBvBCBUircrgvaAAAiUWwJJaWl0YN6vtP/nqUofivN20u4Jb2lxdUa8qqQhAAIgAAIgAAIgAAJWBDCvsKKCOBAAgXgjgOVv8XZF0B4QAIFyTaDG9UOIkpIs+5DapBlV6XaKZRoiQQAEQAAEQAAEQMBMAPMKMxGEQQAE4o0AhErxdkXQHhAAgXJNIK1pC6p6Wn/LPmRdcYOQN1kLnCwLIBIEQAAEQAAEQMDTBDCv8PTlR+dBoFwQgFCpXFwmNBIEQKA8Eah+3e1EyclKk1PqNqCMU62FTUpGBEAABEAABEAABEBAIoB5hQQDXhAAgbgjAKFS3F0SNAgEQKC8E0itn0sZ/S9QupF9+SBKMgmalAwIgAAIgAAIgAAIgIAFAcwrLKAgCgRAIG4IQKgUN5cCDQEBEEgkAtUH3kokDHezq1CjFmX0HZBI3UNfQAAEQAAEQAAEYkgA84oYwsapQAAEHBGAUMkRLmQGARAAgdAIpNSqQ9XOv1zLnH3xNcQ7uMCBAAiAAAiAAAiAQDgEMK8IhxrKgAAIxIIAhEqxoIxzgAAIeJJA9pU3UkpOfco891JP9h+dBgEQAAEQAAEQcI8A5hXusURNIAAC7hFIKhHOvepQEwiAAAiAgEzg8Kb1lCqMdMOBAAiAAAiAAAiAQKQEMK+IlCDKgwAIuE0AQiW3iaI+EAABEAABEAABEAABEAABEAABEAABEPAAASx/88BFRhdBAARAAARAAARAAARAAARAAARAAARAwG0CECq5TRT1gQAIgAAIgAAIgAAIgAAIgAAIgAAIgIAHCECo5IGLjC6CAAiAAAiAAAiAAAiAAAiAAAiAAAiAgNsEIFRymyjqAwEQAAEQAAEQAAEQAAEQAAEQAAEQAAEPEIBQyQMXGV0EARAAARAAARAAARAAARAAARAAARAAAbcJQKjkNlHUBwIgAAIgAAIgAAIgAAIgAAIgAAIgAAIeIAChkgcuMroIAiAAAiAAAiAAAiAAAiAAAiAAAiAAAm4TgFDJbaKoDwRAAARAAARAAARAAARAAARAAARAAAQ8QCDFA31EF0EgoQisXr2axowZQ9OnTyf2r1mzJqH6p3emUaNGmrdx48bEfwMHDqSePXvqySEfwStkVEZGMDNQhOQBr5AwKZnATMERNABeQRH5ZQAzPyQBI8ArIB7LRDCzxGIbCV62aGwTwMwWjWUCeFliiU1kCRwIgEC5IDBt2rSSHj16lIg7g2f/uP/MIRQHXqSNl1B5MVMwc8YMvJzxwhgrvXfjPubsGeaEF8YYxlg4cySMMWe/SWbshBmelc544T6G+1gs7mM8ztx05GZlqAsEQCA6BK6++mrPCpKsbqzMI5ADL3WCGIwXswQzZ8zAyxkvjDGVF9/XeAwFchhjKrNgvDDGVF4YY/48rOYTchzGmPvMcB9TmWKMqTzk35+dPxgzjDGVaTBegeYdkaQlcWFxEeFAAATilAAv+ZoxY4bSOnHD0JaCcRovDUtExyqs7HiZHy/3MzMQX8m0eHP/rXhd2uVM6t68I3UTf7k16mr1Jtp/a3ds0ro0c/kfNH7Wd/TLvwuULtrx4kxWzDDGiOyYgZez3yTGmDv3Mfwm7X+TdmMM9357Zlb3MfCy54UxRuR0foEx5s58DL9L+9+l1RjDs9KeF9/HouUgVIoWWdQLAi4QMN8s+SWXhSxedCxkevTRR+m9994zum/mYeZ1UrMO9O2QV4z8XvKwkGnEd+/QB7MnGt028+IEMzOrPEYFCe4JZ4yBV+DfJMaY+qPBGFN5BAuFwstqjOHeH/jeb77vg1dgXhhj6i81lPkFxpiPWSi8MMZ8vNgXCjPzGMN8LPh8TKXsbghCJXd5ojYQcI2A+WYp1qQTx3ndsdbSNddcY2DgLxIcZ+b1zR0vCc2kY418XvVMEFpLt4x70ui+zosjzMwwxkoxhTrGwCswL4yxUj5W/2OMWVGxj7PjxSXM9zHc+0s52t37wct6nNnxwhiz5sWxdswwxqyZ2fHi3GDmjJmZF+ZjpfwCPSutCbsXC6GSeyxREwi4RoC1kXr16mXUh5ulgULzmG+ao0aNojvvvNPIhJcKA4XmMU9keDyxwxjTMFj+F2yM4TepYjPzwhhT+ViFzMzM9zGMMZWamZfVGMO9X2Vmvvebxxh4BeaFMabysQphjFlRsY8z88IYs2elp5iZme9jeFbqpEqPVs9KFsJF2yWL5SSPRvskqB8EQMAZgYEDB9KaNWu0QqzOiZ+pyq9Dhw7EyyIWLlyoJcyePZsKCgo0P6vx/6ffdWoBj4faNmhOa8RyuD83/KuRYHYsuMQYsx8YgcYYfpP+3My8MMb8GZljzMzk+xjGmJkWkZmXeYzh3u/PzHzvl8cYeAXnhTHmz8gcgzFmJhI4bOaFMRaYF6eamcn3MTwr/flZPSv5vTLaDppK0SaM+kHAIQF+wDRp0sQotWrVqoQ1xm10MgyPmZNexaJhnySsMW69j+EceX16u0cutCyKMWaJhezGGHg548W5wcwZM/Byxotz495vzczu3g9eznhhjFnz4liMMXs2Vil2vDgvfpdWxOzHGJ6V1rzM89dYaHNVsG4KYkEABMqKAKst6o7t35h3N9PTvH5kLvyFQna8Q0ai7u4m9zMcP3PhL9NmhzFmJuILW40x8PLxMfuseHEeMDOT8oWtmIGXj4/ZZ8WL8+DebyblC1vd+8HLx8fss+LFecDMTMoXtmIGXj4+Zp8VL84DZmZSvrAVMzwrfXzMPvOzUn63NOd1KwyhklskUQ8IuERA3t0tFmtgXWp2mVRjVufs3rxjmbSjvJz08hP6+jUVY8wPiRJhHmPgpeDxC5h5cQYw88OkRJiZgZeCxy9g5sUZcO/3w6REmO/94KXg8QuYeXEGMPPDpESYmYGXgscvYObFGcDMD5MSYWaGZ6WCxy8gPytZcynaDkKlaBNG/SDgkID8w8cNMzA8M59uECoFBGbFx8wwYAUeTDTzMYc9iCRgl634WMUFrMRjiWY+5rDHcATtrhUfq3tb0Io8lMHMxxz2EIqQumrFxyoupMo8ksnMxxz2CIaQu2nFxyou5Ao9kNHMx+pZ4AEMIXdR5iO/W4ZcgcOMECo5BIbsIBBtArrxZD4Pqy/ChU6A1WPhnBHAGAMvZwSc58YYc8YMvJzx4ty49ztjBl7OeGGMgZdzAs5L4HfpjBmelc54RTs3hErRJoz6QQAEokYADxRnaDFhccaLc2OMOWMGXs54YYyBl3MCzkvg3u+MGXg548W5wcwZM/ByxgtjzDkveT4mKyw4rym0EhAqhcYJuUAABEAABEAABEAABEAABEAABEAABEAABCQCECpJMOAFARAAARAAARAAARAAARAAARAAARAAARAIjQCESqFxQi4QAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAGJAIRKEgx4QQAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQiMAoVJonJALBEAABEAABEAABEAABEAABEAABEAABEBAIgChkgQDXhAAARAAARAAARAAARAAARAAARAAARAAgdAIQKgUGifkAgEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQkAhAqCTBgBcEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQCA0AhAqhcYJuUAABEAABEAABEAABEAABEAABEAABEAABCQCECpJMOAFARAAARAAARAAARAAARAAARAAARAAARAIjQCESqFxQi4QAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAGJAIRKEgx4QQAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQiOQElo25AIBECgPBJYuXUrz58/XmpqdnU19+/bV/LNnz6Z///1X8zdu3JhOOumkmHXn8OHD9PXXX9OBAwcoKSmJTj75ZGrQoAHt2bOHJk2aRJyenJxMffr0oaysrJi1i090uKiQJi2aSQcOHxJtIzqpWQeql12b9h7Ipx+WzBLpRZRcoQKdenQXqlY5I2ZtW7Z5NS1c+492vqwqVen0Y07U/HNX/UUrt23Q/I1q5FCXo9rFrE36iTDGdBKhHeN1/MfjddSJxmPb4vU6MrN4bVs8Xkd9jMXjPTZen0faGMOzUh86IR8xxkJGpWWM1/Efj9dRJxuPbYvX66gzwzF6BCBUih5b1AwCMSdw22230dSpU43zrlu3ThPgnHPOObRlyxYtvnr16rRjxw4jT7Q9LNAaMGCAcZrrrruO3nrrLZowYQLdfPPNRvxLL71E3P5YunlCSHPl2w8ap7yyaz96+fL/0Cdzp9BdHz1rxI+8YAjd2PMCIxxtz9BPRtGMZfOM0yx57DNN2HXp6Pto295dWnx2pQxa9cxEI0+sPBhjzkjH6/iPx+uok43HtsXrdWRm8dq2eLyO+hiLx3tsvD6PmFm8ti0eryPGmE7A2RFjzBkvzh2P4z9er6NzuijhlACESk6JIT8IxDGBlBT1J62H9SM3PTU11bIHrDX0xhtv0IoVK6ikpETLU6VKFU3LqFatWpZlQomUz8359bB+1Ouwa5eeHo0ja0jJLqVCaVg/6mmpySpXPT5aR/P59bB+5POa+UWrLeZ6zefVw/qR84dyLZ977jltbJkFnKzNdsMNN9DgwYPNp7YNy+fmTHpYP+oFQ2mXnteto7kNelg/6ucJ1ra//vqLnn76aVqwYAEVFxfrxbQjayV+8cUXxALjUJ35/HpYP3I9wdoU6rmc5pPbwGX1sH7kuFi3TT63XZvKol1yW9jPTm+rfiyNjU9msb6OOgv5Xqoxs7j3m/npZaN1jNfnEfc3XtsWj9dRHx/x2LZ4vY5ujrG/N66kF6aMp8Ub/qXiI3NZ/ZpkVapKE258irKrZOpRQY/xeB31RkerbSu2rqNRk8fRgrXLqKhEnW9UTk2j5y+5h9rnttSboRzjeYwpDUXAdQKxfVNyvfmoEARAQCZQu3ZtI8gv5zVr1tTCHL9hQ+myKTsBEb/Es0DJ7BYvXky9e/c2R4ccltvEhfSwftQrsmuXnh6NY62MbKXaWhmlL+W1MtRleDWrVlPyRTtQs6qvXWJVHlU/cn5u76bd27XTy3mi3R65fvm6OR1jej28FPPuu+/Wg37H77//3pFQSW4TV6aH9aN+grIYY+Y26GH9GGrbRowYQePHj9ez+x1XrVrlSKgknz/c6+jXCJci4rFtcpu4m3pYP+pdL89jTO+DW0eZTbyNMfn+GS/32Hh9HvF4iNe2xeN11H8/8di2eL2Obo6x5yaP1bTN9etgPq7ZvtGRUCker6Pep2i17ZWpH9C4Wd/qp/E7/rZyka1QKZ7HmF9HgkTwB/adO3dSjRo1guREMhOAoW6MAxBIIALyCw1rL+hfWuV42S93vbCwUA4afl1ryYhw6DGfTw/rR706c1iPj+axZhVVeFSjamlYP+rnrnkkXg9H+1hTEmpliWVuKUc0peR2xFrQpfdZvk5Ox5heh91Y09OdHuU2cVk9rB/1+sxhPT6aR/M59bB+1M9tDuvx+jGazMK9jnrb3D7KLOKlbXKbuL96WD/qDMxhPT6aR/M59bB+1M9tDuvx0TrK54uX66j3NR7vsfH6PGJm8dq2eLyOGGM6AWdHt8ZYUXGRsxMHye3FMVYYhGGg9wK3rmOQy+Io+YcffqDu3btTt27daOLEiXTo0CHNjiuH77jjDsu69u/fT23atNE+IH3++eeWeaIVedlll2ltvfDCC7VTjBs3TguzTdo//vgjWqeNuF4IlSJGiApAIH4IyF+G7fy69pK51ffff7/x9d2cFkk4IyOD0tPTjSr0dulHPcGuXXp6NI5VK1WhiilpRtW1jgiPzF9azEImo0CUPLUkTaWamb4lTfJXqVi3Se+qfN3s/MGuZatWreiiiy6iCsIIuhsunseYW2276aabqG7dum7g0uqwu3ZyfLDr6FpjTBXJbbDzx7ptbl1HU1ddCcZr2+yunRwf6+uoA4/He2y8Po+YWby2LR6vI8aYTsDZ0a0xdm23c6lOpnuaJV4cY1d27U91q5WudHB2FePzXvH333/TzJkz6ZdffiE2JXDw4EFijXgOz5gxw7KLW7dupSVLlmjmBlizvkhs3BMrN3nyZK1tLABjx4IkbuvPP/9Ma9asiVUzHJ/HnRm949OiAAiAQDQIyF+GQ/HLbWA7Nps3b/aznSDnCddv1RY5jus1h8M9l9Ny8lco3S8Lb7i+WAtwFI2kKr6ld3r7uE1yHg7HysnXKRS/Xbs++ugjYu0b3rnqzjvvtMsWcrxVW+Q4rsgcDrnyCDPK59X9+lGv2hzW4/Vjz549aePGjRqzvLw8PTrso3y+UPxhnyiMgqG0R84TxinCKiKfU/frR71Cc1iPj/ZRPq/u14/6uc1hPT5aR/l8ofij1Q6reuX7Z804uscq9/gjGqtl/TzS+cVj2+L1OjKzeG1bPF5HN8dYtxbH0rInv6QdL82gtU9P0qsO+xiv15E7FK22Hd+0LS194guN4fYXp9OFx53qiF+8jTHz84c/xFSsWFHrk92HjcaNG1Pnzp21PCtXrqRPPvnEEYNIMuvtNR+5Trv2RnI+t8rCppJbJFGP6wTYRsjYsWMjqpfVGqtV872UR1RZOSick5NjtNLOX6dOHSOP2cN2L/jPzq1fv14TAjRq1MiRlgm3hXeiY6e3KzMzkypVqkQHDhzQlumV1ZrlOsKO0oZdW7W26V+3MoQGU7rQYCooPERsCLG69NKhZQzhv/yC/bRt3y6qn12HnBr6rl3Np51Up5rvi5vePj69bv8phKa4mkW/flypnT/QGJMbw2ONl2iaDTvKeUL1x/MYc7NtzEpf1hoqG6t8dtdOjg/1OlrVH0mc3AY7fzhtY5V3FpzzvYY3IXDquC3xeh+Lx7bZXTs5Ppzr6PS6WeWP13tstJ5HVgycxkWrbdvFjqa8ZKm20C4JNP+wam+8Xkdua6zbxsaVK6elU92swBurROs6Wl0fp3Futi1ZzN3Mhqydtofzx/o6OmljtNvGDNklJTnTQXHzOjrhYZdX1o7V/Xzk57kuuLEqO3ToUNKXoI0cOZIuueQSq2yux3HbWLtKbqt+kkDt1fOU1RFCpbIij/MGJcAGoh955JGg+QJl4JuBl4RKJ554Il188cWUn59P1157rYGmf//+muokLzc6//zzjfhQPLyueODAgZqqKL+QsWNhEGtOvPrqq9SkSZOg1dxyyy306aefahJ2Xvqku3vuuYfmzZtHxx57rCMhlV7ejeOg7ufTlwunUw0hOGpep5FR5e2nXkYL1i2jDg1bhtS2Q4WH6c0Zn9KUJb/RP1vW0qa8bcR76PGkpkmtBtSufjO6+4yrqHX9o4xz2Hm6NGlL5x/bm/IPFdAVXfsZ2fq0OZFmCQOJFcQD/uz2JxvxsfREY4y50f54HmPx2LZ4vY48FtxsG39dfP/992nZsmXEXxtZhZ1fXBs0aEAtW7akvn37akbhQ9mFLB6vo/7bice2uXkd9X66dQznHvvl/B9pwu+TaOOubUozMitVpiGnXUGnHdNViefAkg0r6GVh9HaJ2JFK3okqTQiH+7TtRvecOVAp49bzSKnUpYBbbdu6ewc9O/l9mr96Kf0rBCF5B/ZqLayUWpGa1c6l1nWbCJ6X09Hl/FkZzhiTL9UisfPWq9M+pqWbVoodeUtT+JvfAKE1cofgw+7TuT/QNwtn0C8rFtLWPTu1uNZ1m9KlXfoQz2GsnFvX0aruSOPisW2RXsdImQQq72bbflw6m+aJ3+SfYte8dTs3U6MadenoekfRldIcNFBb5LR4u46yIEb38zGYUInfl5o3b07Lly/Xdt7lJXNnnHGG3NWo+OU28gn0sNkflZNHUGmSMLZ15FYVQS0oCgKCwDfffKMJGXjyvm3bNm3Szj/Gs88+my699FLHX4a/+uorOueccyJiy+thW7duHVEdsS4sf6kri58nv1yFahSYv/bPmTOnTBnLvPJemRnry6Wdb8pfv9F/Pn1JmyAHagALmK4/+Xx6qP8NVDm9UqCsUUvLGtxNqbssxpjSABFg4eKzzz5rRLMQ9OuvvzbCZe2Rx1g88GKhcdWqVRUsc+fOpeOOO06JK6uAzIvbUBbM/vzzT7r99ttp2rRpQTGwcOmFF17QDHcGzRylDDKzsuAVpW5FrVqZF58k2vd+1qRpft9ZtHP/Hss+tW/Qgmbc945f2s3vP04fCEGUlWOd4D+Hf0r1q9trD1uVCzdOvvdHm5dVGw8XFdIb0z+hkd+9S3sP7rfKYsQliw8n13Y/lx7oN4iyHGz/blTggkfmxdXFmtmVb95PXy/8ya8nJ4ilSR/d9DTd8P5j9P2fv/ql6xGf3foc9W7dRQ/G5CgzizUvqw7uLzhA9e4+TUmafs9b1KGR7+OmkhjjgMyLT10WzDaLD6C3TRgpPojOsuw9a+2zY8193Y0YcDvd3OsiPRjTo8ws1Gcl7+DGy8Y4P5sRYPuU/G7K80zeWfe+++6z7cObb75JbB6EHX9MD2VOwR/g+QMWL7Hj87KW9Pz584l3Pm7WrBl17NjRWH5ndWJeZfPSSy9p533jjTe0sjy/4w/6PP8zP/+s6tDj5Lyh8tLLOj1CU8kpMeS3JHD99dfTW2+9paSx6h7/8Y+WjZyxRspRRwXX0tAryc3NjVioVL26bxmRXi+O7hHgmxvbw5k0yXrS7N6Z4rcm/np99TsPh9RA3lHjv2JSvWn3dhpz3WMhlUEmEAABZwTYEGeXLl2ItSxDcfwh5Mwzz9S0KZ1qcoZSP/IkBoFAOyKxVqmVyz94wCpai+MvuvsPW5ezLVSOE+768Bka+5v9NuVy14pKiunNnz6jOav+osn/9zqlpaTKyZ7wFxUXW/Zz+7486v/i7bR4w3LLdD1y8fp/Yy5U0s+NY/kg8LfQoOwz6lZDW9Cq1bIwySq9PMTxuyAbui4Wvyl9w5OXX35Z01LmuUIgd9VVV2mrZjZt2kTTp0+n2bNna/MLqzIsPOLVGGy+RXcsHHr44YdJtoV5zDHH0BdffKEJmPR88vGBBx6gfv36Ubt27bToDh060NSpUykrK8uRQEmuMxZ+CJViQTnBz8HLmswCJXOXd+/eTXv3lqo4m9Pswvwj4h8dXNkTYBsu/LLFN1XefUB2rA66Y8cOzU6JHO8F/7odm+j2CU8rXa2SVolObnks9W51PPF69Gl//04zls2jPQX5Rr4v/phGb4kJ8yChtQQHAiDgHgF+zgwYMMBPoMRLf3k73oYNG2r3K54cmoVOgwYNok6dOhF/0IADAZkA38uHiqVqL06ZoNnKk9N4l6T/O/1KLYo1mnhJV21hqy9baNjc2PMCbTn035t9LxmckZ8TF3Q6VVlyLdeZaP7PxDItK4FSPWH/p0uTNtqL0l/iBXfZ5tVK13kJ+vCv3qDHzx+sxHshMOjk8+iPtX9rH6Hk/vL4kh1rQPP4PChpknD6qTHWUpLbBH/8E2ABy+DxIwIKlOK/F6G3sGtXdXky24blv2COtY1Yc0jXZnrqqafo888/tyzGO7PJAiXOxBrTZscfvu666y7iFTlWjm0pnX766UYSz1969+5thOPVA6FSvF6ZctSuH374QWntsGHDtEk9G3WeMmUKserevn37lDwIlB8CLFDi68hqn+zee+89zcaSFjjyH6t0lpWhbbkdsfbf88ko2l3gG9s8ufvxntHUUtiE0B2r8LPR7rNfup3miQmi7p785i0IlXQYOIKASwTYzhtrHsmO7Sd9+OGHdNJJJxnRbF+Jl2X//vvvRtyuXbtoyJAh9Nlnnxlx8ICATmDwKZcKIdGF1OD/Tlde4L+/67+UK+yP7MrfQ8c/drkmdOJnwWQRf1LzjjTrwbHU7N7+tD3ft2vjj0PfpJY5jfWqE/pYcOgg3fGB+vGFOzyo+3n0+HmDKT2tdBcmXprB2kn3/e8Fxf7Uqz9+SJccfwa1adA8oTmZO8dL13gHruVb1lBnMa7MjpcI3tf3WrpOcExLTqFvFv1M3y76iVij7tLj+9AxDZqZiyAMAgaBt37+nOauWWqE2VO1YmV6/uK76ZwOPeiQWK767i9fakLdQFqaSgUJGrj55pu1ZXKsIPHll19qq3Bk+7B6t9nky/3330+vvfaaopnES+DOOussmjhxorZZCOfnVTxcXyLZ/a2gg8ARBMIlwPaTZMdL4Vi1j42ZsZ0Ulto+9NBDVFa7vMhtg985Af56rwuUuDQbAjc7fUckc3yih2etWKx08eLOZ1BmpaqakW421K3/sZbS3X2uVvKybY7V2zcocQiAAAhERsD8kYNrGzNmjCJQ4rimTZtqy914F0rZmTUx5TT4QYB38mxTr6kCQtdCGi02auAdP9nxS9jTk8ZofhY2yQIl3qGruTBI7RXHhn/NNpROataenrnoLkOgxCzY9scNPQbQTUJwJ7sSEfhtxSI5yvN+HkPjb3hSM/RevWo1qip2rL1EGOcee/2T9MGNI+nsjr08zwgAAhP4Tgggze6tgQ/TRcefThWFoJd3QWZj74+cfaM5m+fCPE+46aabtH6z8Pvpp/2F5DqUJ554gmStKC67evVqeuedd+i3337Ts2nHRHt3gqaScnkRCIdAmzZttMm5XpaFSazNwobI2LGEdvjw4XpyyEc2Fr1ly5aQ81tlrF+/vlU04hwQ4CUjsktPTye+Se7Zs8eIZoN0XnNrtm/0UxseP/s74r9Q3QKxu0vjmhijofJCPhAIRIDtGbDdBNm1b9+eTjnlFDnK8LMGE+8Q+vbbbxtx27dv13aE4WVycCBgRaBjo9aK1uk/m9fQ6cecKIwmq2Nv2t9z6cDBAk3TRK6nndC44eUMXnEL1/3j19VbhJFf2YCsnGFw70voNbHrmeys6pDTveb/9JZnqWuzDl7rNvrrIgFebiq7NvWaaTtSynHsv0n8Vp+d9L6ilW/O44UwazHzhh4HDx6kcePGae+1PIcI5lhDiTc1Yte4cWPKyMgwzMGYlTKC1RXv6d55qsX7lSjH7WO1QP6R6G7x4sWaETPe0cmpHSW9Dj6ymiD/YCP5Y0PhcJER4LW9Zle5cmVzlOfCy7asjrjPFT1ofDRiaKgABGwIsCp5QYFq+Jh3WgnkrNKXLlWXBAQqjzTvEejQsKXS6b83raYde/OI7f/Ijm3czPhnrhAqrZWjqb2pvJKYgAGrZ2XTmvYvY/Wya4vlXKkKCbOtJSXRg4GWOb4l9h7sProcIYGd+3bTtr2lWpV6Va3rNta9ypG1M5vVtv+9KpkTOJCTk0NXX1264uDw4cM0atSokHrLihey0wVMclyi+KGplChXsgz7wcvaJk+erG3PqEtd+QfHS9/+97//aVpLZm2XUJrrxtaHbtQRSluRx3sEGmbV8et02/rNqW5WTb94cwRv0cr2NE5vc6I5CWEQAIEwCbBWrPwVkKth236BnFU6hOaBiCGtY666HTkLPH4UGzIUi2UR7Hhp0v4ju8HxNt0ZFUu/UuvkzOX1+EQ9Nsz2f1Zu2L2NWtc/yrLLLKA7VHRYSatcMV0JIwACIBA+AbbBlSSKl96xSuvZc9B+t9Q9AXaxDL8V5a8k72TOG1OxkfPRo0fTgw8+SNnZ2eWvI1FqMYRKUQLrtWpPOOEEba0oS3Hl5Qe8jrRXr17aWlJdwhsqGzfUw92oI9T2Ip+3CLQQX3VYOCRvt9q//cl0b99rgoLIEzY2ssTOQHAgAALuEeDlNLxrqGwXaf78+cSaR61bt/Y7EWvSstFN2fHyXt4BDg4E7Ai0FPf+iuLer++2xUKlH5bMNrI/fcEQGjzhKS08+a9Z1La+qi3XoWELI68XPO0t+vvx75Pp1KNPsOz+R3Mn+8V3bdreLw4RIAAC4RFgG1y8ucAasYOx7uau+ov2HsjXbCnpcXxcuW09rRJ/cERsiJt3wmaFCd6A6pVXXtFsBoNNKQEsf8NIcI3AUUcdpU3m2T4FfzHWHUt0b7jhBpo1a5YeFdKxb9++xPYtIvlr2VJVUw/pxMgEAiEQ4C1825heFp77/n36ZfkflqV5q+mv/5hOpz5zAzW+ty9d8OpdlvkQCQIgED6B4447TinMWrP8QWPr1q1KPC+Tu/HGG/00mU488URiwRIcCNgRSBFf+WVBEW/E8NGc77XsmelV6NITzqQmR2zlrdu5mb5bPNOoqlJqRWqe08gIe8HTrkELqiAEvrL7WAiOxv/2rRyl+WcLg9yPfz3aL75Hy2P94hABAiAQPoFj6qmagjvyd9ODn7+iaeHotbJNuP/76Flt4wE9zuvHe++910Dw8ssv04EDB4wwe3i+MW3aNCPu+eef15bK7dixg/r06WPs/sYZeA7y3Xeh22E1Ko1TDzSV4vTClNdm8Zfia6+9ls4991waPHgwffDBB1pX2IDqiy++SKzRFKpjLSMvblMfKh+3802fPp345scG0mXHxuluueUWYttZc+bMoZEjRyo3Rc7Lu/utWbOGhg4dKhdNeP/wc2+ms166g4pKirW+ssr+2SJ8/rG96dRjulLtjGyxbj2PFq3/hz6ZO4W27NlhMPlh6e+0XaxprynyeMnx7he87fs///xD+vJU3iFSdvxA7ty5sxHFa9D5fnLBBRcYcV7xMKNHH32UfvrpJ+3LGPfb/BvluEsvvdTYmpbvnSxQ5wlPIm1Xy/0M5vgeNH78eNKXYnN+vm+xXQP+uMFceMeVsWPHatsCy/Xx84ttAcKBQDACHRu1EttxL/HL1r3FscQfHM4QS5tfn/6JXzp/iOB0LznWyr3r9CvpWfHRRXa3jh9BXy2cQae07qJp/f6+6k/6YPZE43mq5z2haVs6Xvx5zT078T36+d/5tDFvu1/Xz3rpdmF3qvQVju9bOdVq0jAxH2lex1sCSxkMPytHfPs2/bpiAeUXlL7oF4qP2mZ33ZhHiYW/7FjY2Uwwe+bCOymzclVz1oQO39zrQpooBN4lUi/f+/Vr4o0HzurYkw4dPkQf/v496btbStnolR8/1Oav9/cf5Ln7GWsy8+YfU6dO1eYZrEjB81N2K1eupPffV+9zPBd57rnnNPvA339f+vFBZ7l8+XJtoxBWokgElyR+hPJ4SoQ+oQ8xJsAChdNPP526d++unJmHVm5urvElmA1uJ9r2iUqHXQrwBEF3sfx58o1y3rx5+qmVI7+kbty4URMYBpKq8zKTVq1aKWWjHZB55b0yM9qn86ufJzEjJ77rFx8sgm0qzX5wXLBsrqdnDe6m1BnLMcYn7t27t/IVR2lMgECjRo20bVkDZIlakjzGYs2LhUk9evQIq2/vvvsuDRw4MKyykRSSeXE9sWb27bffUv/+/R134YEHHqDHH3/ccTk3CsjMYs3LjfbHug6ZF5871vf+Cb99R7eMf9Kv2/xyen2PATTj7zl0zit3+qVff/L59MxFZaOlKt/7Y82rsKiQzhx1K81Z/Zcfk0ARNatk0cz/vEs5WbUCZYtKmsyLTxBLZqyxdcaoWxz1qyzHlt5QmVksefH5fxVa4n1fvE1viqPja5ffT5d1jf2LvcyLGxxrZnd9+Ay9M1NdAu4E3Ne3v0jdW6jawU7Kh5NXZlZWz8opU6Zo773cft5hdsGCBVpXeGUOz3F5CT772VWqVIluvfVW4g/0p556qvIxq3r16poW01VXXaXljcZ/8rMy2ryw/C0aV9BjdbKQgQ1xn3feeZpdJf0rOn8dlpccwL5RfA8MXh9s5/jmmJeXR/n5+XZZtPidO3cGTE/ExKFnDqS7TrvCb7eaQH1tWD2HXr7Mp0IbKG+ipekPWqf94rEX7Qei0zbFIn+4vLhtXvw9cr/79etHLFCTl2FzvJ2rWLEisUBp2LBhdlkQDwIKgY651kvre7XqrOU7sXlHqpbur/lg3jlOqTSBA7xkcOygx6mPg80p2otlc5/e+lyZCJTK+lKE86zbV2BvaLms+xOL8+uG8sM51679e8IpVu7LDD/nFurfTlUIsOpUlbRKVtGUl7/XMj7RI0877TTq2bOn1k15Nzd+z+VVH0VFRdp8lX/H+/fvp2eeeYbq16+v2XfkOP2Pl8RFU6AU6+sAoVKsiSfw+b744gtiexRZWVmahlKXLl2Il73pLpwvx3pZHKNP4I477qDMTH/j0SxJv/7667VlI7fddpvlixqXu+iii6hr167Rb2icnYGXMjx8zk1C62gs9RMPZzbebed4kvzwWTfSL/eN8aQ6P3OxG0N2zDieNR75pV/+4hIofyKlsQYob3aQnBz6kpm0tDRtwnPxxRcnEgpHfWENLV5iyWrpdksA+QsifwxZsmSJpqHkhLGjxiBzwhHgnctObX280q/Lu/QVS2lytTjehvtRsRxJdvWza9PZHXrKUZ7ys7bRhzc9Tf+75Vlhk6o5JSdZv4LwR5cXLrmHpg19i9rbCO8SHRwv9+vVqhOlhLBUknXbeW4x8KSzEx1LwP51bdaeugthrt24sirMv9NuzTvQ+cedYpWc8HFssHvcDSPojaseojqZNfz6yztZ3nHqZTT17jdIFiyxbbjThKH904SZB686Ntb92Wef0aRJk7yKwK/fWP7mhwQRTgmcdNJJ9OuvvwYs1qRJE81Qd+3atQPmQyIpL87hfK3yGkNZ0BBr1WEr1qxZsn7XFlq+ZQ1t2b2TsqtkUK2M6tRAvFCUhQq/uY2y6jCnYYyZCfmH5TEGXv58zDEyL06LB2abN2+mZcuWaUsoc3JyNCE5L6k0t9Xcl1iF5XbEA69Y9Tvc88i8uI6yuPcXHDpI05fNobz9+zTD3a3rNSWzRvaitcto8YZ/iQVKnRodTfwSV1ZOvveXBS9zv9lmy4qt62j51rV0SNhybFa7obAJlEtV0iubs5ZJWObFDYgHZmUCwsFJZWbgFRyczItzlzWzLbu3Cxugy2mX0EBqKwTnvMtxvNmAk5nhWRl8jMnPymjzSgneHOQAgcAE2H4FGz0dPXo0/fnnn0pm/mLOWi4PP/wwQaCkoEEgQQnwSwVv1cp/cCAAAvFBgAVJ/Beufar46AVaEU8E0tMqUp+2qo06c/vaCU0b/oPzJ5CWmkas8cV/cCAAAmVPoI4w+H6a+IMDgXAIQKgUDjWUUQjwcjde0sJ/e/fu1b4Eb9++XVs/yhpKqampSn4EQAAEQAAEQAAEQAAEQAAEQAAEQAAEyj8BCJXK/zWMqx5kZGRQ27be2/o1ri4CGgMCIAACIAACIAACIAACIAACIAACMSBgbSUvBifGKUAABEAABEAABEAABEAABEAABEAABEAABMovAQiVyu+1Q8tBAARAAARAAARAAARAAARAAARAAARAoMwIQKhUZuhxYhAAARAAARAAARAAARAAARAAARAAARAovwQgVCq/1w4tBwEQAAEQAAEQAAEQAAEQAAEQAAEQAIEyIwChUpmhx4lBAARAAARAAARAAARAAARAAARAAARAoPwSgFCp/F47tBwEQAAEQAAEQAAEQAAEQAAEQAAEQAAEyowAhEplhh4nBgEQAAEQAAEQAAEQAAEQAAEQAAEQAIHySwBCpfJ77dByEAABEAABEAABEAABEAABEAABEAABECgzAhAqlRl6nBgEQAAEQAAEQAAEQAAEQAAEQAAEQAAEyi8BCJXK77VDy0EABEAABEAABEAABEAABEAABEAABECgzAhAqFRm6HFiEAABEAABEAABEAABEAABEAABEAABECi/BCBUKr/XDi0HARAAARAAARAAARAAARAAARAAARAAgTIjAKFSmaHHiUEABEAABEAABEAABEAABEAABEAABECg/BKAUKn8Xju0HARAAARAAARAAARAAARAAARAAARAAATKjACESmWGHicGAWsCjRo1MhJWr15t+OHxJ2Dms3bHJv9MiDEIWPExMzQyw6MRMPMxh4FJJWDFxypOLeXtkJmPOextOv69t+JjdW/zL+ndGDMfc9i7ZKx7bsXHKs66tDdjzXzMYW9Sse+1FR+rOPsavJdi5mP1LPAeFfsey3zkd0v7EpGlQKgUGT+UBgHXCTRu3NioU74hGJHwGASmT59u+NmzdieESgoQU2Dm8j9MMUQYY35IlAjzGAMvBY9fwMyLM4CZHyYlwswMvBQ8fgEzL86Ae78fJiXCfO8HLwWPX8DMizOAmR8mJcLMDLwUPH4BMy/OAGZ+mJQIMzM8KxU8fgH5WSm/W/pldCkCQiWXQKIaEHCLwMCBA42qxowZY/jh8Scg3zA5dfysif6ZEGMQ+NlCqIQxZuCx9JjHGHhZYjIizbw4AcwMPJYeMzPwssRkRJp5cQLu/QYeS4/53g9elpiMSDMvTgAzA4+lx8wMvCwxGZFmXpwAZgYeS4+ZGZ6VlpiMSPlZ2bNnTyM+Wp6kEuGiVTnqBQEQcE6AJe9NmjTRCrK6It8UYiFhdt7Ssi+RlJSkNKJh9Rz69o6XKbdGXSUegVICWYO7+aHAGPNDokSYxxh4KXj8AmZenAHM/DApEWZm4KXg8QuYeXEG3Pv9MCkR5ns/eCl4/AJmXpwBzPwwKRFmZuCl4PELmHlxBjDzw6REmJnhWang8QvIz8pVq1ZF/V0Smkp+lwARIFC2BFiA1KNHD60Ra9asoUcffbRsGxSnZ5el7llZWVor1+3cTCO+eydOW1y2zer3wmCjATy+MMYMHLYeqzGG36QtLpJ5YYzZc5JTZGb6fQxjTCak+mVe8hjDvV/lJIfke78+xsBLJqT6ZV4YYyobu5DMDGPMjpIvXuaFMebjEsgnM9PHGJ6V9sTMz8pYKCdAqGR/PZACAmVGQBYkvffeexAsma4Ea2/NmDHDiH3kkUcM/wezJ9KIbyFYMoAIz8zl8+mXfxcYUTy+MMYMHJaeQGMMv0l/ZGZeGGP+jMwxZmbyfQxjzEyLyMzLPMZw7/dnZr73y2MMvILzwhjzZ2SOwRgzEwkcNvPCGAvMi1PNzOT7GJ6V/vysnpX+udyPSRaD+VH3q0WNIAACkRBgiTIvg1u4cKFWDfvz8vJIljxHUn95Lss3y169ehlduPrqq+mpp55SeLGxw93791H3Fh2NfF718MO4/4u3G91nXkOGDNHUYDHGDCyKJ5Qxht+kD5kVL4wxHx8rnxUz830MY8xHzoqX1RjDvd/HzOrebx5j4BWYF8aYj4+VD2PMiop9nBUvjDF7Xpxixcx8H8Oz0sfQ7lnpyxE9H4RK0WOLmkEgIgIdOnSgBQsWEKt37t69W9PM4Rsnx+uqnxGdoJwV5r6fe+65NGzYMKPlrDb8xRdfaGGZ154D+4Rmzh+0ZscmategOVWrnGGU8YqHt169bPR/aOTEd40uy7w4UmaGMVa6S1moYwy8gvPCGDN+eobHyX0MY8z5GMO9X+wgFeTeL9/3wSs4L/N9DMyCM8MYM275mifYbxJjTOXFoWDM5DGGZ2Voz0p/yu7GwFC3uzxRGwi4SoBfQHg3OHmpFxumY40ljmeNJv5LVMf9Z6k7/7GKq+xYQMLxsrPixYYPuzXvSJefcCblVq+b0Ea8+SHMW67yDhm8tEF2Vrw43YoZxlgpOStm4OXsN4kxVvob43sV/4V7H8Nv0v43aTfGcO+3Z2Z1HwMve14YY6Uv+U7mFxhj7szH8Lu0/11ajTE8K+15laZE8X/e/Q0OBEAgfgkIi/0lYskS79KIvyMMxMu+7QUDL/9xEogXgwQzZ8zAyxkvjDF/Xnw/D/S7xBjzZxaIF8aYPy+MMWsmgeZSGGPuMsN9zJ8nxpg/k0C/SdzH3OXFz8poOYpWxagXBEDAXQLTpk0r4YdRsJtvIqdz/5lDKA68Sl9aQ+XFTMHMGTPwcsYLY6x0coj7mLNJshNeGGMYY+HMgTDGnP0m9Rf9UOcXeFbiWRnt3yXGmPMxxs9LNx2Wv4lRDgcC5YkAq3vyMooxY8YQ+9nmUqI6VmPl5X3ycj+nfQUvp8R8y3UwxkJjhzEWGic5F5jJNIL7wSs4I3MOMDMTCRwGr8B8rFLBzIqKfRx42bOxSwEzOzLW8eBlzSUWsRAqxYIyzgECIAACIAACIAACIAACIAACIAACIAACCUagQoL1B90BARAAARAAARAAARAAARAAARAAARAAARCIAQEIlWIAGacAARAAARAAARAAARAAARAAARAAARAAgUQjAKFSol1R9AcEQAAEQAAEQAAEQAAEQAAEQAAEQAAEYkAAQqUYQMYpQAAEQAAEQAAEQAAEQAAEQAAEQAAEQCDRCEColGhXFP0BARAAARAAARAAARAAARAAARAAARAAgRgQgFApBpBxChAAARAAARAAARAAARAAARAAARAAARBINAIQKiXaFUV/QAAEQAAEQAAEQAAEQAAEQAAEQAAEQCAGBCBUigFknAIEQAAEQAAEQAAEQAAEQAAEQAAEQAAEEo0AhEqJdkXRHxAAARAAARAAARAAARAAARAAARAAARCIAQEIlWIAGacAARAAARAAARAAARAAARAAARAAARAAgUQjAKFSol1R9AcEQAAEQAAEQAAEQAAEQAAEQAAEQAAEYkAAQqUYQMYpQAAEQAAEQAAEQAAEQAAEQAAEQAAEQCDRCEColGhXFP0BARAAARAAARAAARAAARAAARAAARAAgRgQgFApBpBxChAAARAAARAAARAAARAAARAAARAAARBINAIQKiXaFUV/QAAEQAAEQAAEQAAEQAAEQAAEQAAEQCAGBCBUigFknAIEQAAEQAAEQAAEQAAEQAAEQAAEQAAEEo0AhEqJdkXRHxAAARAAARAAARAAARAAARAAARAAARCIAQEIlWIAGacAARAAARAAARAAARAAARAAARAAARAAgUQjAKFSol1R9AcEQAAEQAAEQAAEQAAEQAAEQAAEQAAEYkAAQqUYQMYpQAAEQAAEQAAEQAAEQAAEQAAEQAAEQCDRCEColGhXFP0BARAAARAAARAAARAAARAAARAAARAAgRgQgFApBpBxChBIBAKHig5SSUlJInQFfYgzAsUlxcTjCy40AgWFB2jfoT2hZUYuWwI87vYfzqfC4sO2eZAAAuESOFx0CM/McOGhXEDmgPtFAABAAElEQVQC/AzAfCwgIiMR8wsDhasevBO4ijMhKktJiF6gEyAAAlEhMG/Tz/Ttvx/Q8p2LiSfIFZIqUKNqzenMZpfQybl9o3LO8l7pwi2z6NO/3za60a/ZpdSlfm8jDE8pgXW7V9L3qz6hlbuW0prdy4VQqYBqV6lHuZnNNV49G/UHqiME8gp20My1k+jXDZNpw57VtL9wn5ZSOaUq1c3IpaNrHkfnt7qWqqZlgpkDAi/Mvp9+2zCFOtXtQfee+LyDkomZ9Y35T9CGvauDdi4tuSI9cNLLlJSUFDSvVzPM3fQTvfz7Q9Sv+eV00dE3eBWD0e/vln9Aszb+aISdeGpXqUuDOw13UiTh8hYWF9J3Yi62cMtvtHbPCsor2E4VkytRbrWj6KjsY7T7f3Z6zYTrd7gd2rZ/E32+7F1tfrF29wo6XHyIcqo2oKOyWlO72l2pd5Ozw626XJeLdH7qxXeCSJnxgHGjjvIw8CBUKg9XCW0EgRgT4C87by8YSZNX/k85c5FQVPp311/08pyHaL4QOA3uPJxSKqQqebwe2LJvPS3dPt/A0KFOV8MPD1FB4X76eMlobYJcVFKoINmav5H4b+6mGfTb+il003EPESbKpLHiCbLZsXBpxa4l2t+01V/RdR3vpW4NzzBnQ9iCwGd/v6MJlDgJmkqlgJZsn0cb966xoOUfVUIllCT+wakEWHvkk6Vvir/RIoH9o8VLf2s6rm53NaPHQqt2L1Oei066X7Oytz9g/bNjMf13/nBav2elgu1g0QHxwe9P7e+nNd/SVe3upFOanKvk8WJgysrP6P3Fo7S5htz/zfvWEf/9sn4yzdk0jW7t9Kj4EFNNzpLw/nDnp15+JwiXmTyY3KhDri9e/Vj+Fq9XBu0CgTIkMOHPV/wESubm8IP53YXPmqMRBoGABN78YwR9vXwsmQVK5kLzN8+kJ2YOpqLiInMSwhYE9h3eTa/OfYTW7v7XIhVRMgH+2vrhX6/JUfCDQMQE+MVr1Oz7hCDpDVGXvlS8hF76/UEs742A7tnNr4igdPkuypqpw3++2U+gZO4Vf2B4ff5j2scYc5qXwlNWfkqj/3jCT6BkZsCahEOnXq4tfzanIexPAO8E/kwQ408AQiV/JogBAU8T4K9iX/7znolBEtWsXFcsf0tW4lmTafHWOUocAiAQiECRUONXXRJlpdegtOR0NVqEeFmc/1j0y+aZiOSkFGpVowP1aNSPjq/Xi6qkqsvdWOPm1bmPeoZHOB3llzR+yWdNGzh7AvpY4/Fm/mtX+wRoKZnQsYYSC3V/2/CDksLPzPNaXUOpFdKUeK8FKqdWIR5Twf7MXNrU6kyNs1qaoz0R5vv587/fR6yRJLtq6dWpZY32VEvMycyOl7DuOLDFHO2JMGuDvLdolNLXJKoglocfS8fldKfsSrWUNF4i9z+hVQgXmADeCQLzQaqPAJa/+VjABwIgIAhMXPGhwqF+RhN6qPurVKNSHbGOfwc9+cvttCrvbyPPxH8/pLa1OxtheEAgVAJ9jrqYzm15tTa2+Cv/nI0ztK+Mew7uMqrgSd/ZLa709DJLfrFKT6lMvRufowngdDj5h/fSG/MeV15kV+YtJY6vkpqhZ8PxCIH9h/fR07PuMmxSAYw9gdY1O9IjJ79unwEpCoF3Fz5DP639TonjDzF3Hj+CWtRoq8R7MXBN+3uI/wI5nl/cPLGfshy1v7BJ5VW3bMcioXm6XOn+xUffJJ6Z14jnYenr24y139Lr8x4zmPG9/+e1E0WegUo5LwS+EB9DZQFclrAxdc8Jzxq/PzYs/Y74nU5d9bmBg+1UndrkPKqX0ciIg0clgHcClQdC9gSgqWTPBikg4DkCuw/uFOrTvi+tqRUq0l1dntJe+hkGa5Tc3vlx8dW1osGG1Yi9+mXMgACPQwJJdF37e+m6DkONscVG4LvU70X3deUvjT5bLWxgk7VLvOza1emiGWLl35/sWHDEds1qV6kvR2MJnEKjNMBCSzbMHarNIIsqEAUClgR+3zhdfIz5SEnLqdqQnuj5jvFCqyQiYElg0oqPDeEIZ+APWsfmdLPM64XIv7bNU7p5krCXd0Hr6w2BEif2yO1HLGiS3cpdvo9+cnyi+3nTD9nd0PF+5ffHGwzc2PEBal69jZGNl+H/vG6iEYZHJYB3ApUHQoEJQKgUmA9SQcBTBKau+kKxdXNyo75id5FmCoMGmU2oe+6ZRlwJFdMP0pcfIwEeELAgUEvs8HZLp0eoT7OLLFKJmouv+p1MRm3X7l1hmReRJJYNVtSWQsgsIOSVaZT6P/jrVfpjyy/+CYgBgQgI8EsXawvKjgVKw05+k6pXqi1Hwx+AAGuRmDcG6dfsMk/vMLjvUJ5CjHeptHKd6/ZUotd58HnJthd5ubzueGe8TnVP1oPGkXesZE0v2W30+EcrmYXZj3cCMxGEAxGAUCkQHaSBgMcI/LH5V6XHnW0mMcfmnKTkm78ZL2sKEARsCVze5jbq1egs23ROaJDZVEnfdWCbEkZAJbDv4G4lIjdTFQQriR4MzFz3PX2xbIzR80opVQw/PCAQCQE2YLvnkG+5Lu+GeneXZ4RAqVYk1Xqu7Iw139BeSYiSmZat2Y7zHAipwykmO1z5h/ZIqT4v76gqu3QhUPGaKy4pIv7THQuP+M/KNRAacLLbsG+1HIRfIoB3AgkGvEEJQKgUFBEygIB3COws8Bl4ZMOibWsfb9n5trW7KEa7d3rUMKQlHERGTGDvIVVIUltoN8FZE1i6/Q9auHWWkcjGuxtmHmWEve5ZJZaC/HfecAMDf8Ee2vU5IwwPCIRLgDUCZ4it3GV36TG3UqOs5nIU/EEIsJHzb/6doOQ646gLNS1MJdJjgVY1Oyg95k0r2C6c2X2s7Tboi62f2dgX8IgvNTmN6lRtYPSWBW28y6eVY+Pdstuav1EOwi8RwDuBBAPeoATUX1bQ7MgAAiCQqAR4Yrdj/1ajezUq17Gd1PFOLtnCCKLu8gp2ClsIhXoQRxCIiMDKXUuU8g0ymiphrwf4Zfbv7Qvo/UUv0BMzb1O+0LYTgmC7L7Re48YG35+e9X9iO/cCo+uDOw+jhtUgdDOA2Hj+3DaHrviiG9079Qp6ec5D9P2KT3CPN7H6evl4Zbk42zbzsmFpE56Qg/M3zxS2zlYb+fmDFguVvO5aiR3eZAEI71Z2/7SBtHDLLG0zhtV5/9CIX+4g5ie705pcIAc9429crYXS19fmDSPeuUx2O4XW86fL3pSjqGqauouqkujhAN4JPHzxw+x6SpjlUAwEQCDBCLAKPxst1F1GWpbutTxmpFWTDHSX0M4DW4XBYGiUWMJCZMgE2EbJmt3/GvnTktOpbtVcI+x1D2+bPPj7cywx8G5T13S4xzLNa5Es5H521lDavn+z0fXzhC2NE+qfQjzG4IIT4J2UeDdB/uOdzSat/JjY+C3vDOd1xy9cv4hllbIrEcbgh/10I23OX69plNTLaExNslpSz9z+ZNY6kct53f+NEM7JrntuX6pWsboc5Ul/ZsVsYZh7EH2ydLTR/w17V9HjM281wmbPSQ1OFzb22pmjPRHm3WRnbfhR9LVE6y9/VHhw+jXUoc6JVKtKXWKNJDZ+frj4oMKDDcLD+RPAO4E/E8QEJgBNpcB8kAoCniEgaylxpzODCJWqCqGS7FioBAcCkRL4fNkYRfPmlMbnUHKF5EirTZjygTQC7xXLumQNwoTpdBgdeXfhs7R0+3yjJL9YXHLMLUYYHucE1u9ZSQ/PuN52WYnzGstvCTYKnFewXekAa5IsEWOOn4W8/IY1Lnn78odnDKJxi19SdjZTCno4sDpvGbFWnM8lUf9ml/uCHvfxbm8sCA/FHV3zWLEb6GOhZE3IPMfUOo5ObzpA6VuJEDDxBg1sBH7Bll/9BEqcuV5GI6UMAqUE8E6AkeCUAIRKTokhPwgkKIGi4sNKz5LEFu+BXHIFVdGxSDKSGKgc0kDAjsCmvWtpslhmo7vkpBQ6q8VVehDHIAQeEi+vf8BoPv2w8jPxEuEbR1npNejm4x6iw0WH6GBhgXjhP6CQLBT3Po7nPy+7JtVaajsmnSZezLo17EPNso9Rlt+UsikhXlbCWgBedou2zg65+/xiy/Zw3l0IW15maF8vH6dEdajTVSxPxXJnHcrKXUvpn53qEi49zXxcJ4S+y0PMay6bKOGr2t4pDLz3d9Sd+lUbO8rvlcx4J/DKlXavn+pboXv1oiYQAIFyRiDLtFtN/uG9AXtg3omkejq2Tw4IDIkBCfByktfnPya+JB4y8nXPPZNqVc4xwvAQVa2Yqb3wbxA2SFhbQt7xhrUj3lowkl48/TNKMQl9vcKObU0xA9nlFeygG787U45S/Jr9oC9Ld7R8sNur1L7OCUq6VwJDuozw6+qGPatp7OIXaN7mn400FiiNF7uesaDOq27rfmvjvjXF/apW5Xq0q2Abbd63TsHD2hLdGp6B5YNHqLB9m1/WTVYYnd3iSiXs5cB2YTtvxK93WAhwk6iy2MFyf2G+wFO61Is58e55I3+9i0aeMo7qCPteXnQVU9JpcKdhdFxON5q44mNalfe3pjXILHiThrTkisougyTE5q2FhhecPwG8E/gzQUxgAhAqBeaDVBDwDIHSZTO8BWvpJEXe3tcKwh5p+19Or1EZQiUrTogLjcAPqz7Tlo7oudmW0oBWg/QgjkcIsK2RO45/QgvtE7vkvTZ3OM3ZNN3gszV/A/2+cRqd2OA0I85LHtaikW3DOe27LNR0WjYR8/NOUkNPfJ6eFi+rsmBp2Y6FidjdkPuUd0Bd+tYgsyld2fYOOla8zOqODSjzeNwtNrIodSX02d/v0APdXtazePo4acVHym+VDS3b7TjrRVCfLHlDESilVqhIF4rlcGc2u4TSUyrRgcP5QnDyEf1v6ZvGx5j8w3s0G0wsWPGy6yqef/xXLOyc8cYWlVIqC4Pc1WjUrPvo1w1TDDQdxbJoaMYZOBQP3gkUHAiEQCDw+pYQKkAWEACBxCDAmg3V0rONzuwSXxFZe8TK8YPaN1Em4m3M+QsQHAiEQ4C1Id5bNEopemWbOyhH2iJYSURAI8CT5Lu7PkMNM5spRNYKDSavugNCWwvOXQIVxFLoWzo9Iirljw6lbuPeNWJXPdXgrZ7mheNeIdCV3eDjhikCJU5jAdOtIl52a/Z497cpc+AlqKy5Jbt+zS+Xg5728xzr57WTFAaDOtxL57W6RhMocUIlsQvv+a2upUEd7lPy/bpuiiZMUSI9GuB7Vy2xgQU/K5eLneB+2zBVIXFOy6uVMAI+Angn8LGALzQC0FQKjRNygYAnCPASNl1YxMvfeD3/UdWP9us7f6XmnYF0V6NyHd2LIwg4IsD2bF6cc78yntrVPgFbSodIkSfNbMx8zCKfvRa2TeVVx1/ozS/8ZhZ7xfKtdxY+Y0TnVG1IFx99sxbGzmYGFsXDO1GxbSrdOHUJFdOWfRs8+5Wfdz+Vnd1mAh1zThTcahrc+GMNaxiaN7qQ6/KCf/rqr0leYp8tlt/z0kC4UgI7hLF3eZcy3o23d5NzLPFw/Pg/XyberYsdl+PyWDruw8UC8FfmPSL08IuNyKOyjyY27g1nTwDvBPZskOJPAEIlfyaIAQHPEmiS1Upbg64DmCfU962ESnM2ztCzaMcW1dsqYQRAIFQCY8WuSKvEDkC6qym+KvLyrqQkn1aEnoajNYEKSclKgpfZhWIPaffBnapQqUpDvNAqI8g/wEbMzca52b6XV129jMZK1zfnr6fGWS2VOD1QUSzllZ21/q+cI7H9rIXz7YoJSif7NL1I2IFLVeK8HCgQS9tkVym1shz081dOq2oIlTiRbV5CqFSKqai4iP47bzixdqXsLmx9gxyE34IA3gksoCDKlgCWv9miQQIIeI/AaU3OVzo9Y+03hpFDPWGfmKzMXK+qZZ/R9EI9GUcQCJnAb+t/oO/+9b1csM2Ie054ljIrZoVchxcy7jmYF7CbvFWy7HKrNZeD8INAQAL80sUv+oHchL9eVYzCV69Um0ptbgQqlbhp9TJylc5NETsOWrktwsbZ1vyNRlJ1oZFj1nIyEj3imbfpJ8WIORtQPr3pBR7pfWjdZO1J3v1Ud1vzNxEvE7dyLOzdJtJll12pphz0rJ/tTj35y+00c506Z+WllsfV7e5ZLqF2HO8EoZJCPiYAoRLGAQiAgEGgWfVjiL9M6I6N/o7+Y4Qe1I6vzn2EWIVfd6yl1DirhR7EEQRCIrB+zyp6de6jSt6bjnuQmmb7xp+S6NHAroLtdN03p9JTvwyhZTsWKRRYEMCGf9kgsOyaZreWg/CDQEAC74vd3e6ccgH9tPY7P+ES7yg4TmgTysJfrqx5dpuAdSZ6YsvqHUjWEFy0dRZ9sew9pdv7xQvta3OHKUtuGlez1mZSCiZ44Kt/xik97NX4bLEc0LtabwqMI4HU5DRqpMyrSui52UPFktP1SnYWKD03a6hi8Jxt7PGGDl53vLvgQzOuI/5tyq5VjY7ENhvhghPAO0FwRsjhI+ATg/vi4AMBEPAwgdObDKA3/ijdXYox/CxeNNjwb45YIrJh32pav2elQueMoy5SwgiAQDAC/PXwmVl3K3aUuAwbbjUbb9Xr4he4e8UuVFVSM/QoTxxLNA2SEm3nLd59izVEGmQ01Tis3r2MNu1T7SfVy2hER2OLZE+MDbc6WVh8SFsa8vKch2isEDCx4IN3l+KNGv7eucCws6efj3+L57S4Sg968lg3oyGdIbRrePct3Y3/8yVNwNumVmdiW3E/r5tI2/fLGiRJ1K/ZZXp2Tx5X7FxCf+/4w+h7kjD+7nUmBgyTp1fuWcKu5RIjdt2eFTRECH871+1BvEx898EdYqfP6X7a5Cc2ONUo41XP2t3/ahpKvPOb7Ngu3F0nPEV2NtDkvPCXEsA7AUZCqAQgVAqVFPKBgEcI9Gx8Fv245itavnOx0eM1QqjEf2bXtnYXYYukjzkaYRCwJcAvqqyhtHHvar88wbYp5y//XhMqmSHtFAZY+c/KJQnl49s6DcdOjFZwEBcSgbyCHbSgQF1OaS44oNV11LwG7OhddPSNmnaXbHB66fb5xH9Wjpd4tavTxSrJM3Ff/ztO6Wvnej2xy6dCxBfo0+wi+nPbHJq98UcjkoWVv234wQibPa1qdKDzWl5rjvZcePjMm/2E4dXSq9O9XZ/39LLdcAYC3gnCoebNMlj+5s3rjl6DgC0BNpZ59wlPU4PMprZ5OKFpVmsacvyTYgkAbiMBQSFRIfCBsM0iT5KVRATCJlA5pSoN7jyMmlX39rKksAF6uCBvHR2KYxsvA1oN0v5CyZ/oeXgHt+E93qL6GU2CdrVHo/50VdshQfMlcgZeSsl29GR3VvMr5CD8JgK3dHqEutTrbYq1Dh5Tq5PQwhkJLRyBZ0DLQQokNtPwdO8JeD4qVEIL4J0gNE7IRRTaTAKkQAAEPEWAl9iM6PUefbTkdfpx1Ze0v3Cf0f8qqZnCqOYAuqD19dCIMKj4PGkp6b6A8Jl3/lESPRbgrd7NdkdCRcBaOKG+/IZaZ3nIx7/FJ3qOEdqDX9Jv/8/efYDJTZwNHH+v+u58dy7YuGM6AULvDr13+ELvndAhtEAgNNNr6ITeQ3FC76HEoRhM79VgG+N6ts/2na/vN69srSWtdlfa1V7Z/c/znFdlNNL8pJVP782MJr/m+i7q8VeX9ZG1TOuHQ9c83XSNG9gTqtTlx6jBEe3C1RFrt46l0L+jh615hqw96A/y5i/PymfT30u4xvR17yv2XV0O+v3JMqx22S4/f93pAJbps6JcufVD1ivdPzbdU52Dcut1NsL8cWa/1Y+X9Yds3p0Ou0uOpaK0Ss7f9BZ56cfH5UMzWPeK/VeT3w1Yu0uOpafstKqsWs7c5BrzvRxnfh+7XX6Z+720mu6qdtJrbFjtcibQe5SMGr6dvbjgP3dacT/TNXyi1T1VWwgesdaZvF3QXBWZ/n5ayM8EmZo5v4RRlOEsr7tOF5muCIX+dtPuem44LgS6hUBbR5v1ZpGYdFgPYgNNX376o3eLU8NBFKCA/aafpvaFouMnFfIbuArw9HdKlRtbF5ixgKaZPxpUWG9i1AdbUjAB7Qo3uf4n648JI/qswINsErZZZqyb9vZWGVQ9PEkOFvsJ6MsZpi+YInULp5l7/0DTddC8Ja64xC9rwS9Tq5lmTLNBvYcVvEWUADwTRKmZX2URVMqv80ltEEAAAQQQQAABBBBAAAEEEEAAgU4RYDCUTmFmJwgggAACCCCAAAIIIIAAAggggEB+CRBUyq/zSW0QQAABBBBAAAEEEEAAAQQQQACBThEgqNQpzOwEAQQQQAABBBBAAAEEEEAAAQQQyC8Bgkr5dT6pDQIIIIAAAggggAACCCCAAAIIINApAgSVOoWZnSCAAAIIIIAAAggggAACCCCAAAL5JUBQKb/OJ7VBAAEEEEAAAQQQQAABBBBAAAEEOkWAoFKnMLMTBBBAAAEEEEAAAQQQQAABBBBAIL8ECCrl1/mkNggggAACCCCAAAIIIIAAAggggECnCBBU6hRmdoIAAggggAACCCCAAAIIIIAAAgjklwBBpfw6n9QGAQQQQAABBBBAAAEEEEAAAQQQ6BQBgkqdwsxOEEAAAQQQQAABBBBAAAEEEEAAgfwSIKiUX+eT2iCAAAIIIIAAAggggAACCCCAAAKdIkBQqVOY2QkCCCCAAAIIIIAAAggggAACCCCQXwIElfLrfFIbBBBAAAEEEEAAAQQQQAABBBBAoFMECCp1CjM7QQABBBBAAAEEEEAAAQQQQAABBPJLgKBSfp1PaoMAAggggAACCCCAAAIIIIAAAgh0igBBpU5hZicIIIAAAggggAACCCCAAAIIIIBAfgkQVMqv80ltEEAAAQQQQAABBBBAAAEEEEAAgU4RIKjUKczsBAEEEEAAAQQQQAABBBBAAAEEEMgvAYJK+XU+qQ0CCHSSQMfCRmn55adO2lvP3g1W2Z8/DIMbYhXcys6JmS2R/hOr9EbpcmCYTmjJeqyWWASZwiuI0qI8WAW3SpYTwyUyBJWWWDCFAAIIpBWIdXTIvOfHyMT9t5em775Mm7+QM2CV/dnHMLghVsGt7Jyx9naZ98xjMnG/7aTlh6/txXz6CGDlgxJyEYbBwbAKbqU5uf8H98IquFWynHw/E2VKExexBAEEEEDAT6Bx/DtSd8tV0vLTd9bq8mHL+GVjmRHAKvvLAMPghlgFt7JzLnj7dZl927XSOmmCtah02Eh7FZ8eAaw8IBnMYhgcDavgVpqT+39wL6yCWyXLyffTX4agkr8LSxFAAIG4QMuEH2TWrVfLwvfHxpfpROnQEa55ZkSwyv4qwDC4IVbBreycTV99JnW3XS1Nn31oL7I+y0YQVHKBmBmsvCLh5zEMboZVcCvNyf0/uBdWwa2S5eT7mUxm0XKCSql9WIsAAgUs0DZ7lsy++0aZb7q7ien25kxFlVVS2n+Ac1FBT2OV/enHMLghVsGt7JytUyZJ3R3XScObL9uL4p/FtX2lpKZPfL7QJ7DK/grAMLghVsGtNCf3/+BeWAW3SpaT72cyGfdygkpuD+YQQCCkQNucOintt1TIrbp/9o7GBvnt1MOk9ecffQ+2LINWSlj5UoZaiGFwLqyCW2lO/eU7XwPF7fPnydSzj5PWif4vFygbHq4rL1bhri2/3Bj6qfgvw8rfJdVS7v+pdNzrsHJ7hJ3j+xlWLD/zM1B3fp5XaoVApwgsNN0nJu6zjTXQa6fssBN3UlzVW4bf8bjU7PxH372WhRxPCStfxlALMQzOhVVwK8258NPx1r1s7r8eCbdhD8ldUlMrw+8eIzW77+t7xGXDl/Vd7rcQq+BWfn66DMPghlgFt9JrSxP3/0UOQf7FKohS8jx8P5dNjlNgawgqFdgJp7oIRCXQ8stPMu2c482gEwtl5jUXSt2dN0RVdLcpp7h3tdTudbAZPCmxUWfpsODjKWEV3CrZyccwuCFWwa30emsxA1VPO/cEkeYmqbvhEjN+2lUSi8WSXYo9dnmx6bJbvdVOIkVFCXUI2lIJK5GgVgnIixdgGNwQq+BW9vXG/T/4/R+r4Fb29eX85PsZ/vvp9Mu3aYJK+XZGqQ8CnSRQ0qeflDneFjT3wTtkxqV/kVhbWycdQe5309HYKNMv/LPpF7OoTsXmr/12CtP9DavsfnFRcwyDG2IV3Mq6tmr6StmIZXXSSvX/vFemX3CadLQ024vy4lO7KEy/5Ezz7u1FAbPivv3j9Sp31D++0GeiBCsJauXDZy3CUAIbYhXcyr7euP8Hv/9jFdzKvr6cn3w/w38/nX75Nl1ykUn5VinqgwACuRcorqyU6u13k5YfvpHWXydaO2z58VvrbTm9N99WisrKc38QOdxDrL1Npv31JGn55nNrL0W9e8uIe56WitXXkoUfj5Pa3fczQbVg45BgFdwq2SnFMLghVsGt9Hpb5LW7tJrWl60TJ1iXYOsvP5rv+fvSe7NtpLiiMtll2WOWa4B86ulHSduvv1jHXGxeMjDigWelfPlVTD3fkz77HiGlAwelrQ9Wwa2SYRa24cpcb54LI6rvpl0s9//g93+sglvZ15fzs7DvZeH+73S65es0QaV8PbPUC4FOECgqLZPqbXaWtrqZ0vL9V9Ye236bLA1j/yOV620sJY6/hHfC4US2C+36MuOyc6Xxv6/Gyxz01yulcu0NpHyFlaVmxz2ldOnBoR42scr+