From 6f6427137dc957e94bc5acb1dec38dfef8325451 Mon Sep 17 00:00:00 2001
From: Louis Oliphant <ltoliphant@wisc.edu>
Date: Wed, 9 Oct 2024 07:46:03 -0500
Subject: [PATCH] finished Lec 15

---
 .../15_CSVs/Lec_15_CSVs.ipynb                 |  280 +-
 .../15_CSVs/Lec_15_CSVs_Solution.ipynb        | 5523 +++++++++++++++++
 .../Lec_15_CSVs_Solution_Oliphant.ipynb       |  649 --
 f24/Louis_Lecture_Notes/15_CSVs/colors.csv    |  146 +
 4 files changed, 5805 insertions(+), 793 deletions(-)
 create mode 100644 f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs_Solution.ipynb
 delete mode 100644 f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs_Solution_Oliphant.ipynb
 create mode 100644 f24/Louis_Lecture_Notes/15_CSVs/colors.csv

diff --git a/f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs.ipynb b/f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs.ipynb
index b3aff24..b92b72b 100644
--- a/f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs.ipynb
+++ b/f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs.ipynb
@@ -9,110 +9,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['peanut butter']\n",
-      "['peanut butter', 'bread', 'jelly', 'cheese', 'pickle']\n",
-      "['peanut butter', 'jelly', 'cheese', 'pickle']\n",
-      "['peanut butter', 'jelly', 'pickle']\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Warmup 0: Mutating a list\n",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup 1: Mutating a list\n",
     "\n",
     "my_groceries = []\n",
     "\n",
     "#use .append() to add an item to the end of a list\n",
-    "my_groceries.append(\"peanut butter\")\n",
+    "\n",
     "print(my_groceries)\n",
     "\n",
     "#use .extend() to add *ALL* items from one list to another list\n",
-    "my_groceries.extend([\"bread\",\"jelly\",\"cheese\",\"pickle\"])\n",
-    "print(my_groceries)\n",
     "\n",
-    "#use .pop() to remove an item at a specific index\n",
-    "my_groceries.pop(1)\n",
     "print(my_groceries)\n",
     "\n",
-    "#use .remove() by matching a value\n",
-    "my_groceries.remove(\"cheese\")\n",
-    "print(my_groceries)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Warmup 0: Write a program that manages a grocery list!\n",
-    "# A: Add an item. Ask the user to add an item to their list.\n",
-    "# D: Delete an item. Ask the user what to remove from their list.\n",
-    "# P: Print the grocery list.\n",
-    "# Q: Quit.\n",
+    "#use .pop() to remove an item at a specific index\n",
     "\n",
-    "my_groceries = []\n",
+    "print(my_groceries)\n",
     "\n",
-    "while True:\n",
-    "    choice = input(\"What do you want to do? (A, D, P, Q): \")\n",
-    "    \n",
-    "    # TODO_0: There's a bug... Fix this.\n",
-    "    choice.upper()\n",
-    "    if choice == 'A':\n",
-    "        # TODO_3: Prompt the user to enter in a food and add it to the list.\n",
-    "        pass\n",
-    "    elif choice == 'D':\n",
-    "        # TODO_4: Prompt the user to enter in a food and remove it from the list.\n",
-    "        pass\n",
-    "    elif choice == 'P':\n",
-    "        # TODO_2: Print the user's list.\n",
-    "        pass\n",
-    "    elif choice == 'Q':\n",
-    "        # TODO_1: Quit the program\n",
-    "        pass\n",
-    "    else:\n",
-    "        print('I don\\'t understand. Please try again!')\n",
-    "        \n",
-    "print('Thanks for shopping!')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Warmup #1: Profanity Filter\n",
+    "#use .remove() by take out a value\n",
     "\n",
-    "def profanity_filter(sentence, bad_words):\n",
-    "    ''' replaces all instances of any word in bad_words with\n",
-    "    a word with the first letter from the profanity and the rest of the characters\n",
-    "    using @ with the same length as the profanity'''\n",
-    "    \n",
-    "    sentence_split = sentence.split(\" \")\n",
-    "    cleaned_sentence = []\n",
-    "    \n",
-    "    for word in sentence_split:\n",
-    "        # TODO We need to improve this! Extra practice!\n",
-    "        if word in bad_words:\n",
-    "            cleaned_word = word[0] + \"@\" * (len(word) - 1) \n",
-    "            cleaned_sentence.append(cleaned_word)  \n",
-    "        else:\n",
-    "            cleaned_sentence.append(word)\n",
-    "    # all done cleaning, now join and return\n",
-    "    return \" \".join(cleaned_sentence)\n",
-    "    \n",
-    "    \n",
-    "bad_word_list = [\"darn\", \"heck\", \"crud\", \"exam\"]\n",
-    "print(profanity_filter(\"I unplugged that darn Alexa\", bad_word_list))\n",
-    "print(profanity_filter(\"What the heck was my boss thinking?\", bad_word_list))\n",
-    "print(profanity_filter(\"He is full of crud?\", bad_word_list))"
+    "print(my_groceries)"
    ]
   },
   {
@@ -125,8 +44,7 @@
     "# https://www.w3schools.com/python/python_ref_list.asp\n",
     "dairy = [\"milk\", \"ice cream\", \"cheese\", \"yogurt\" ]\n",
     "\n",
-    "#use the .index() method to get the index of \"ice cream\"\n",
-    "\n"
+    "#use the .index() method to get the index of \"ice cream\"\n"
    ]
   },
   {
@@ -138,7 +56,7 @@
     "# Warmup #3:  Because a list is a sequence, we can use the 'in' operator\n",
     "food_shelf = [\"peanut butter\", \"milk\", \"bread\", \"cheese\", \"YOGURT\"]\n",
     "for item in food_shelf:\n",
-    "    if ???:\n",
+    "    if ???:  # see if item.lower() is in the dairy list\n",
     "        print(item, \"is dairy\")\n",
     "    else:\n",
     "        print(item, \"is not dairy\")"
@@ -173,12 +91,32 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Reading a CSV"
+    "## CSV File Format\n",
+    "\n",
+    "CSV file format is a non-propriatary format for sharing tables of data.  The data in the CSV file is contained in rows with the values in the rows separated by commas.  It is very common (though not required) to have the top row of a CSV file contain the the header names for the columns of data:\n",
+    "\n",
+    "```\n",
+    "Animal,Country,Population\n",
+    "panda, China,1864\n",
+    "lemur,Madagascar,2500\n",
+    "macaque,India,100000\n",
+    "```\n",
+    "\n",
+    "You can open CSV files using a spreadsheet program like Microsoft Excel or Apple Numbers.  With Jupyter Lab you can open a CSV file for viewing by doubule-clicking on the file name within Jupyter.  If you want to open it for editing then you need to right-click on the file name and select *Open With -> Editor* in the context menu which will open the file in a text editor."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Reading a CSV in Python\n",
+    "\n",
+    "Python has a module for working with CSV files called `csv`.  One common approach for reading in all the data from a CSV file is to load the data as a list of lists.  Look at the function defined in the cell below which takes a file name, loads the data from the file using methods from the csv module and returns a list of lists."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -204,51 +142,68 @@
     "    return exampleData\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finish the code in the cell below by useing the `process_csv()` function to load the `colors.csv` file as a list of lists and store the data in the `colors` variable then print the loaded data.  Open the colors.csv file in a separate tab to see data in a spreadsheet type layout and compare what you see in Jupyter Lab with the content on that tab."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Call the process_csv function and store the list of lists in cs220_csv\n",
-    "cs220_csv = process_csv('cs220_survey_data.csv')\n",
-    "cs220_csv"
+    "##TODO load the 'colors.csv' data and store and print the data\n",
+    "\n",
+    "colors = ...\n",
+    "\n",
+    "print(colors)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can use double indexing to access specific elements from the loaded data.  Recall that the first indexing will access the row and the second indexing will access the column within that row:\n",
+    "\n",
+    "```python\n",
+    "colors[3][0]\n",
+    "```\n",
+    "```\n",
+    "Aqua\n",
+    "```\n",
+    "```python\n",
+    "colors[3][2]\n",
+    "```\n",
+    "```\n",
+    "rgb(0,100,100)\n",
+    "```\n",
+    "\n",
+    "On web pages you can describe colors using the color's name, the color's hex value, or the color's rgb value.  The function defined in the cell below accepts any of these three ways of describing a color and displays a tiny swatch of that color."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Section',\n",
-       " 'Lecture',\n",
-       " 'Age',\n",
-       " 'Primary Major',\n",
-       " 'Other Primary Major',\n",
-       " 'Other Majors',\n",
-       " 'Zip Code',\n",
-       " 'Latitude',\n",
-       " 'Longitude',\n",
-       " 'Pizza Topping',\n",
-       " 'Cats or Dogs',\n",
-       " 'Runner',\n",
-       " 'Sleep Habit',\n",
-       " 'Procrastinator',\n",
-       " 'Song']"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Store the header row into cs220_header\n",
-    "cs220_header = cs220_csv[0]\n",
-    "cs220_header"
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from IPython.display import HTML\n",
+    "\n",
+    "def show_color(color):\n",
+    "    color=color.replace(' ','')\n",
+    "    color_html = '<div style=\"background-color: {}; width: 50px; height: 20px;\"></div>'.format(color)\n",
+    "    display(HTML(color_html)) \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Using Double Indexing\n",
+    "Finish the code in the cell below by calling `show_color()` with specific values from the `colors` variable."
    ]
   },
   {
@@ -257,16 +212,53 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Store all of the data rows into cs220_data\n",
-    "cs220_data = cs220_csv[1:]\n",
-    "cs220_data"
+    "## Display Blanched Almond (index 9) using its name (index 0)\n",
+    "print(colors[9][0])\n",
+    "show_color(colors[9][0])\n",
+    "\n",
+    "## Display Blue Violet (index 11) using the HEX value (index 1)\n",
+    "print(colors[11][1])\n",
+    "show_color(colors[11][1])\n",
+    "\n",
+    "## Display Khaki (index 61) using the rgb value (index 2)\n",
+    "print(...)\n",
+    "show_color(...)\n",
+    "\n",
+    "## You pick a color and display the color swatch using the name, HEX value, and rgb value\n",
+    "## also print the name, HEX value, and rgb value\n",
+    "\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## CSVs as a List of Lists"
+    "Now let's work with our survey data.  Finish the code in the cell below to load the data using the `process_csv()` function.  Then  divide the header row off from the data portion, and printer the header and the top 2 rows of the data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Call the process_csv function and store the list of lists in cs220_csv\n",
+    "cs220_csv = process_csv('cs220_survey_data.csv')\n",
+    "cs220_csv\n",
+    "cs220_header = ...\n",
+    "cs220_data = ...\n",
+    "\n",
+    "print(cs220_header)\n",
+    "print(...)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## CSVs as a List of Lists\n",
+    "\n",
+    "Finish the cells below to access and print the desired item.  Since the csv_data is a list of lists, you will need to use double indexing."
    ]
   },
   {
@@ -446,15 +438,6 @@
     "# Get the average age of each lecture..."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# What are the unique ages for each lecture?"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -495,6 +478,15 @@
    "source": [
     "# Does the oldest basil/spinach-loving Business major prefer cats, dogs, or neither?"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Summary\n",
+    "\n",
+    "The `csv` module can be used to load CSV files and store them as a list of lists.  Use double-indexing and helper functions to work with data in this format."
+   ]
   }
  ],
  "metadata": {
diff --git a/f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs_Solution.ipynb b/f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs_Solution.ipynb
new file mode 100644
index 0000000..e237773
--- /dev/null
+++ b/f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs_Solution.ipynb
@@ -0,0 +1,5523 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Warmup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Apples']\n",
+      "['Apples', 'milk', 'cheese']\n",
+      "['Apples', 'cheese']\n",
+      "['cheese']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Warmup 1: Mutating a list\n",
+    "\n",
+    "my_groceries = []\n",
+    "\n",
+    "#use .append() to add an item to the end of a list\n",
+    "my_groceries.append(\"Apples\")\n",
+    "\n",
+    "print(my_groceries)\n",
+    "\n",
+    "#use .extend() to add *ALL* items from one list to another list\n",
+    "\n",
+    "my_groceries.extend(['milk','cheese'])\n",
+    "print(my_groceries)\n",
+    "\n",
+    "#use .pop() to remove an item at a specific index\n",
+    "my_groceries.pop(1)\n",
+    "print(my_groceries)\n",
+    "\n",
+    "#use .remove() by take out a value\n",
+    "my_groceries.remove('Apples')\n",
+    "print(my_groceries)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Warmup #2: Take a look at these list methods \n",
+    "# https://www.w3schools.com/python/python_ref_list.asp\n",
+    "dairy = [\"milk\", \"ice cream\", \"cheese\", \"yogurt\" ]\n",
+    "\n",
+    "#use the .index() method to get the index of \"ice cream\"\n",
+    "dairy.index(\"ice cream\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "peanut butter is not dairy\n",
+      "milk is dairy\n",
+      "bread is not dairy\n",
+      "cheese is dairy\n",
+      "YOGURT is dairy\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Warmup #3:  Because a list is a sequence, we can use the 'in' operator\n",
+    "food_shelf = [\"peanut butter\", \"milk\", \"bread\", \"cheese\", \"YOGURT\"]\n",
+    "for item in food_shelf:\n",
+    "    if item.lower() in dairy:  # see if item.lower() is in the dairy list\n",
+    "        print(item, \"is dairy\")\n",
+    "    else:\n",
+    "        print(item, \"is not dairy\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Comma-Separated Values (CSV) Files\n",
+    "\n",
+    "## Readings\n",
+    "\n",
+    "- [Sweigart Ch 16 (through \"Reading Data from Reader Objects in a for Loop\")](https://automatetheboringstuff.com/2e/chapter16/)\n",
+    "\n",
+    "## Learning Objectives\n",
+    "\n",
+    "After this lecture you will be able to...\n",
+    "\n",
+    "- Open an Spreadsheet file and export it to a Comma Separated Value file.\n",
+    "- View a CSV file in Jupyter Lab's *CSV Viewer*.\n",
+    "- Open a CSV file in TextEditor/Jupyter and connect the elements of the CSV file to the rows and columns in the spreadsheet.\n",
+    "\n",
+    "- Use pre-written Python code to read a CSV file into a list of lists.\n",
+    "\n",
+    "- Write Python statements with double list indexing to access any element of a CSV file via a list of lists.\n",
+    "\n",
+    "- Write code that answers questions about CSV data by writing for loops on lists of lists.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## CSV File Format\n",
+    "\n",
+    "CSV file format is a non-propriatary format for sharing tables of data.  The data in the CSV file is contained in rows with the values in the rows separated by commas.  It is very common (though not required) to have the top row of a CSV file contain the the header names for the columns of data:\n",
+    "\n",
+    "```\n",
+    "Animal,Country,Population\n",
+    "panda, China,1864\n",
+    "lemur,Madagascar,2500\n",
+    "macaque,India,100000\n",
+    "```\n",
+    "\n",
+    "You can open CSV files using a spreadsheet program like Microsoft Excel or Apple Numbers.  With Jupyter Lab you can open a CSV file for viewing by doubule-clicking on the file name within Jupyter.  If you want to open it for editing then you need to right-click on the file name and select *Open With -> Editor* in the context menu which will open the file in a text editor."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Reading a CSV in Python\n",
+    "\n",
+    "Python has a module for working with CSV files called `csv`.  One common approach for reading in all the data from a CSV file is to load the data as a list of lists.  Look at the function defined in the cell below which takes a file name, loads the data from the file using methods from the csv module and returns a list of lists."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Now lets store the contents of the CSV file into Python lists\n",
+    "\n",
+    "# copied from https://automatetheboringstuff.com/chapter14/\n",
+    "import csv\n",
+    "\n",
+    "def process_csv(filename):\n",
+    "    # open the file, its a text file utf-8\n",
+    "    exampleFile = open(filename, encoding=\"utf-8\")  \n",
+    "    \n",
+    "    # prepare it for reading as a CSV object\n",
+    "    exampleReader = csv.reader(exampleFile) \n",
+    "    \n",
+    "    # use the built-in list function to convert this into a list of lists\n",
+    "    exampleData = list(exampleReader)        \n",
+    "    \n",
+    "    # close the file to tidy up our workspace\n",
+    "    exampleFile.close()  \n",
+    "    \n",
+    "    # return the list of lists\n",
+    "    return exampleData\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finish the code in the cell below by useing the `process_csv()` function to load the `colors.csv` file as a list of lists and store the data in the `colors` variable then print the loaded data.  Open the colors.csv file in a separate tab to see data in a spreadsheet type layout and compare what you see in Jupyter Lab with the content on that tab."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[['\\ufeffName', 'HEX', 'RGB'], ['Alice Blue', '#F0F8FF', 'rgb(239,247,255)'], ['Antique White', '#FAEBD7', 'rgb(249,234,214)'], ['Aqua', '#00FFFF', 'rgb(0,255,255)'], ['Aquamarine', '#7FFFD4', 'rgb(127,255,211)'], ['Azure', '#F0FFFF', 'rgb(239,255,255)'], ['Beige', '#F5F5DC', 'rgb(244,244,219)'], ['Bisque', '#FFE4C4', 'rgb(255,226,196)'], ['Black', '#000000', 'rgb(0,0,0)'], ['Blanched Almond', '#FFEBCD', 'rgb(255,234,204)'], ['Blue', '#0000FF', 'rgb(0,0,255)'], ['Blue Violet', '#8A2BE2', 'rgb(137,43,226)'], ['Brown', '#A52A2A', 'rgb(165,40,40)'], ['Burlywood', '#DEB887', 'rgb(221,183,135)'], ['Cadet Blue', '#5F9EA0', 'rgb(94,158,160)'], ['Chartreuse', '#7FFF00', 'rgb(127,255,0)'], ['Chocolate', '#D2691E', 'rgb(209,104,30)'], ['Coral', '#FF7F50', 'rgb(255,127,79)'], ['Cornflower Blue', '#6495ED', 'rgb(99,147,237)'], ['Cornsilk', '#FFF8DC', 'rgb(255,247,219)'], ['Crimson', '#DC143C', 'rgb(219,20,61)'], ['Cyan', '#00FFFF', 'rgb(0,255,255)'], ['Dark Blue', '#00008B', 'rgb(0,0,140)'], ['Dark Cyan', '#008B8B', 'rgb(0,140,140)'], ['Dark Goldenrod', '#B8860B', 'rgb(183,135,10)'], ['Dark Gray', '#A9A9A9', 'rgb(168,168,168)'], ['Dark Green', '#006400', 'rgb(0,99,0)'], ['Dark Khaki', '#BDB76B', 'rgb(188,183,107)'], ['Dark Magenta', '#8B008B', 'rgb(140,0,140)'], ['Dark Olive Green', '#556B2F', 'rgb(84,107,45)'], ['Dark Orange', '#FF8C00', 'rgb(255,140,0)'], ['Dark Orchid', '#9932CC', 'rgb(153,51,204)'], ['Dark Red', '#8B0000', 'rgb(140,0,0)'], ['Dark Salmon', '#E9967A', 'rgb(232,150,122)'], ['Dark Sea Green', '#8FBC8F', 'rgb(142,188,142)'], ['Dark Slate Blue', '#483D8B', 'rgb(71,61,140)'], ['Dark Slate Gray', '#2F4F4F', 