wRzD4IZYBbfSL3mR6eLae6sdpWPBfGn++jPre98+Y6oseP1FqVhj3UABl/jNoptNxFpaZOpf/iTNX3y86MhM97fBV94uvcy9rNdKv5Pq7XaVskFDzR8CygIdOVbBrZKBFq7hqouut8HBDQvXKvx3077euP8Hv/9jFdzKvr6cn3w/g9/LnG75OE1QKR/PKnVCoBMFioqLpfemW1vjdDR98oG15476OTL/paesljzly6/UiUcTza7qzJgq8595LF5Yv8NPlD77HBKf10G8M2m9gFWcMOMJDIPTYRXcSnMWmWBL1cabS3F1jSz84B1r446G+eZe9rRZVisVq60ZrsBukDvW3i7TL/qzLHxvbPxoBp59iRlbacf4fImpW9CAkr0RVrZE5p8YBrfDKriVnZP7vy2R/hOr9EapcvD9TKVTOOsIKhXOuaamCORUoHKdDc0ApiOlYdz/REzXMWlrlYa3XpEO8yrryvVHif6n3RPSbDM21NwHbo8fas0e+8mAk8+Jz0cxgVX2ihgGN8QquJXmrFh9bSlfeTVZ+P7/JKbjKnV0yMJxY0UHda3aaLMe07U3Zo575lXny4L/vBAH6H/cGdJ3n8Pi89lOYJWtINdbGEGutzBai/Jy/w9uhlVwK7+cfD/9VApnGUGlwjnX1BSBnAv0WmEVqTZjkDR++J50zJtr7U+7kui8/mddUtsn58eQ6Q60y1vdbVe7Akq9t9hOlj7vKqsFQ6blJtsOq2QywZdjiJX+hTQXqXyZ5ayuvQs//1ja62ZYu2j9+UdZYALlFaut1e27w3WYN9npYOMNry8JKPXZ/whZ6uhTI+fCKntSDIMbYhXcys7J/5W2RPpPrNIbpcrB9zOVTn6vI6iU3+eX2iHQ6QIl/ZaS2p3+T1on/xwf9LZ9xjSpf+5Jq8tYL9OFJFcPgplWVt9YN+PSs02Xt8fjRVSsu5EMufxWa6yV+MKIJ7DKHhTD4IZYBbfSnCXmbY96L2uvnyvN335pbazB8vnPj7HGXqpYa31zfwg2DlG4PWeXu33ubJl6xlHSZIL5dqrZZS8ZcPoFObv3YmVLZ/6JYXA7rIJb2Tm5/9sS6T+xSm+UKgffz1Q6+buOoFL+nltqhkCXCRSVl1t/5S+uqLLelGa9wtp0iVv4wdvSOP4dqfj9ut1mEO/2+fUy9dwTpPHtN+JevTffTgZffosUl/eKL8vVBFbZy2IY3BCr4Faas6ikRHqP2tK8An05aTT3L+3Wq6n5q09lwWvPS/lyK5mx47J7LbNVYET/tEyaIL+deri0/vRdvMQ+BxwlA/78t5wFlOwdYWVLZP6JYXA7rIJb2Tm5/9sS6T+xSm+UKgffz1Q6+bmOoFJ+nldqhUC3ENC3JlX9YSvrAax9dp11TNpqad5zT1gPZ71+t0aXjk/SOP5dmfrnI6X1xyUPYLX/d6Dp8nalFHdyCwSssr9kMQxuiFVwK82pb32s3n43a1yltimTrI07FsyTBa88I61TJkuvVVYTHfC6q5J2363/1yMy7byTpWPOonutiSLJUn++QPofdnzOA0rOemPl1MhsGsPgblgFt7Jzcv+3JdJ/YpXeKFUOvp+pdPJrXZH5RSSWX1WiNggg0N0EtHvZnIf/IXPuNwNgL/5Lvx5jcZ9+0u+w46TPngeK/lWos1KHGXx39h3XSf0TD7h22e/YP0v/Q49zLevsGayyF8cwuCFWwa3snPPM2+Dqbr7cjBtXby8SMUHoPnvuJ30PPV5K+w9YsrwTptpMoH7GFefKQhMkjyfTynLQxdebMe62jS/qigmsslfHMLghVsGtNCf3/+BeWAW3SpaT72cymfxYTlApP84jtUCgRwi0TPjBevhp/uYL1/GWDhoq/Y440WoJkMsuZxpDb3j9Ram7+0Zp+3Vi/BiK+/aXgedcJtWbbh1f1tUTWGV/BjAMbohVcCvN2WZaA826YbQ0vPGSe8OKSvN2tUOlz16HSOmAge51Ec91NCyQuU/cL/WP3Sc6bafyFVeRQX+71mpdZS/ryk+sstfHMLghVsGt7Jzc/22J9J9YpTdKlYPvZyqdnr2OoFLPPn8cPQI9TkBfcz3/tedkzt03SdvUX13HX2zeDlez4/9JrfmLf/kyy7vWZTuzYOxr1j5bJnzvKqrKjJcy8NzLpdQMMN7dElbZnxEMgxtiFdzKzrnwsw9l9j+ul6bPP7IXLfrUsZj+sLXU7r6vVG64qRQVF7vXZzHX0dgoc8c8aIJJ97pbS5nubn0POkb6H3WK6Vbc/QYQxyqLk754UwyDG2IV3Epzcv8P7oVVcKtkOfl+JpPpucsJKvXcc8eRI9CjBWKtrVL/zGOmS9xt0mHeVuRNFWtvIL1N142qDUZJ+fIre1cHmm/+4RuZ/58XrNZJbdOmuLYprq6RpU44yzz07eda3h1nsMr+rGAY3BCr4FZ2zsb3/it1d14vLT98ay+Kf2pLzN5b72Tdy/SNccW9KuLrgk5ol93GcWNlgWlp2fjuWxJb2OjatMwE4Zc+91KpWGM91/LuOINV9mcFw+CGWAW30pzc/4N7YRXcKllOvp/JZHrecoJKPe+cccQI5JWA/tW9/qlHZJ4JMLX95m65ZFe0eKmBUrX+KOllBsstHTLc/AyTssHDrEG+Y60tZlyAdok1N0nr5J+l2bz1qOWn76Xp609NF7dFA+ra5ehnUWWV9N33MOmz/5HWK8Od67r7NFbZnyEMgxtiFdxKc1rda996xQyY/bA0fTref2PTgkgHfq34/TpSNtTcywYPlzJzP9NXWMfMGzJ13A4xAff2+rnSPGHRvcy6n33xkcQaGxLKLB2+jPQ7/ESp2W436011CRm66QKssj8xGAY3xCq4lZ2T+78tkf4Tq/RGqXLw/Uyl03PWEVTqOeeKI0UgrwX0P5WF49+ReU8/Jg3vvCHS3h5pfYtraqVm172ln+keUmLGUOrJCavszx6GwQ2xCm5l52wxAe55zz4h8198Sjrq59iLI/ssW3YF6XvAUaa78B4mmFQaWbldURBW2atjGNwQq+BWmpP7f3AvrIJbJcvJ9zOZTPdfTlCp+58jjhCBghNomzXTdPF4UxpNkGnhR+PMuCFzMzIoquotvTfdRmq23WXRuCalPfvhyw8BKz+VcMswDO6FVXArzandIxo/eFsWfviuNJqf1p9/DFeAI3fpiGWlxnSjq956524zCLfj8LKexCprQq63EIRcbyGwFmfl/h/cDKvgVn45+X76qXTvZQSVuvf54egQKHgBHRCx+fuvpOmLT0z3uMnSagb3bps6Rdqm/2b+gtZh/kpvBqQ1XUqKzSu9SwcNMQ9bq1jd5PSzfJXVJZdvk+tuJwer7M8IhsENsQpuZedsq5spTR+Pk5aJE8y9zNzHzFhvek/rmD9PijTobVod6SDb2k23fOQKi+5lZky58pV+J+UjlrOLKYhPrLI/zRgGN8QquJXm5P4f3Aur4FbJcvL9TCbTfZYTVOo+54IjQQABBBBAAAEEEEAAAQQQQAABBHqMQHTvuO0xVeZAEUAAAQQQQAABBBBAAAEEEEAAAQSyFSColK0g2yOAAAIIIIAAAggggAACCCCAAAIFKEBQqQBPOlVGAAEEEEAAAQQQQAABBBBAAAEEshUgqJStINsjgAACCCCAAAIIIIAAAggggAACBShAUKkATzpVRgABBBBAAAEEEEAAAQQQQAABBLIVIKiUrSDbI4AAAggggAACCCCAAAIIIIAAAgUoQFCpAE86VUYAAQQQQAABBBBAAAEEEEAAAQSyFSColK0g2yOAAAIIIIAAAggggAACCCCAAAIFKEBQqQBPOlVGAAEEEEAAAQQQQAABBBBAAAEEshUgqJStINsjgAACCCCAAAIIIIAAAggggAACBShAUKkATzpVRgABBBBAAAEEEEAAAQQQQAABBLIVIKiUrSDbI4AAAggggAACCCCAAAIIIIAAAgUoQFCpAE86VUYAAQQQQAABBBBAAAEEEEAAAQSyFSColK0g2yOAAAIIIIAAAggggAACCCCAAAIFKEBQqQBPOlVGAAEEEEAAAQQQQAABBBBAAAEEshUgqJStINsjgAACCCCAAAIIIIAAAggggAACBShAUKkATzpVRgABBBBAAAEEEEAAAQQQQAABBLIVIKiUrSDbI4AAAggggAACCCCAAAIIIIAAAgUoQFCpAE86VUYAAQQQQAABBBBAAAEEEEAAAQSyFSColK0g2yOAAAIIIIAAAggggAACCCCAAAIFKEBQqQBPOlVGAAEEEEAAAQQQQAABBBBAAAEEshUgqJStINsjgAACCCCAAAIIIIAAAggggAACBShAUKkATzpVRgABBBBAAAEEEEAAAQQQQAABBLIVIKiUrSDbI4AAAggggAACCCCAAAIIIIAAAgUoQFCpAE86VUYAAQQQQAABBBBAAAEEEEAAAQSyFSColK0g2yOAAAIIIIAAAggggAACCCCAAAIFKEBQqQBPOlVGAAEEEEAAAQQQQAABBBBAAAEEshUgqJStINsjgAACCCCAAAIIIIAAAggggAACBShAUKkATzpVRgABBBBAAAEEEOg8gY6WZom1t3XeDtkTAggggAACnSRQ2kn7YTcIIIAAAgj0WIGm77+W+S+MkZaJE6R9xnSJNTdJSf+lpHTgYKneaU+p3mzbHls3+8Bjra1Sd8d1EmtrsRfFP2u22UUq1lwvPs8EAgikF4i1tEjdPTdJ47tvSesvP4oUFUnpoKEy8OzRUrXBqPQFkCO0QNv032T6JWfHt+t/9ClSuc6G8fmePtFh/u+ZevafRNrarar02XN/qd5u155eLY4fAQR6uABBpR5+Ajl8BBBAAIHcCXQsbJQZl54tDf99LWEn+vDS/M0XUr7ciiJ5EFTqaFwg9Y/fl1BPXVDSfyBBJV8ZFiLgL9A2e5ZM+8tx1j0iniMWk7apv0rHvLnxRUxEK9A2u06aPhsfL7T1t8l5FVSKNS2Upo/GxetXufb68WkmEEAAga4SIKjUVfLsFwEEEECgWwvE2tvlt9OPkuYvPu7Wx8nBIYBA9xOYfdff3QGl7neIHBECCCCAAAKRCBBUioSRQhBAAAEE8k2g/t+PEFDKt5NKfRDoBIGWXyfK/Bf/7dpTr9XXkvLlV5H2ObOkdMSyrnXMIIAAAggg0JMFCCr15LPHsSOAAAII5Eyg4a1XclY2BSOAQP4KNI413WVNS0c79dnvCBlw8jn2LJ8IIIAAAgjklQBBpbw6nVQGAQQQQCAKgVhHhzSbwbn9UsnSg2XpMy8WbXnQ+tuvUk6rAz8mliHQqQLNP3wrM648T0bc869O3a/fzlqn/bZksRmcu+/BxyyZZwoBBBBAAIE8EyColGcnlOoggAACCGQv0Gre8hYzg3T7pZrtd5eqUVtaq0r69PPLYi1rmzldWn76TlomTbDeGtdqusQUlZVL+TLLS/myy0uZfq6wipTU1CYto2Xyz76DhBcVl0jt3gdLcXkvaa+fI/XPPC4t334p7QvmS5kJcumbpXpvsb152VRR0rKjXBFFXf2OJ4py0xm2/TpJmj7/UJp/+t46T0Xl5VI2ZLhUbrSZ9N5kcykq4Vclv3PTnZY1ffeVTP3zEdLR3NwtDqtt2pT4cRT3M2+JND8kBBBAAAEE8lWA35Ty9cxSLwQQQACBUAKx9japu/UaibW2mODCT0m3bfriE5l53cXW+r4HHmUFIJyZOxoWyOy7b5T6fz0sYlo8edPCcWPji4p695b+R58mff54kAlelMSX2xP6lp/Zd1xnz7o+NWjUZB5ep19ypnTUzYyva/p4nMx/5jHp9ft1ZPgdj8WX52Iiyro6jy/KclMZNn35iTT87z8i5q1czrTQzMx76lEpGThIlv7rlUlf/97R2GBejVcixb0qnJtnNR1rbZW2WdOldOBgKSrtml/TojiGmDFtN4FVE9k0bw8c4Ht9ZwW1eOMm8wZGK6BkAqqS4XmIor7OurTPqYvPlvbtH5/uiok2c2/QQGlJTZ/Idp+pl36v2+fXm2t7UEbB2iiuKQ1UF1fXSHFlVWQeURSUrU0Ux5CujEzPe7pyWY8AAj1foGt+W+n5btQAAQQQQCDPBGLNLVL/xP1pa6Wvq7ZfWd37D1u5gkoLzFgqGnByBnlSFRhraJC6Gy+T+S+MkYEmeFGx8mqpsrvWNU/4TmZcclbSFlXts2eaWEksZ62VclXXXJXrwls806Bj36RIGhTRgMVSf75A+u51UDynuk7/26nS8PbrUlxRKf2OPlX67n1IfH3YCW1tNvvum6Tpy4+l5WcT0GxrFSktMwM7rySV621iAo+nxANXrSaQOPUMd3cq7V5Vu9P/+e5WA19TzzlB2h2Bx8p1NpSBZ17kyh/mGFwbOmY6TOu+OQ/eIQs/HS8t5vrU69tKJvCmdanZbnep3mF3KV1qoLROmSRT/3KcCegtyjLglHOlyrQO86YFxnj27YsDq6bh3dDr75VS0wVVU9NXn8pU84ZGfSC3UnOTTDpo50XTi/+tWG1NWfq8K13LdCaK+noL/fXYfcyxNEirIyjdMuH7+DH13f9wqd1tX+9mooGfRhPctFrLTfjBBLabpcgEPXqZlozamrF6qx2luKp3wnb2giknHyLtsxcFsqq33F76H3OaNJqA9MzrLpK2ST9b2bScfkedLNWbb2dvFuozU68m8/bMOQ/faVptfi/xFlzmeigbNlL67neY1Oy6T8qAY5hrKlmFrGN49B7z/fpEOjTgZ75bFWuuJ71Ni9M++x4mRcXFyTb1Xa6BsSknmPvB4j8a6PU49IZ7ffNqIGbKCQdIR+Oilq/FpmWqHezP1sZvh1F8r5zlZnrenWUwjQAC+S9AUCn/zzE1RAABBBDoBAF9eJx+wZ8XBQRC7q/lx+9k+rknyoiHnk/58OgsdvqFZl8tLc5FrumaHfbMWUApV3XNVbkumAxm6m66THqtuIpUrrW+tfXC8e+IPZB7h2khM/uuG6R2l70yav2gD/8zRp8p7bOWtDazdmICSy1mXC/9aTSt2wZfepOUjzTdJgcPkwoznpfz7WIzrzrfBFqGSNV6G7tqp2ODTb/4DNHWa/FkWq0s/dcr4rM6EfYYXBsvntEH9umXni3anTAhmUGrW8yYR3Xmp80EOwecdI60z6uX1l+WtAhsmzUjYTNdoIE9Z5CmY8E8EfMQ3/TFR/KbCa7FtLWYIznz6mK/FilR1Nexy/hks+mG5xyg215hH1Pr1CXd4nSdBifnP/ek1N12teh15E3ayk7TnHtvloFnXSJVG2/uzWLNN3//VTyA1zL5F1lgAlQa9JS2tnh+7Yo7/a8nSdOBR8uAE86KLw8ykYmXXntzHrrDHPstiSbmemg13YJnXnOhzH/teRn69/t9W+WFvab86jLv+THSbFqzWYFaO4P5bul3Qn/aZkyVAaf81V4T6LO42nRZjnXEr0s9v43mnlC1wR8Stp//xouL9r94TdUmW