'rgb(45,79,79)'], ['Dark Turquoise', '#00CED1', 'rgb(0,206,209)'], ['Dark Violet', '#9400D3', 'rgb(147,0,211)'], ['Deep Pink', '#FF1493', 'rgb(255,20,147)'], ['Deep Sky Blue', '#00BFFF', 'rgb(0,191,255)'], ['Dim Gray', '#696969', 'rgb(104,104,104)'], ['Dodger Blue', '#1E90FF', 'rgb(30,142,255)'], ['Firebrick', '#B22222', 'rgb(178,33,33)'], ['Floral White', '#FFFAF0', 'rgb(255,249,239)'], ['Forest Green', '#228B22', 'rgb(33,140,33)'], ['Fuchsia', '#FF00FF', 'rgb(255,0,255)'], ['Gainsboro', '#DCDCDC', 'rgb(219,219,219)'], ['Ghost White', '#F8F8FF', 'rgb(247,247,255)'], ['Gold', '#FFD700', 'rgb(255,214,0)'], ['Goldenrod', '#DAA520', 'rgb(216,165,33)'], ['Gray', '#BEBEBE', 'rgb(191,191,191)'], ['Web Gray', '#808080', 'rgb(127,127,127)'], ['Green', '#00FF00', 'rgb(0,255,0)'], ['Web Green', '#008000', 'rgb(0,127,0)'], ['Green Yellow', '#ADFF2F', 'rgb(173,255,45)'], ['Honeydew', '#F0FFF0', 'rgb(239,255,239)'], ['Hot Pink', '#FF69B4', 'rgb(255,104,181)'], ['Indian Red', '#CD5C5C', 'rgb(204,91,91)'], ['Indigo', '#4B0082', 'rgb(73,0,130)'], ['Ivory', '#FFFFF0', 'rgb(255,255,239)'], ['Khaki', '#F0E68C', 'rgb(239,229,140)'], ['Lavender', '#E6E6FA', 'rgb(229,229,249)'], ['Lavender Blush', '#FFF0F5', 'rgb(255,239,244)'], ['Lawn Green', '#7CFC00', 'rgb(124,252,0)'], ['Lemon Chiffon', '#FFFACD', 'rgb(255,249,204)'], ['Light Blue', '#ADD8E6', 'rgb(173,216,229)'], ['Light Coral', '#F08080', 'rgb(239,127,127)'], ['Light Cyan', '#E0FFFF', 'rgb(224,255,255)'], ['Light Goldenrod', '#FAFAD2', 'rgb(249,249,209)'], ['Light Gray', '#D3D3D3', 'rgb(211,211,211)'], ['Light Green', '#90EE90', 'rgb(142,237,142)'], ['Light Pink', '#FFB6C1', 'rgb(255,181,193)'], ['Light Salmon', '#FFA07A', 'rgb(255,160,122)'], ['Light Sea Green', '#20B2AA', 'rgb(33,178,170)'], ['Light Sky Blue', '#87CEFA', 'rgb(135,206,249)'], ['Light Slate Gray', '#778899', 'rgb(119,135,153)'], ['Light Steel Blue', '#B0C4DE', 'rgb(175,196,221)'], ['Light Yellow', '#FFFFE0', 'rgb(255,255,224)'], ['Lime', '#00FF00', 'rgb(0,255,0)'], ['Lime Green', '#32CD32', 'rgb(51,204,51)'], ['Linen', '#FAF0E6', 'rgb(249,239,229)'], ['Magenta', '#FF00FF', 'rgb(255,0,255)'], ['Maroon', '#B03060', 'rgb(175,48,96)'], ['Web Maroon', '#800000', 'rgb(127,0,0)'], ['Medium Aquamarine', '#66CDAA', 'rgb(102,204,170)'], ['Medium Blue', '#0000CD', 'rgb(0,0,204)'], ['Medium Orchid', '#BA55D3', 'rgb(186,84,211)'], ['Medium Purple', '#9370DB', 'rgb(147,112,219)'], ['Medium Sea Green', '#3CB371', 'rgb(61,178,112)'], ['Medium Slate Blue', '#7B68EE', 'rgb(122,104,237)'], ['Medium Spring Green', '#00FA9A', 'rgb(0,249,153)'], ['Medium Turquoise', '#48D1CC', 'rgb(71,209,204)'], ['Medium Violet Red', '#C71585', 'rgb(198,20,132)'], ['Midnight Blue', '#191970', 'rgb(25,25,112)'], ['Mint Cream', '#F5FFFA', 'rgb(244,255,249)'], ['Misty Rose', '#FFE4E1', 'rgb(255,226,224)'], ['Moccasin', '#FFE4B5', 'rgb(255,226,181)'], ['Navajo White', '#FFDEAD', 'rgb(255,221,173)'], ['Navy Blue', '#000080', 'rgb(0,0,127)'], ['Old Lace', '#FDF5E6', 'rgb(252,244,229)'], ['Olive', '#808000', 'rgb(127,127,0)'], ['Olive Drab', '#6B8E23', 'rgb(107,142,35)'], ['Orange', '#FFA500', 'rgb(255,165,0)'], ['Orange Red', '#FF4500', 'rgb(255,68,0)'], ['Orchid', '#DA70D6', 'rgb(216,112,214)'], ['Pale Goldenrod', '#EEE8AA', 'rgb(237,232,170)'], ['Pale Green', '#98FB98', 'rgb(153,249,153)'], ['Pale Turquoise', '#AFEEEE', 'rgb(175,237,237)'], ['Pale Violet Red', '#DB7093', 'rgb(219,112,147)'], ['Papaya Whip', '#FFEFD5', 'rgb(255,239,214)'], ['Peach Puff', '#FFDAB9', 'rgb(255,216,186)'], ['Peru', '#CD853F', 'rgb(204,132,63)'], ['Pink', '#FFC0CB', 'rgb(255,191,204)'], ['Plum', '#DDA0DD', 'rgb(221,160,221)'], ['Powder Blue', '#B0E0E6', 'rgb(175,224,229)'], ['Purple', '#A020F0', 'rgb(160,33,239)'], ['Web Purple', '#800080', 'rgb(127,0,127)'], ['Rebecca Purple', '#663399', 'rgb(102,51,153)'], ['Red', '#FF0000', 'rgb(255,0,0)'], ['Rosy Brown', '#BC8F8F', 'rgb(188,142,142)'], ['Royal Blue', '#4169E1', 'rgb(63,104,224)'], ['Saddle Brown', '#8B4513', 'rgb(140,68,17)'], ['Salmon', '#FA8072', 'rgb(249,127,114)'], ['Sandy Brown', '#F4A460', 'rgb(244,163,96)'], ['Sea Green', '#2E8B57', 'rgb(45,140,86)'], ['Seashell', '#FFF5EE', 'rgb(255,244,237)'], ['Sienna', '#A0522D', 'rgb(160,81,45)'], ['Silver', '#C0C0C0', 'rgb(191,191,191)'], ['Sky Blue', '#87CEEB', 'rgb(135,206,234)'], ['Slate Blue', '#6A5ACD', 'rgb(107,89,204)'], ['Slate Gray', '#708090', 'rgb(112,127,142)'], ['Snow', '#FFFAFA', 'rgb(255,249,249)'], ['Spring Green', '#00FF7F', 'rgb(0,255,127)'], ['Steel Blue', '#4682B4', 'rgb(68,130,181)'], ['Tan', '#D2B48C', 'rgb(209,181,140)'], ['Teal', '#008080', 'rgb(0,127,127)'], ['Thistle', '#D8BFD8', 'rgb(216,191,216)'], ['Tomato', '#FF6347', 'rgb(255,99,71)'], ['Turquoise', '#40E0D0', 'rgb(63,224,209)'], ['Violet', '#EE82EE', 'rgb(237,130,237)'], ['Wheat', '#F5DEB3', 'rgb(244,221,178)'], ['White', '#FFFFFF', 'rgb(255,255,255)'], ['White Smoke', '#F5F5F5', 'rgb(244,244,244)'], ['Yellow', '#FFFF00', 'rgb(255,255,0)'], ['Yellow Green', '#9ACD32', 'rgb(153,204,51)']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "##TODO load the 'colors.csv' data and store and print the data\n",
+    "\n",
+    "colors = process_csv('colors.csv')\n",
+    "\n",
+    "print(colors)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can use double indexing to access specific elements from the loaded data.  Recall that the first indexing will access the row and the second indexing will access the column within that row:\n",
+    "\n",
+    "```python\n",
+    "colors[3][0]\n",
+    "```\n",
+    "```\n",
+    "Aqua\n",
+    "```\n",
+    "```python\n",
+    "colors[3][2]\n",
+    "```\n",
+    "```\n",
+    "rgb(0,100,100)\n",
+    "```\n",
+    "\n",
+    "On web pages you can describe colors using the color's name, the color's hex value, or the color's rgb value.  The function defined in the cell below accepts any of these three ways of describing a color and displays a tiny swatch of that color."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from IPython.display import HTML\n",
+    "\n",
+    "def show_color(color):\n",
+    "    color=color.replace(' ','')\n",
+    "    color_html = '<div style=\"background-color: {}; width: 50px; height: 20px;\"></div>'.format(color)\n",
+    "    display(HTML(color_html)) \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Using Double Indexing\n",
+    "Finish the code in the cell below by calling `show_color()` with specific values from the `colors` variable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Blanched Almond\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"background-color: BlanchedAlmond; width: 50px; height: 20px;\"></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "#8A2BE2\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"background-color: #8A2BE2; width: 50px; height: 20px;\"></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "rgb(239,229,140)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"background-color: rgb(239,229,140); width: 50px; height: 20px;\"></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Dark Gray', '#A9A9A9', 'rgb(168,168,168)']\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"background-color: DarkGray; width: 50px; height: 20px;\"></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"background-color: #A9A9A9; width: 50px; height: 20px;\"></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"background-color: rgb(168,168,168); width: 50px; height: 20px;\"></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "## Display Blanched Almond (index 9) using its name (index 0)\n",
+    "print(colors[9][0])\n",
+    "show_color(colors[9][0])\n",
+    "\n",
+    "## Display Blue Violet (index 11) using the HEX value (index 1)\n",
+    "print(colors[11][1])\n",
+    "show_color(colors[11][1])\n",
+    "\n",
+    "## Display Khaki (index 61) using the rgb value (index 2)\n",
+    "print(colors[61][2])\n",
+    "show_color(colors[61][2])\n",
+    "\n",
+    "## You pick a color and display the color swatch using the name, HEX value, and rgb value\n",
+    "## also print the name, HEX value, and rgb value\n",
+    "print(colors[25])\n",
+    "show_color(colors[25][0])\n",
+    "show_color(colors[25][1])\n",
+    "show_color(colors[25][2])\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now let's work with our survey data.  Finish the code in the cell below to load the data using the `process_csv()` function.  Then  divide the header row off from the data portion, and printer the header and the top 2 rows of the data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Section', 'Lecture', 'Printed Copy', 'Age', 'Primary Major', 'Other Majors', 'Secondary Majors', 'Zip Code', 'Latitude', 'Longitude', 'Data Science Major', 'Pizza Topping', 'Cats or Dogs', 'Runner', 'Sleep Habit', 'Procrastinator', 'Song']\n",
+      "[['COMP SCI 220:LEC004, COMP SCI 220:LAB344', 'LEC004', 'No', '19', 'Engineering: Other', 'Engineering Mechanics', '', '53726', '44.39', '-89.83', 'No', 'none (just cheese)', 'dog', 'No', 'night owl', 'Maybe', 'Family Ties-Baby Keem'], ['COMP SCI 220:LEC004, COMP SCI 220:LAB341', 'LEC004', 'Yes', '18', 'Business: Finance', '', 'economics', '53706', '22.7626', '120.3652', 'Maybe', 'pineapple', 'dog', 'Yes', 'no preference', 'Yes', 'Singer: Haruno\\n\\nSong: Like a seraph']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Call the process_csv function and store the list of lists in cs220_csv\n",
+    "cs220_csv = process_csv('cs220_survey_data.csv')\n",
+    "cs220_csv\n",
+    "cs220_header = cs220_csv[0]\n",
+    "cs220_data = cs220_csv[1:]\n",
+    "\n",
+    "print(cs220_header)\n",
+    "print(cs220_data[:2])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## CSVs as a List of Lists\n",
+    "\n",
+    "Finish the cells below to access and print the desired item.  Since the csv_data is a list of lists, you will need to use double indexing."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'LEC001'"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Print out the lecture number of the 4th student...by hardcoding its row and column....\n",
+    "cs220_data[3][1] # [row][col]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'no preference'"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Print out the sleeping habit for the 2nd student...by hardcoding its row and column....\n",
+    "cs220_data[1][-3] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "935"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Print out how many students completed the survey.\n",
+    "len(cs220_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "night owl\t\tEngineering: Other\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tScience: Other\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tBusiness: Finance\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tScience: Other\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Other\n",
+      "no preference\t\tEngineering: Other\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Other\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tScience: Other\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "night owl\t\tBusiness: Finance\n",
+      "early bird\t\tStatistics\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tScience: Other\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Chemistry\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Finance\n",
+      "early bird\t\tStatistics\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Other\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tStatistics\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "no preference\t\tBusiness: Finance\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tStatistics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tScience: Other\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tScience: Other\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tBusiness: Other\n",
+      "no preference\t\tScience: Chemistry\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Other\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Other\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Other\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "night owl\t\tBusiness: Other\n",
+      "night owl\t\tBusiness: Other\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "no preference\t\tScience: Physics\n",
+      "early bird\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tStatistics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Other\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Information Systems\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tScience: Physics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Other\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tStatistics\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "no preference\t\tScience: Physics\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tScience: Other\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tBusiness: Other\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tStatistics\n",
+      "no preference\t\tStatistics\n",
+      "night owl\t\tScience: Other\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tComputer Science\n",
+      "no preference\t\tScience: Other\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Other\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "no preference\t\tStatistics\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Other\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tBusiness: Other\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Other\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tScience: Chemistry\n",
+      "early bird\t\tLanguages\n",
+      "no preference\t\tComputer Science\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tScience: Other\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tBusiness: Other\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tScience: Physics\n",
+      "early bird\t\tComputer Science\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tScience: Chemistry\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Other\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "no preference\t\tMathematics/AMEP\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tBusiness: Other\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tScience: Chemistry\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tStatistics\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tScience: Other\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Other\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "no preference\t\tEngineering: Other\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Other\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tBusiness: Finance\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Other\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tStatistics\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tStatistics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tStatistics\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "early bird\t\tScience: Other\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tBusiness: Other\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tBusiness: Actuarial\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Other\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "no preference\t\tComputer Science\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tScience: Other\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Other\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Other\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tScience: Other\n",
+      "no preference\t\tBusiness: Information Systems\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tStatistics\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tBusiness: Other\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tBusiness: Finance\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tStatistics\n",
+      "night owl\t\tLanguages\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Other\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Information Systems\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tEngineering: Other\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tBusiness: Finance\n",
+      "early bird\t\tStatistics\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tScience: Other\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tStatistics\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Other\n",
+      "early bird\t\tStatistics\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tBusiness: Finance\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Other\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Other\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "0\t\tScience: Other\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tBusiness: Other\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "early bird\t\tBusiness: Actuarial\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "no preference\t\tBusiness: Other\n",
+      "night owl\t\tStatistics\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Other\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tStatistics\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tStatistics\n",
+      "no preference\t\tBusiness: Actuarial\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tStatistics\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Other\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tBusiness: Other\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tBusiness: Other\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tBusiness: Actuarial\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Other\n",
+      "early bird\t\tStatistics\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tStatistics\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Other\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Other\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Other\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tComputer Science\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tComputer Science\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print out every student's sleep habits and major\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_sleep_habit = cs220_data[i][-3]\n",
+    "    current_major = cs220_data[i][4]\n",
+    "    print(current_sleep_habit + '\\t\\t' + current_major)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "29\n",
+      "28\n",
+      "29\n",
+      "29\n",
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+      "30\n",
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+      "35\n",
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+      "34\n",
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+      "30\n",
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+      "31\n",
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+      "31\n",
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+      "30\n",
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+      "28\n",
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+      "30\n",
+      "29\n",
+      "10\n",
+      "28\n",
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+      "35\n"
+     ]
+    }
+   ],
+   "source": [
+    "# FIX: Print out every students' age in 10 years.\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_age = cs220_data[i][3]\n",
+    "    if current_age == '' or '.' in current_age:\n",
+    "        continue\n",
+    "    print(int(current_age) + 10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## It would be nice to have a helper function!\n",