5hNs7dJ2NHiBdl+r5zlZnLendszjQAChSMQLjRfOC7UFAEEEEAAgcAC2nVu+mXnuB9cAm+9KGPb9N/Mw+U1wbdKEVDSQmp23CN4WSFy5qquuSo3RNWSZzUPwbNMizI7aRcaZ9IWOfHWMs4VaaabTMBIW0IlBJQ827X+/INpkXOkxBaf84Fnj5aKdTdakssED6b/9UTTyunHJcvMVJ3pOtn4zpuuZYPOvdwKStkLMz0Ge3v9bP7hG5ly4kH+ASVnxoimW8yYZ7+dfnRCQClI8VHUN8h+0uWJmWtq6pnHyMyr/+YbUHJu3zZ9qpV31q1XORf7TreaoNL0i890BZRcGU333jApUy9t4TLnrhsTA0qenTeZVm1zHr3bszS6a6rZtJRyBZQ8rZLqn3hA5j37RML+Uy3Qser67ne4K8vcx+93zdsz87QbtCNpy6hsbRzF5Wwy0/OeswOiYAQQ6NYCtFTq1qeHg0MAAQQQ6DSBEvN3Fh3DxvHX/bT7NgNla6p/2gyUra0UkqTKDTeV6i13kI6WZjNWzz/jf+H2Zp/39D+ldo/9pNdKq3pXhZrXrh1lw5YJtU3QzLmqa67KTVev6u12lV6rrmm6D82SeS/8a1H3GJ+NtMWQDghdscrq1rmcZVov2d27KjfaXEoHLO2zVfJF2kpl1g2j411oNGcv01Wr/5EnS+nQ4dI2ZbLU3Xm91cJH12lgoX7MQ6LjeOlYS4Mvu1l+/dN+8e5NGtTSIMWwu56U0v4DZN5LT0u952G932HHS/V2u2lxVsrmGJxlaDcrbwsdddXrUAc6165w8199XjrmzbU3y+qzuLaP9D/qFKuMec8/6WrxtJRpBeVMammnKOprl+X3OfCMC61uTtoF0K6rHmu/Q4+3sjsDgXMevF0Wvv8/VzGlw0eKdk0s7tVLNHDZOP5dV+Cs/p/3StW6G4u2dkmWWkyAT1OxuQa09ZwGr+a/8ozVJbfYjO9kuyXb3rk8Mi/T3azSBEH1R7tjLnjrlfh1q/tb8PIz0v9Q0xVycdL9RnlNFdf2NS29LjbdK01Lr+IimWW6KM9/6Sl7d9b4d7W7J3ZLjGfwmajeYQ+p+8cN0jF3trVWx8rTlzLoixjs1PTtF9L89ef2rJQtu4LVmqnNMeaWdsULYxMvLIcTkZ33HB4jRSOAQPcSIKjUvc4HR4MAAggg0EUCOtjy8q99ag3a3PDeWzL9vJN9j2TI1f+QyvVHWet0AFxN+vawZKnavC1u6b9dHe+KVrvzH61ggLY+8UsLzV/WQwWVzF/e9WFUxwrpmG+6BplUs+OefkVHsixXdc1VuakqPejK26R6023iWWpMwGXKiQcmbTnS+O6bVlCpuHe1jHzyDZn/nxesYJKOrRU26QDhViuKxRtqAGbozQ/Fx5fRh1MNQkw+dFcrwKTZtDtRH9NCQgd114GXh15zp/x67L7SYVqFaNLWbtPOPk76H3eGaQFzvrXM/qe3CWrq2E/OlO0xaFnzX31Wmr8035vFSccCGjz6xoSuWv2PPUPq//2wlJkufNkmfZta3/2PsIpp+fHbJUEl8x22l/vtI4r6+pVrL6vdfT9rcoG5LpoXB9BKh4xIOCYNNsy5/zZ7M2sw836Hnyga9HMOzq6BxBlXX2CCT2PjeadfeZ4s8/ALKQfeLjVvLxx684NWV0ndsN8BR1lBGg1s6yDVQVM2XvY+dLD7wVfcKhW/W8NeJP0OPlZ+3tV01Vzc8q71t0nxdToR5TWlQcUh190t5SOWi+9j4DmXyULTXbNt8i/WMu0aqMGuVONWxTdePKFv3uyz5wHmPN4aX1X/xIOuscrmjXk4vk4n+u5zqGs+ExtXATmayea8+71wIkeHSbEIINCNBIq70bFwKAgggAACCHSpQFFZmfWmpOKyRcEi34MxDxMaTLIDSppHxwJKlvofe1o8oKR59MGl/6F/SpbdGtA26UrPihIztsywu8bIyEdflmVfeF+WOuFs0YBH9dY7eXJGN5uruuaq3FQ177Xcyq7V5SusLH1SDLjdNmNaPH+Jaf3Q17y1Twc+1tY4YZO+RdCZBpx+YTygZC/XQKc+gNtJg4YaaLCTtkYbcqV5qDXXrZ2aTcBi6mmHi5gBgu1UblpXLX3+Va7rUNdFcQzafcmZ+h9xUkJASdcXV1VZdanebFtn9k6djqK+URywBp2cLbv67HWwaUF0siugpPspHTREhlx1u5Sv9Lv4bvUlAA3vvhWf95tY6uRz4gElXV/Sr781Jlf1trv4ZU+6LBuv4l6VogH14ff82xVQ0p3pPdBqNWTv2bQO1dYxdorymup32AmugJLuQwMfOvi5M2mXtLCp9o8Hur57815+2nq7nZbTblow6XhKdtIWa9q6SVM2NnZ5ufzM5rzn8rgoGwEEuq9A+N+Cum9dODIEEEAAAQQ6XUDf7tO6+A1L3p2XDBjoeriz1/dafR17MuEzVXDFldmM6zH44husljO6XN9gpF2j9CdXKVd1zVW5mThoACZZak8ymHSy/KmW60DFzqTd6fyS99pqnTJRyhxduirWWE8GmYG3rXF0fArQa3DIlbdbb6nzro7iGFocg21rK5g+5o1e3TVFUd8o6ubsElWkQeZjT09arLZcGnjmxTLFdHW0k7bOksUBCnuZ/annO9M3vNll2J/Zeg26IHGMOA226CD3rutaW3yawavFBHs0dcY1VTZ4qF1N69NvoHRXBp8Z7WZaYwJn8023WSs1LbTGZ+p30DGiA4TbLbF0nb7lTt8UqUkDrJnaWAXk+J9sz3uOD4/iEUCgGwoQVOqGJ4VDQgABBBDoOQIdjQtcrQ6cR15UUeWcjU8XVS56uIgvcEwEfb11b9Pio2KNdR1b5n4yV3XNVbmZiJTom52SpCLzMBhVavEEIps+fj9Q0W1TTFchz1umdJyklok/u7ri2IUNNgGlUtMFyS9FcQytZtBsO5Utu2JGrbbs7XP9GUV9sz1GbZHT9O2X8WLKV1jFCjLEF/hM9NKuYxp4WdxdTAdGT5bKllkh2arQy6Py0jo3vPGSNWbZwo/eS7xfar0cLZU65ZrytC6MhRlLzyHZd9/DlwSVzPJ6MzB3330OM2PnPboklwb89zpoybxjKqyNY9OcTUZ13nN2gBSMAALdToCgUrc7JRwQAggggEBPEtBBYK3uR47uRvbx62C7OlCud5wJfY110uR52EmWrzZFN61k22S7PFd1zVW5mdS33Qx4nSxZrxJPtjLs8o521xZBx8EqX35l13b2jA4C75fscbb81kkEx9BhWmfYKWhA1M7f6Z8R1DfrY9YWOeaV9nayW6/Y836fev/QMXw6FgeV2k0XuGSppG+/ZKvCL4/Aq9EMRl53+zXS8uN3S/av3TV97pd2hp50TWmX2coNRslCM6i6pnbTRXb6ZX9xdVPtbbrIlg5yt4zSvJnY6HY5TxGc95wfIztAAIFuJUBQqVudDg4GAQQQQKCnCejrpUvN2Eb6tq6E1Nxk/YVe34TlTPNf/Ldz1jVdZsoKksp8HlKCbJdNnlzVNVflZlLXBWZclGTJOdhvsjxBl5cOcFwzpovTgLMvsQIHQbd35tOxXLxverPXTzv/ZBl+22OiD7/eFMUxlI9cLv6GOme3Je++EuZN6w1n0oGSc52iqG+2x6gBorJl1rMMvQAAQABJREFUlosPLt4y8ae0RbbNmukaPN4vQJG2kAwyZOs1z9znZl5+bnzP+vY5HUhd37Q297H7ZK55S55fyvia8iusE5b13e+IeFBJd9fw+pKxlHS+776JXUIztdHyUqYIvlfZnveUx8dKBBDISwH3/+h5WUUqhQACCCCAQG4FKtf/Q9IdzLz5CmlyvFZaAwDznnkiaf6qjTZNuq47rMhVXXNVbiqzBW++JDqek53mvfS0Nd6LPe/9LDevBI8qlY0YuaQo0/Vm3r8d3WWWrEk71fTVpzLzKveb3pwbxRoa5Lczj5Y2n/GgojiGctPlzU4d5o1n855Lfm3b+fRTB5R3pnbna9adK9JNOx+iTQugZC22tJgo6pvucIKs77XyavFs2rJF33aWKs156HbX6sq1N3DN52omG6/2+fUy68ZL44dWagJpyzz0gjVYuw5ynyplek2lKjOX6yo32kzKktwbdIw2fbOjM2Vj4yzHbzqK71U2593vmFiGAAL5L0BQKf/PMTVEAAEEEMixQO1ueyfdQ8fsWTLl2H3k5502kJ93GyUzL/2Lq/uLc8Pimlqp2mJ756JuN52ruuaq3FSAs++4Tn7Za0uZdtHpMuWEA2Wm6baSLOlDcaVjLCNtWdM4/h1pyzAYUr3Nzq5d1d15vTR+NM61zJ7RwNfcMQ/JxL22klZHizh9E9zUc05wdSXq9fu1Zfh9T4teS3ZqN90wp551jHlteqO9yPqM4hh6rewe2LzulqvMW+U+du3HOWMHfUo8r7a3xtpxZjTT+vCdqlWfld35pkbT1bTpsw9dpcRMdzP90RRFfV2FZzhTudb6ri1n3TBamr76zLXMnrGC0P96xJ61PjsrqJSNlw5GrgFNO9Xu/EfrLXT2fKrPTK+pVGXmcp22tNSxlfxSn70PTVicjU1CYZ4FUXyvsjnvnsNhFgEECkSA7m8FcqKpJgIIIIBA7gQqzEC6+vrsBSlaHKQc22bxoS11wlkZd4HKXe3cJeeqrrkq1330iXMa9GvQV7ynSUsddUp8bCwNAPx22uESW2iCNKVlMui8K8XbxTFNcVK53iaiAzA3f/vFoqxmvJyppx4m1TvuKb1Ny4di82aptmlTrDdhNbz5sjWtGWPNi8Yw0nFnpp5zvHQ4glolpuvk4MtvFX0r1eArbpPf/nxEPODU8sO3Mu1vp8qQq++I1yPbY9Djqf2/A6T+349I29RfdVY6zJhUU44/QGpMEKHK1KN0yHDRFkxNpp4LXn3eesPXMg89LyWmK1SJGUBcA16amo3p3Cfulz5mkGMd66n5my9k5jUXSstPjrF4rJzuf0r7LeVaMPveW6xBn0uXHiJNn34gc0w3Kx3TZoD5bkVRX9fOMpzRN4HNe+kpaf7yU6sEvTdMOW4/qTHdwqpM4LJ0qYHSajwXmOuy8d23XHvpve0uUvH75G+PdGXOciYbr4559a69t/46MT7fYb43CcE/08qszbTaKh00OONrKr6DLpio3nEPqbvzBukwb7ezU7G5NmvM+fKmbGy8ZXnno/heZXPevcfDPAIIFIYAQaXCOM/UEgEEEEAgxwIDzZg4LRO+cw9IG2KfNbvtI7W77Rtii67Lmqu65qrcbKUq1t1Iem+9U7yYec88tiigpEvMw/Dcx+8PHVTSQa0HX/MPK5jgHI9Lx3RKNa6T7lLfGDVj9NlmLKNvdHZR6lUh1pveTEBJk7ZmGXTeVTLdtMKy08L3x8rM6y6Spc8ebS3K5hjsMnWg6YGmvKkawHIkbWHk18qodNCQeK7qrXeW+sfvi8/X3XSF1P3jBisoJEkGHo9nXjyh50buvzW+uNm0kpp6+lHxeWuipcn6iKK+7oIzm9NxlZY+/2qZfPgeIvZA5+aczn/mcesnWamlw0bI0mddkmx15Muz8SodubzreOY/P0Zaf5ss2rVNA2UaMHWmX4/eS1rNGxGH3HCfVK23ccbXlLPMzpzWgdT77HmA6w2MOl+kg5J7UjY2vVZcxVNa4my236tsznvi0bAEAQQKQYDub4VwlqkjAggggEDOBfThetjtj4kGh0Il86rwpU4733qICrVdF2bOVV1zVW42VLV/PEiGXn+vaBeXeHKO4xNfGH5CW9kMue4e0QGMg6Sy5VaS4j79ZM49N0vDf191bTLo/KukwjFWj66sNq0k+h9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"
-    }
-   },
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<div>\n",
-    "<img src=\"attachment:Strings-2.png\" width=\"600\"/>\n",
-    "</div>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -81,7 +67,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/677413304.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mday\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# last\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mday\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# 2nd last\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mday\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m50\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# this won't work\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "Input \u001b[0;32mIn [2]\u001b[0m, in \u001b[0;36m<cell line: 8>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28mprint\u001b[39m(day[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]) \u001b[38;5;66;03m# last\u001b[39;00m\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28mprint\u001b[39m(day[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m2\u001b[39m]) \u001b[38;5;66;03m# 2nd last\u001b[39;00m\n\u001b[0;32m----> 8\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mday\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m50\u001b[39;49m\u001b[43m]\u001b[49m)\n",
       "\u001b[0;31mIndexError\u001b[0m: string index out of range"
      ]
     }
@@ -212,7 +198,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/571427960.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# the 2nd variable must be defined\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;31m# 2nd var b undefined\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "Input \u001b[0;32mIn [6]\u001b[0m, in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# the 2nd variable must be defined\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;66;03m# 2nd var b undefined\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m \u001b[43mb\u001b[49m: \n\u001b[1;32m      4\u001b[0m     \u001b[38;5;28mprint\u001b[39m(a)\n",
       "\u001b[0;31mNameError\u001b[0m: name 'b' is not defined"
      ]
     }
@@ -391,7 +377,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/3200803703.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;31m# TODO: discuss why the following gives IndexError\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgrocery_list\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgrocery_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     17\u001b[0m \u001b[0;31m# last possible index is always 1 value lesser than length\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "Input \u001b[0;32mIn [12]\u001b[0m, in \u001b[0;36m<cell line: 16>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[38;5;28mprint\u001b[39m(grocery_list[\u001b[38;5;241m2\u001b[39m:\u001b[38;5;241m4\u001b[39m])\n\u001b[1;32m     15\u001b[0m \u001b[38;5;66;03m# TODO: discuss why the following gives IndexError\u001b[39;00m\n\u001b[0;32m---> 16\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mgrocery_list\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mgrocery_list\u001b[49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m)\n",
       "\u001b[0;31mIndexError\u001b[0m: list index out of range"
      ]
     }
@@ -696,11 +682,20 @@
    ]
   },
   {
+   "attachments": {
+    "Mutability.png": {
+     "image/png": 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"
+    }
+   },
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "### Difference 2: lists are mutable\n",
     "\n",
+    "<div>\n",
+    "<img src=\"attachment:Mutability.png\" width=\"600\"/>\n",
+    "</div>\n",
+    "\n",
     "- Mutability has nothing to do with variable assignments / re-assignments\n",
     "- Mutability has to do with changing values inside a sequence"
    ]
@@ -744,7 +739,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/719601015.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# TODO: let's try to change \"Andrew\" to \"Andrea\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mname\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"a\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;31m# doesn't work because strings are immutable, that is you cannot change the value inside an existing string\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "Input \u001b[0;32mIn [23]\u001b[0m, in \u001b[0;36m<cell line: 4>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m name \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAndrew\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;66;03m# TODO: let's try to change \"Andrew\" to \"Andrea\"\u001b[39;00m\n\u001b[0;32m----> 4\u001b[0m name[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
       "\u001b[0;31mTypeError\u001b[0m: 'str' object does not support item assignment"
      ]
     }
@@ -808,7 +803,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/619664973.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# TODO: try to add \"blueberries\" at index 5\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mgrocery_list\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"blueberries\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;31m# doesn't work because grocery_list does not contain a previous item at index 5\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "Input \u001b[0;32mIn [25]\u001b[0m, in \u001b[0;36m<cell line: 4>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m grocery_list \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapples\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmilk\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbroccoli\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mspinach\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moranges\u001b[39m\u001b[38;5;124m\"\u001b[39m] \n\u001b[1;32m      3\u001b[0m \u001b[38;5;66;03m# TODO: try to add \"blueberries\" at index 5\u001b[39;00m\n\u001b[0;32m----> 4\u001b[0m grocery_list[\u001b[38;5;241m5\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mblueberries\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
       "\u001b[0;31mIndexError\u001b[0m: list assignment index out of range"
      ]
     }
@@ -865,7 +860,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/161169733.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mgrocery_list\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"peanut butter\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"jelly\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"bread\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;31m# doesn't work because append only accepts a single argument\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "Input \u001b[0;32mIn [27]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mgrocery_list\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mappend\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpeanut butter\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mjelly\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mbread\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
       "\u001b[0;31mTypeError\u001b[0m: list.append() takes exactly one argument (3 given)"
      ]
     }
@@ -1084,7 +1079,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m/var/folders/k6/kcy8b4f57hx9f1wh4sbs8mn40000gn/T/ipykernel_20561/4220427818.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mL\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m\"str\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2.0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mL\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Doesn't work as you cannot compare different types!\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "Input \u001b[0;32mIn [36]\u001b[0m, in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m L \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstr\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2.0\u001b[39m, \u001b[38;5;28;01mFalse\u001b[39;00m]\n\u001b[0;32m----> 2\u001b[0m \u001b[43mL\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msort\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
       "\u001b[0;31mTypeError\u001b[0m: '<' not supported between instances of 'int' and 'str'"
      ]
     }
@@ -1172,71 +1167,68 @@
      "data": {
       "text/plain": [
        "['Engineering: Biomedical',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Biomedical',\n",
+       " 'Engineering: Mechanical',\n",
+       " 'Engineering: Mechanical',\n",
+       " 'Engineering: Mechanical',\n",
        " 'Engineering: Industrial',\n",
        " 'Engineering: Other',\n",
-       " 'Engineering: Biomedical',\n",
+       " 'Engineering: Industrial',\n",
+       " 'Engineering: Mechanical',\n",
+       " 'Engineering: Mechanical',\n",
+       " 'Engineering: Mechanical',\n",
        " 'Engineering: Mechanical',\n",
        " 'Engineering: Biomedical',\n",
+       " 'Engineering: Mechanical',\n",
        " 'Engineering: Other',\n",