+    "Let's introduce `cell`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Section',\n",
+       " 'Lecture',\n",
+       " 'Printed Copy',\n",
+       " 'Age',\n",
+       " 'Primary Major',\n",
+       " 'Other Majors',\n",
+       " 'Secondary Majors',\n",
+       " 'Zip Code',\n",
+       " 'Latitude',\n",
+       " 'Longitude',\n",
+       " 'Data Science Major',\n",
+       " 'Pizza Topping',\n",
+       " 'Cats or Dogs',\n",
+       " 'Runner',\n",
+       " 'Sleep Habit',\n",
+       " 'Procrastinator',\n",
+       " 'Song']"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Remember creating cs220_header?\n",
+    "cs220_header"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "11"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Get the column index of \"Pizza Topping\"\n",
+    "cs220_header.index(\"Pizza Topping\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# We want to invoke something like...\n",
+    "# cell(24, \"Cats or Dogs\")\n",
+    "# cell(63, \"Zip Code\")\n",
+    "def cell(row_idx, col_name):\n",
+    "    col_idx = cs220_header.index(col_name) # get the index of col_name\n",
+    "    val = cs220_data[row_idx][col_idx]     # get the value of cs220_data at the specified cell\n",
+    "    return val"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'LEC001'"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Print out the lecture number of the 4th student... using the cell function\n",
+    "cell(3, \"Lecture\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "night owl\t\tEngineering: Other\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tScience: Other\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tBusiness: Finance\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tScience: Other\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Other\n",
+      "no preference\t\tEngineering: Other\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Other\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tScience: Other\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "night owl\t\tBusiness: Finance\n",
+      "early bird\t\tStatistics\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tScience: Other\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Chemistry\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Finance\n",
+      "early bird\t\tStatistics\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Other\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tStatistics\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "no preference\t\tBusiness: Finance\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tStatistics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tScience: Other\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tScience: Other\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tBusiness: Other\n",
+      "no preference\t\tScience: Chemistry\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Other\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Other\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Other\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "night owl\t\tBusiness: Other\n",
+      "night owl\t\tBusiness: Other\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "no preference\t\tScience: Physics\n",
+      "early bird\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tStatistics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Other\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Information Systems\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tScience: Physics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Other\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tStatistics\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "no preference\t\tScience: Physics\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tScience: Other\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tBusiness: Other\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tStatistics\n",
+      "no preference\t\tStatistics\n",
+      "night owl\t\tScience: Other\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tComputer Science\n",
+      "no preference\t\tScience: Other\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Other\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "no preference\t\tStatistics\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Other\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tBusiness: Other\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Other\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tScience: Chemistry\n",
+      "early bird\t\tLanguages\n",
+      "no preference\t\tComputer Science\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tScience: Other\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tBusiness: Other\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tScience: Physics\n",
+      "early bird\t\tComputer Science\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tScience: Chemistry\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Other\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "no preference\t\tMathematics/AMEP\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tBusiness: Other\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tScience: Chemistry\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tStatistics\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tScience: Other\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Other\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "no preference\t\tEngineering: Other\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Other\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tBusiness: Finance\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Other\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tStatistics\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tStatistics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tStatistics\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "early bird\t\tScience: Other\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tBusiness: Other\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tBusiness: Actuarial\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Other\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "no preference\t\tComputer Science\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tScience: Other\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Other\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Other\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tScience: Other\n",
+      "no preference\t\tBusiness: Information Systems\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tStatistics\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tBusiness: Other\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "no preference\t\tBusiness: Finance\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tStatistics\n",
+      "night owl\t\tLanguages\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Other\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Information Systems\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tComputer Science\n",
+      "night owl\t\tEngineering: Other\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tScience: Physics\n",
+      "night owl\t\tBusiness: Finance\n",
+      "early bird\t\tStatistics\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tScience: Other\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tStatistics\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Other\n",
+      "early bird\t\tStatistics\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tScience: Biology/Life\n",
+      "night owl\t\tBusiness: Finance\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tEngineering: Other\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Actuarial\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tScience: Other\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "0\t\tScience: Other\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "early bird\t\tScience: Biology/Life\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tBusiness: Other\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tStatistics\n",
+      "early bird\t\tBusiness: Actuarial\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tBusiness: Finance\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "no preference\t\tBusiness: Other\n",
+      "night owl\t\tStatistics\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Other\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tStatistics\n",
+      "early bird\t\tBusiness: Information Systems\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tStatistics\n",
+      "no preference\t\tBusiness: Actuarial\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "no preference\t\tStatistics\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Other\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tOther (please provide details below).\n",
+      "early bird\t\tBusiness: Other\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tBusiness: Other\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tStatistics\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tData Science\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "early bird\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tBusiness: Actuarial\n",
+      "no preference\t\tData Science\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Other\n",
+      "early bird\t\tStatistics\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tOther (please provide details below).\n",
+      "night owl\t\tBusiness: Information Systems\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "early bird\t\tMathematics/AMEP\n",