-       " 'Engineering: Biomedical',\n",
        " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
        " 'Engineering: Mechanical',\n",
        " 'Engineering: Industrial',\n",
+       " 'Engineering: Industrial',\n",
        " 'Engineering: Mechanical',\n",
        " 'Engineering: Mechanical',\n",
        " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Biomedical',\n",
        " 'Engineering: Biomedical',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Other',\n",
+       " 'Engineering: Mechanical',\n",
+       " 'Engineering: Industrial',\n",
        " 'Engineering: Mechanical',\n",
        " 'Engineering: Mechanical',\n",
-       " 'Engineering: Other',\n",
        " 'Engineering: Biomedical',\n",
-       " 'Engineering: Industrial',\n",
        " 'Engineering: Biomedical',\n",
-       " 'Engineering: Mechanical',\n",
        " 'Engineering: Biomedical',\n",
        " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
+       " 'Engineering: Mechanical',\n",
        " 'Engineering: Biomedical',\n",
-       " 'Engineering: Industrial',\n",
+       " 'Engineering: Mechanical',\n",
+       " 'Engineering: Mechanical',\n",
+       " 'Engineering: Mechanical',\n",
        " 'Engineering: Biomedical',\n",
        " 'Engineering: Mechanical',\n",
+       " 'Engineering: Other|Civil- Intelligent Transportation System',\n",
+       " 'Engineering: Mechanical',\n",
        " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
        " 'Engineering: Mechanical',\n",
        " 'Engineering: Biomedical',\n",
        " 'Engineering: Industrial',\n",
+       " 'Engineering: Biomedical',\n",
+       " 'Engineering: Biomedical',\n",
+       " 'Engineering: Mechanical',\n",
+       " 'Engineering: Mechanical',\n",
        " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
        " 'Engineering: Other',\n",
        " 'Engineering: Industrial',\n",
        " 'Engineering: Biomedical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Mechanical',\n",
+       " 'Engineering: Biomedical',\n",
+       " 'Engineering: Biomedical',\n",
        " 'Engineering: Mechanical',\n",
        " 'Engineering: Biomedical',\n",
        " 'Engineering: Industrial',\n",
-       " 'Engineering: Industrial',\n",
        " 'Engineering: Mechanical',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
-       " 'Engineering: Other',\n",
-       " 'Engineering: Other',\n",
        " 'Engineering: Mechanical',\n",
-       " 'Engineering: Industrial',\n",
        " 'Engineering: Mechanical',\n",
+       " 'Engineering: Other',\n",
+       " 'Engineering: Biomedical',\n",
        " 'Engineering: Mechanical',\n",
-       " 'Engineering: Mechanical']"
+       " 'Engineering: Industrial']"
       ]
      },
      "execution_count": 39,
@@ -1249,7 +1241,7 @@
     "\n",
     "for idx in range(project.count()):\n",
     "    lecture = project.get_lecture(idx)\n",
-    "    major = project.get_primary_major(idx)\n",
+    "    major = project.get_major(idx)\n",
     "    \n",
     "    if lecture == \"LEC001\":\n",
     "        if major.startswith(\"Engineering\"):\n",
@@ -1391,7 +1383,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.9.12"
   }
  },
  "nbformat": 4,
diff --git a/f22/meena_lec_notes/lec-14/lec_14_lists_template.ipynb b/f22/meena_lec_notes/lec-14/lec_14_lists_template.ipynb
index 01edaa76087499dd816600b07351b59b4a79b4ef..ff9fdbb4cfb00273ba74801713b56e539e9e3cca 100644
--- a/f22/meena_lec_notes/lec-14/lec_14_lists_template.ipynb
+++ b/f22/meena_lec_notes/lec-14/lec_14_lists_template.ipynb
@@ -32,20 +32,6 @@
     "- `for` loop"
    ]
   },
-  {
-   "attachments": {
-    "Strings-2.png": {
-     "image/png": 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"
-    }
-   },
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<div>\n",
-    "<img src=\"attachment:Strings-2.png\" width=\"600\"/>\n",
-    "</div>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -183,13 +169,12 @@
     "phrase = \"National Collegiate Athletic Association 2022\"\n",
     "acro = \"\"\n",
     "for letter in phrase:\n",
-    "    if letter.upper() == letter:\n",
+    "    if ???:\n",
     "        print(letter)\n",
     "        # How can we make sure you don't consider spaces and numbers?\n",
     "        # TODO: try isalpha method (update if condition)\n",
     "        # TODO: now instead of printing the letter, concatenate the letter to acro\n",
     "        \n",
-    "        \n",
     "print(acro)"
    ]
   },
@@ -464,11 +449,20 @@
    ]
   },
   {
+   "attachments": {
+    "Mutability.png": {
+     "image/png": 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"
+    }
+   },
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "### Difference 2: lists are mutable\n",
     "\n",
+    "<div>\n",
+    "<img src=\"attachment:Mutability.png\" width=\"600\"/>\n",
+    "</div>\n",
+    "\n",
     "- Mutability has nothing to do with variable assignments / re-assignments\n",
     "- Mutability has to do with changing values inside a sequence"
    ]
@@ -867,7 +861,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.9.12"
   }
  },
  "nbformat": 4,
diff --git a/f22/meena_lec_notes/lec-14/project.py b/f22/meena_lec_notes/lec-14/project.py
index 35c611668f3b88410f66d885868b7acd212fb693..ad671f7760f3b5b7b348e0d7226edbbe5dc777c0 100644
--- a/f22/meena_lec_notes/lec-14/project.py
+++ b/f22/meena_lec_notes/lec-14/project.py
@@ -5,7 +5,7 @@ def __init__():
     import csv
     """This function will read in the csv_file and store it in a list of dictionaries"""
     __student__.clear()
-    with open('cs220_survey_data.csv', mode='r') as csv_file:
+    with open('cs220_survey_data.csv', mode='r', encoding='utf-8') as csv_file:
         csv_reader = csv.DictReader(csv_file)
         for row in csv_reader:
             __student__.append(row)
@@ -26,28 +26,30 @@ def get_age(idx):
     return __student__[int(idx)]['Age']
 
 
-def get_primary_major(idx):
-    """get_primary_major(idx) returns the primary major of the student in row idx"""
-    return __student__[int(idx)]['Primary major']
-
-
-def get_other_majors(idx):
-    """get_other_majors(idx) returns the secondary major of the student in row idx"""
-    return __student__[int(idx)]['Other majors']
+def get_major(idx):
+    """get_major(idx) returns the major of the student in row idx"""
+    return __student__[int(idx)]['Major']
 
 
 def get_zip_code(idx):
     """get_zip_code(idx) returns the residential zip code of the student in row idx"""
     return __student__[int(idx)]['Zip Code']
 
+def get_latitude(idx):
+    """get_latitude(idx) returns the latitude of the student's favourite place in row idx"""
+    return __student__[int(idx)]['Latitude']
+
+def get_longitude(idx):
+    """get_longitude(idx) returns the longitude of the student's favourite place in row idx"""
+    return __student__[int(idx)]['Longitude']
 
-def get_pizza_topping(idx):
+def get_piazza_topping(idx):
     """get_piazza_topping(idx) returns the preferred pizza toppings of the student in row idx"""
     return __student__[int(idx)]['Pizza topping']
 
 def get_pet_owner(idx):
-    """get_pet_owner(idx) returns whether student in row idx is a pet owner"""
-    return __student__[int(idx)]['Pet owner']
+    """get_pet_owner(idx) returns the pet preference of student in row idx"""
+    return __student__[int(idx)]['Pet preference']
 
 def get_runner(idx):
     """get_runner(idx) returns whether student in row idx is a runner"""