+      "early bird\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "no preference\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tData Science\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "no preference\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tStatistics\n",
+      "night owl\t\tScience: Biology/Life\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Other\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tEngineering: Biomedical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Other\n",
+      "night owl\t\tEngineering: Industrial\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tData Science\n",
+      "early bird\t\tStatistics\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tData Science\n",
+      "night owl\t\tEngineering: Biomedical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "early bird\t\tBusiness: Finance\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "early bird\t\tEngineering: Other\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tComputer Science\n",
+      "night owl\t\tComputer Science\n",
+      "no preference\t\tData Science\n",
+      "early bird\t\tScience: Physics\n",
+      "early bird\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "early bird\t\tData Science\n",
+      "night owl\t\tMathematics/AMEP\n",
+      "no preference\t\tEngineering: Mechanical\n",
+      "night owl\t\tEngineering: Mechanical\n",
+      "no preference\t\tComputer Science\n",
+      "no preference\t\tBusiness: Finance\n",
+      "early bird\t\tOther (please provide details below).\n",
+      "night owl\t\tComputer Science\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print out every student's sleep habits and major using the cell function\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_sleep_habit = cell(i,\"Sleep Habit\")\n",
+    "    current_major = cell(i,\"Primary Major\")\n",
+    "    print(current_sleep_habit + '\\t\\t' + current_major)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+     ]
+    }
+   ],
+   "source": [
+    "# Print out every students' age in 10 years using the cell function\n",
+    "# ... that didn't really help us here!\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_age = cell(i, \"Age\")\n",
+    "    if current_age != '' and '.' not in current_age:\n",
+    "        print(int(current_age) + 10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Improve the cell function so it returns the appropriate type.\n",
+    "# If there is nothing in the cell, return None\n",
+    "def cell(row_idx, col_name):\n",
+    "    col_idx = cs220_header.index(col_name)\n",
+    "    val = cs220_data[row_idx][col_idx]\n",
+    "    if val == '':\n",
+    "        return None\n",
+    "    elif col_name == 'Age':\n",
+    "        if '.' in val:\n",
+    "            return None\n",
+    "        else:\n",
+    "            return int(val)\n",
+    "    else:\n",
+    "        return val"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "28\n",
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+      "28\n",
+      "35\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print out every students' age in 10 years using the cell function\n",
+    "# ... much better!\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_age = cell(i, \"Age\")\n",
+    "    if current_age != None:\n",
+    "        print(current_age + 10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Average age for LEC001 is 19.09\n",
+      "Average age for LEC002 is 19.48\n",
+      "Average age for LEC003 is 19.22\n",
+      "Average age for LEC004 is 19.09\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Get the average age of each lecture...\n",
+    "students_lec_001 = []\n",
+    "students_lec_002 = []\n",
+    "students_lec_003 = []\n",
+    "students_lec_004 = []\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_lec = cell(i, \"Lecture\")\n",
+    "    current_age = cell(i, \"Age\")\n",
+    "    if current_age != None:\n",
+    "        if current_lec == \"LEC001\":\n",
+    "            students_lec_001.append(current_age)\n",
+    "        elif current_lec == \"LEC002\":\n",
+    "            students_lec_002.append(current_age)\n",
+    "        elif current_lec == \"LEC003\":\n",
+    "            students_lec_003.append(current_age)\n",
+    "        elif current_lec == \"LEC004\":\n",
+    "            students_lec_004.append(current_age)\n",
+    "            \n",
+    "print(\"Average age for {} is {}\".format(\"LEC001\", round(sum(students_lec_001) / len(students_lec_001), 2)))\n",
+    "print(\"Average age for {} is {}\".format(\"LEC002\", round(sum(students_lec_002) / len(students_lec_002), 2)))\n",
+    "print(\"Average age for {} is {}\".format(\"LEC003\", round(sum(students_lec_003) / len(students_lec_003), 2)))\n",
+    "print(\"Average age for {} is {}\".format(\"LEC004\", round(sum(students_lec_004) / len(students_lec_004), 2)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## You try!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Complete the challenges below. First try completing the problem directly using the list of lists (e.g. double indexing \\[\\]\\[\\]), then try using the `cell` function!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "There are 397 runners, of which 205 are procrastinators.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Of all runners, how many are procrastinators?\n",
+    "count_runners = 0\n",
+    "count_running_procrastinators = 0\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_procrastinator = cs220_data[i][cs220_header.index('Procrastinator')]\n",
+    "    current_runner = cs220_data[i][cs220_header.index('Runner')]\n",
+    "    \n",
+    "    if current_runner == \"Yes\":\n",
+    "        count_runners += 1\n",
+    "        if current_procrastinator == \"Yes\":\n",
+    "            count_running_procrastinators += 1\n",
+    "\n",
+    "print('There are {} runners, of which {} are procrastinators.'.format(count_runners, count_running_procrastinators))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "12.129032258064516"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# What percentage of 18-year-olds have their major declared as \"Other\"?\n",
+    "all_18_to_20 = []\n",
+    "all_18_to_20_and_other = []\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_age = cs220_data[i][cs220_header.index('Age')]\n",
+    "    current_major = cs220_data[i][cs220_header.index('Primary Major')]\n",
+    "    \n",
+    "    if current_age == \"\" or \".\" in current_age:\n",
+    "        continue\n",
+    "        \n",
+    "    current_age = int(current_age)\n",
+    "    \n",
+    "    if 18 <= current_age <= 20:\n",
+    "        all_18_to_20.append(i)\n",
+    "        if current_major.startswith(\"Other\"):\n",
+    "            all_18_to_20_and_other.append(i)\n",
+    "(len(all_18_to_20_and_other) / len(all_18_to_20)) * 100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "cat\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Does the oldest basil/spinach-loving Business major prefer cats, dogs, or neither?\n",
+    "oldest_idx = None\n",
+    "oldest_age = None\n",
+    "\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_age = cs220_data[i][cs220_header.index('Age')]\n",
+    "    current_pizza = cs220_data[i][cs220_header.index('Pizza Topping')]\n",
+    "    current_major = cs220_data[i][cs220_header.index('Primary Major')]\n",
+    "    \n",
+    "    if current_age == \"\" or \".\" in current_age:\n",
+    "        continue\n",
+    "        \n",
+    "    current_age = int(current_age)\n",
+    "        \n",
+    "    if current_pizza == \"basil/spinach\" and current_major.startswith(\"Business\"):\n",
+    "        if oldest_idx == None or current_age > oldest_age:\n",
+    "            oldest_age = current_age\n",
+    "            oldest_idx = i\n",
+    "    \n",
+    "print(cs220_data[oldest_idx][cs220_header.index('Cats or Dogs')])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Summary\n",
+    "\n",
+    "The `csv` module can be used to load CSV files and store them as a list of lists.  Use double-indexing and helper functions to work with data in this format."
+   ]
+  }
+ ],
+ "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": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs_Solution_Oliphant.ipynb b/f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs_Solution_Oliphant.ipynb
deleted file mode 100644
index c8ed3aa..0000000
--- a/f24/Louis_Lecture_Notes/15_CSVs/Lec_15_CSVs_Solution_Oliphant.ipynb
+++ /dev/null
@@ -1,649 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Warmup 0: Write a program that manages a grocery list!\n",
-    "# A: Add an item. Ask the user to add an item to their list.\n",
-    "# D: Delete an item. Ask the user what to remove from their list.\n",
-    "# P: Print the grocery list.\n",
-    "# Q: Quit.\n",
-    "\n",
-    "my_groceries = []\n",
-    "\n",
-    "while True:\n",
-    "    choice = input(\"What do you want to do? (A, D, P, Q): \")\n",
-    "    \n",
-    "    # TODO Improve handling of errors (e.g. user tries to remove a food that doesn't exist)\n",
-    "    choice = choice.upper()\n",
-    "    if choice == 'A':\n",
-    "        add_food = input(\"What do you want to add? \")\n",
-    "        my_groceries.append(add_food)\n",
-    "    elif choice == 'D':\n",
-    "        rem_food = input(\"What do you want to remove? \")\n",
-    "        while not rem_food in my_groceries:\n",
-    "            print('{} is not in your grocery list!'.format(rem_food))\n",
-    "            rem_food = input(\"What do you want to remove? \")\n",
-    "        my_groceries.remove(rem_food)\n",
-    "    elif choice == 'P':\n",
-    "        print(\"Your groceries are \", my_groceries)\n",
-    "    elif choice == 'Q':\n",
-    "        break\n",
-    "    else:\n",
-    "        print('I don\\'t understand. Please try again!')\n",
-    "        \n",
-    "print('Thanks for shopping!')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Warmup #1: Profanity Filter\n",
-    "\n",
-    "def profanity_filter(sentence, bad_words):\n",
-    "    ''' replaces all instances of any word in bad_words with \\n\n",
-    "    a word with the first letter and then @s and the same length'''\n",
-    "    \n",
-    "    sentence_split = sentence.split(\" \")\n",
-    "    cleaned_sentence = []\n",
-    "    \n",
-    "    for word in sentence_split:\n",
-    "        # TODO We need to improve this! Extra practice!\n",
-    "        if word in bad_words:\n",
-    "            cleaned_word = word[0] + \"@\" * (len(word) - 1) \n",
-    "            cleaned_sentence.append(cleaned_word)  \n",
-    "        else:\n",
-    "            cleaned_sentence.append(word)\n",
-    "    # all done cleaning, now join and return\n",
-    "    return \" \".join(cleaned_sentence)\n",
-    "    \n",
-    "    \n",
-    "bad_word_list = [\"darn\", \"heck\", \"crud\", \"exam\"]\n",
-    "print(profanity_filter(\"I unplugged that darn Alexa\", bad_word_list))\n",
-    "print(profanity_filter(\"What the heck was my boss thinking?\", bad_word_list))\n",
-    "print(profanity_filter(\"He is full of crud?\", bad_word_list)) # TODO On your own, how would you handle this?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Warmup #2: Take a look at these list methods \n",
-    "# https://www.w3schools.com/python/python_ref_list.asp\n",
-    "dairy = [\"milk\", \"ice cream\", \"cheese\", \"yogurt\" ]\n",
-    "\n",
-    "#use the .index() method to get the index of \"ice cream\"\n",
-    "dairy.index(\"ICE cream\".lower())\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Warmup #3:  Because a list is a sequence, we can use the 'in' operator\n",
-    "food_shelf = [\"peanut butter\", \"milk\", \"bread\", \"cheese\", \"YOGURT\"]\n",
-    "for item in food_shelf:\n",
-    "    if item.lower() in dairy:\n",
-    "        print(item, \"is dairy\")\n",
-    "    else:\n",
-    "        print(item, \"is not dairy\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# CS220: Lecture 15\n",
-    "\n",
-    "\n",
-    "## Learning Objectives\n",
-    "After this lecture you will be able to...\n",
-    "- Open an Excel file and export it to a Comma Separated Value file.\n",
-    "\n",
-    "- Open a CSV file in TextEditor/Jupyter and connect the elements of the CSV file to the rows and columns in the spreadsheet.\n",
-    "\n",
-    "- Use pre-written Python code to read a CSV file into a list of lists.\n",
-    "\n",
-    "- Write Python statements with double list indexing to access any element of a CSV file via a list of lists.\n",
-    "\n",
-    "- Write code that answers questions about CSV data by writing for loops on lists of lists.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Reading a CSV"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Now lets store the contents of the CSV file into Python lists\n",
-    "\n",
-    "# copied from https://automatetheboringstuff.com/chapter14/\n",
-    "import csv\n",
-    "\n",
-    "def process_csv(filename):\n",
-    "    # open the file, its a text file utf-8\n",
-    "    exampleFile = open(filename, encoding=\"utf-8\")  \n",
-    "    \n",
-    "    # prepare it for reading as a CSV object\n",
-    "    exampleReader = csv.reader(exampleFile) \n",
-    "    \n",
-    "    # use the built-in list function to convert this into a list of lists\n",
-    "    exampleData = list(exampleReader)        \n",
-    "    \n",
-    "    # close the file to tidy up our workspace\n",
-    "    exampleFile.close()  \n",
-    "    \n",
-    "    # return the list of lists\n",
-    "    return exampleData\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Call the process_csv function and store the list of lists in cs220_csv\n",
-    "cs220_csv = process_csv('cs220_survey_data.csv')\n",
-    "cs220_csv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Store the header row into cs220_header\n",
-    "cs220_header = cs220_csv[0]\n",
-    "cs220_header"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Store all of the data rows into cs220_data\n",
-    "cs220_data = cs220_csv[1:]\n",
-    "cs220_data"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## CSVs as a List of Lists"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print out the lecture number of the 4th student...by hardcoding its row and column....\n",
-    "cs220_data[3][1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print out the sleeping habit for the 2nd student...by hardcoding its row and column....\n",
-    "cs220_data[1][-3]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print out how many students completed the survey.\n",
-    "len(cs220_data)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print out every student's sleep habits and major\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_sleep_habit = cs220_data[i][12]\n",
-    "    current_major = cs220_data[i][3]\n",
-    "    print(current_sleep_habit + '\\t\\t' + current_major)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# FIX: Print out every students' age in 10 years.\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_age = cs220_data[i][2]\n",
-    "    if current_age == \"\":\n",
-    "        continue\n",
-    "    current_age = int(current_age)\n",
-    "    print(current_age + 10)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## It would be nice to have a helper function!\n",
-    "Let's introduce `cell`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Remember creating cs220_header?\n",
-    "cs220_header"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Get the column index of \"Pizza topping\"\n",
-    "cs220_header.index(\"Pizza topping\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# We want to invoke something like...\n",
-    "# cell(24, \"Pet owner\")\n",
-    "# cell(63, \"Zip Code\")\n",
-    "def cell(row_idx, col_name):\n",
-    "    col_idx = cs220_header.index(col_name) # get the index of col_name\n",
-    "    val = cs220_data[row_idx][col_idx]     # get the value of cs220_data at the specified cell\n",
-    "    return val"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print out the lecture number of the 4th student... using the cell function\n",
-    "cell(3, \"Lecture\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print out the fav pizza topping of the 8th student... using the cell function\n",
-    "cell(7, \"Pizza topping\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print out every student's sleep habits and major using the cell function\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_sleep_habit = cell(i, \"Sleep habit\")\n",
-    "    current_major = cell(i, \"Primary major\")\n",
-    "    print(current_sleep_habit + '\\t\\t' + current_major)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print out every students' age in 10 years using the cell function\n",
-    "# ... that didn't really help us here!\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_age = cell(i, \"Age\")\n",
-    "    print(type(current_age))\n",
-    "    if current_age != None:\n",
-    "        print(current_age + 10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Improve the cell function so it returns the appropriate type.\n",
-    "# If there is nothing in the cell, return None\n",
-    "def cell(row_idx, col_name):\n",
-    "    col_idx = cs220_header.index(col_name)\n",
-    "    val = cs220_data[row_idx][col_idx]\n",
-    "    if val == \"\":\n",
-    "        return None\n",
-    "    elif col_name == \"Age\":\n",
-    "        return int(val)\n",
-    "    else:\n",
-    "        return val\n",
-    "    \n",
-    "# Yours to do... can you handle Zip Code, Latitude, and Longitude?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print out every students' age in 10 years using the cell function\n",
-    "# ... much better!\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_age = cell(i, \"Age\")\n",
-    "    if current_age != None:\n",
-    "        print(current_age + 10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Get the average age of each lecture...\n",
-    "students_lec_001 = []\n",
-    "students_lec_002 = []\n",
-    "students_lec_003 = []\n",
-    "students_lec_004 = []\n",
-    "students_lec_005 = []\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_lec = cell(i, \"Lecture\")\n",
-    "    current_age = cell(i, \"Age\")\n",
-    "    if current_age != None:\n",
-    "        if current_lec == \"LEC001\":\n",
-    "            students_lec_001.append(current_age)\n",
-    "        elif current_lec == \"LEC002\":\n",
-    "            students_lec_002.append(current_age)\n",
-    "        elif current_lec == \"LEC003\":\n",
-    "            students_lec_003.append(current_age)\n",
-    "        elif current_lec == \"LEC004\":\n",
-    "            students_lec_004.append(current_age)\n",
-    "        elif current_lec == \"LEC005\":\n",
-    "            students_lec_005.append(current_age)\n",
-    "            \n",
-    "print(\"Average age for {} is {}\".format(\"LEC001\", round(sum(students_lec_001) / len(students_lec_001), 2)))\n",
-    "print(\"Average age for {} is {}\".format(\"LEC002\", round(sum(students_lec_002) / len(students_lec_002), 2)))\n",
-    "print(\"Average age for {} is {}\".format(\"LEC003\", round(sum(students_lec_003) / len(students_lec_003), 2)))\n",
-    "print(\"Average age for {} is {}\".format(\"LEC004\", round(sum(students_lec_004) / len(students_lec_004), 2)))\n",
-    "print(\"Average age for {} is {}\".format(\"LEC005\", round(sum(students_lec_005) / len(students_lec_005), 2)))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Get the average age of each lecture... With less hardcoding!\n",
-    "lectures_of_ages = [\n",
-    "    [],\n",
-    "    [],\n",
-    "    [],\n",
-    "    [],\n",
-    "    []\n",
-    "]\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_lec = int(cell(i, \"Lecture\")[-1]) - 1 # Will be a number 0 - 4\n",
-    "    current_age = cell(i, \"Age\")\n",
-    "    if current_age != None:\n",
-    "        lectures_of_ages[current_lec].append(current_age)\n",
-    "        \n",
-    "for i in range(len(lectures_of_ages)):\n",
-    "    curr_lec = lectures_of_ages[i]\n",
-    "    total_age = sum(curr_lec)\n",
-    "    total_students = len(curr_lec)\n",
-    "    print(\"Average age for {} is {}\".format(\"LEC00\" + str(i + 1), round(total_age / total_students, 2)))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# What are the unique ages for each lecture?\n",
-    "for i in range(len(lectures_of_ages)):\n",
-    "    unique_ages = list(set(lectures_of_ages[i]))\n",
-    "    print(sorted(unique_ages))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## You try!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Complete the challenges below. First try completing the problem directly using the list of lists (e.g. double indexing \\[\\]\\[\\]), then try using the `cell` function!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Of all runners, how many are procrastinators? [][]\n",
-    "count_runners = 0\n",
-    "count_running_procrastinators = 0\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_procrastinator = cs220_data[i][cs220_header.index('Procrastinator')]\n",
-    "    current_runner = cs220_data[i][cs220_header.index('Runner')]\n",
-    "    \n",
-    "    if current_runner == \"Yes\":\n",
-    "        count_runners += 1\n",
-    "        if current_procrastinator == \"Yes\":\n",
-    "            count_running_procrastinators += 1\n",
-    "\n",
-    "print('There are {} runners, of which {} are procrastinators.'.format(count_runners, count_running_procrastinators))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Of all runners, how many are procrastinators? [][]\n",
-    "count_runners = 0\n",
-    "count_running_procrastinators = 0\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_procrastinator = cell(i, 'Procrastinator')\n",
-    "    current_runner = cell(i, 'Runner')\n",
-    "    \n",
-    "    if current_runner == \"Yes\":\n",
-    "        count_runners += 1\n",
-    "        if current_procrastinator == \"Yes\":\n",
-    "            count_running_procrastinators += 1\n",
-    "\n",
-    "print('There are {} runners, of which {} are procrastinators.'.format(count_runners, count_running_procrastinators))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# What percentage of 18 to 20-year-olds have their major declared as \"Other\"? [][]\n",
-    "\n",
-    "# Could alternatively have 2 count variables.\n",
-    "all_18_to_20 = []\n",
-    "all_18_to_20_and_other = []\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_age = cs220_data[i][cs220_header.index('Age')]\n",
-    "    current_major = cs220_data[i][cs220_header.index('Primary major')]\n",
-    "    \n",
-    "    if current_age == \"\":\n",
-    "        continue\n",
-    "        \n",
-    "    current_age = int(current_age)\n",
-    "    \n",
-    "    if 18 <= current_age <= 20:\n",
-    "        all_18_to_20.append(i)\n",
-    "        if current_major.startswith(\"Other\"):\n",
-    "            all_18_to_20_and_other.append(i)\n",
-    "(len(all_18_to_20_and_other) / len(all_18_to_20)) * 100"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# What percentage of 18 to 20-year-olds have their major declared as \"Other\"? cell\n",
-    "\n",
-    "# Could alternatively have 2 count variables.\n",
-    "all_18_to_20 = []\n",
-    "all_18_to_20_and_other = []\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_age = cell(i, 'Age')\n",
-    "    current_major = cell(i, 'Primary major')\n",
-    "    \n",
-    "    if current_age == None:\n",
-    "        continue\n",
-    "        \n",
-    "    current_age = int(current_age)\n",
-    "    \n",
-    "    if 18 <= current_age <= 20:\n",
-    "        all_18_to_20.append(i)\n",
-    "        if current_major.startswith(\"Other\"):\n",
-    "            all_18_to_20_and_other.append(i)\n",
-    "(len(all_18_to_20_and_other) / len(all_18_to_20)) * 100"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Does the oldest basil/spinach-loving Business major prefer cats, dogs, or neither? [][]\n",
-    "oldest_idx = None\n",
-    "oldest_age = None\n",
-    "\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_age = cs220_data[i][cs220_header.index('Age')]\n",
-    "    current_pizza = cs220_data[i][cs220_header.index('Pizza topping')]\n",
-    "    current_major = cs220_data[i][cs220_header.index('Primary major')]\n",
-    "    \n",
-    "    if current_age == \"\":\n",
-    "        continue\n",
-    "        \n",
-    "    current_age = int(current_age)\n",
-    "        \n",
-    "    if current_pizza == \"basil/spinach\" and current_major.startswith(\"Business\"):\n",
-    "        if oldest_idx == None or current_age > oldest_age:\n",
-    "            oldest_age = current_age\n",
-    "            oldest_idx = i\n",
-    "    \n",
-    "print(cs220_data[oldest_idx][cs220_header.index('Cats or dogs')])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Does the oldest basil/spinach-loving Business major prefer cats, dogs, or neither? cell\n",
-    "oldest_idx = None\n",
-    "oldest_age = None\n",
-    "\n",
-    "for i in range(len(cs220_data)):\n",
-    "    current_age = cell(i, \"Age\")\n",
-    "    current_pizza = cell(i, \"Pizza topping\")\n",
-    "    current_major = cell(i, \"Primary major\")\n",
-    "    \n",
-    "    if current_age == None:\n",
-    "        continue\n",
-    "        \n",
-    "    current_age = int(current_age)\n",
-    "        \n",
-    "    if current_pizza == \"basil/spinach\" and current_major.startswith(\"Business\"):\n",
-    "        if oldest_idx == None or current_age > oldest_age:\n",
-    "            oldest_age = current_age\n",
-    "            oldest_idx = i\n",
-    "    \n",
-    "print(cell(oldest_idx, \"Cats or dogs\"))"
-   ]
-  },
-  {
-   "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": "3.11.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/f24/Louis_Lecture_Notes/15_CSVs/colors.csv b/f24/Louis_Lecture_Notes/15_CSVs/colors.csv
new file mode 100644
index 0000000..dcf9df9
--- /dev/null
+++ b/f24/Louis_Lecture_Notes/15_CSVs/colors.csv
@@ -0,0 +1,146 @@
+Name,HEX,RGB
+Alice Blue,#F0F8FF,"rgb(239,247,255)"
+Antique White,#FAEBD7,"rgb(249,234,214)"
+Aqua,#00FFFF,"rgb(0,255,255)"
+Aquamarine,#7FFFD4,"rgb(127,255,211)"
+Azure,#F0FFFF,"rgb(239,255,255)"
+Beige,#F5F5DC,"rgb(244,244,219)"
+Bisque,#FFE4C4,"rgb(255,226,196)"
+Black,#000000,"rgb(0,0,0)"
+Blanched Almond,#FFEBCD,"rgb(255,234,204)"
+Blue,#0000FF,"rgb(0,0,255)"
+Blue Violet,#8A2BE2,"rgb(137,43,226)"
+Brown,#A52A2A,"rgb(165,40,40)"
+Burlywood,#DEB887,"rgb(221,183,135)"
+Cadet Blue,#5F9EA0,"rgb(94,158,160)"
+Chartreuse,#7FFF00,"rgb(127,255,0)"
+Chocolate,#D2691E,"rgb(209,104,30)"
+Coral,#FF7F50,"rgb(255,127,79)"
+Cornflower Blue,#6495ED,"rgb(99,147,237)"
+Cornsilk,#FFF8DC,"rgb(255,247,219)"
+Crimson,#DC143C,"rgb(219,20,61)"
+Cyan,#00FFFF,"rgb(0,255,255)"
+Dark Blue,#00008B,"rgb(0,0,140)"
+Dark Cyan,#008B8B,"rgb(0,140,140)"
+Dark Goldenrod,#B8860B,"rgb(183,135,10)"
+Dark Gray,#A9A9A9,"rgb(168,168,168)"
+Dark Green,#006400,"rgb(0,99,0)"
+Dark Khaki,#BDB76B,"rgb(188,183,107)"
+Dark Magenta,#8B008B,"rgb(140,0,140)"
+Dark Olive Green,#556B2F,"rgb(84,107,45)"
+Dark Orange,#FF8C00,"rgb(255,140,0)"
+Dark Orchid,#9932CC,"rgb(153,51,204)"
+Dark Red,#8B0000,"rgb(140,0,0)"
+Dark Salmon,#E9967A,"rgb(232,150,122)"
+Dark Sea Green,#8FBC8F,"rgb(142,188,142)"
+Dark Slate Blue,#483D8B,"rgb(71,61,140)"
+Dark Slate Gray,#2F4F4F,"rgb(45,79,79)"
+Dark Turquoise,#00CED1,"rgb(0,206,209)"
+Dark Violet,#9400D3,"rgb(147,0,211)"
+Deep Pink,#FF1493,"rgb(255,20,147)"
+Deep Sky Blue,#00BFFF,"rgb(0,191,255)"
+Dim Gray,#696969,"rgb(104,104,104)"
+Dodger Blue,#1E90FF,"rgb(30,142,255)"
+Firebrick,#B22222,"rgb(178,33,33)"
+Floral White,#FFFAF0,"rgb(255,249,239)"
+Forest Green,#228B22,"rgb(33,140,33)"
+Fuchsia,#FF00FF,"rgb(255,0,255)"
+Gainsboro,#DCDCDC,"rgb(219,219,219)"
+Ghost White,#F8F8FF,"rgb(247,247,255)"
+Gold,#FFD700,"rgb(255,214,0)"
+Goldenrod,#DAA520,"rgb(216,165,33)"
+Gray,#BEBEBE,"rgb(191,191,191)"
+Web Gray,#808080,"rgb(127,127,127)"
+Green,#00FF00,"rgb(0,255,0)"
+Web Green,#008000,"rgb(0,127,0)"
+Green Yellow,#ADFF2F,"rgb(173,255,45)"
+Honeydew,#F0FFF0,"rgb(239,255,239)"
+Hot Pink,#FF69B4,"rgb(255,104,181)"
+Indian Red,#CD5C5C,"rgb(204,91,91)"
+Indigo,#4B0082,"rgb(73,0,130)"
+Ivory,#FFFFF0,"rgb(255,255,239)"
+Khaki,#F0E68C,"rgb(239,229,140)"
+Lavender,#E6E6FA,"rgb(229,229,249)"
+Lavender Blush,#FFF0F5,"rgb(255,239,244)"
+Lawn Green,#7CFC00,"rgb(124,252,0)"
+Lemon Chiffon,#FFFACD,"rgb(255,249,204)"
+Light Blue,#ADD8E6,"rgb(173,216,229)"
+Light Coral,#F08080,"rgb(239,127,127)"
+Light Cyan,#E0FFFF,"rgb(224,255,255)"
+Light Goldenrod,#FAFAD2,"rgb(249,249,209)"
+Light Gray,#D3D3D3,"rgb(211,211,211)"
+Light Green,#90EE90,"rgb(142,237,142)"
+Light Pink,#FFB6C1,"rgb(255,181,193)"
+Light Salmon,#FFA07A,"rgb(255,160,122)"
+Light Sea Green,#20B2AA,"rgb(33,178,170)"
+Light Sky Blue,#87CEFA,"rgb(135,206,249)"
+Light Slate Gray,#778899,"rgb(119,135,153)"
+Light Steel Blue,#B0C4DE,"rgb(175,196,221)"
+Light Yellow,#FFFFE0,"rgb(255,255,224)"
+Lime,#00FF00,"rgb(0,255,0)"
+Lime Green,#32CD32,"rgb(51,204,51)"
+Linen,#FAF0E6,"rgb(249,239,229)"
+Magenta,#FF00FF,"rgb(255,0,255)"
+Maroon,#B03060,"rgb(175,48,96)"
+Web Maroon,#800000,"rgb(127,0,0)"
+Medium Aquamarine,#66CDAA,"rgb(102,204,170)"
+Medium Blue,#0000CD,"rgb(0,0,204)"
+Medium Orchid,#BA55D3,"rgb(186,84,211)"
+Medium Purple,#9370DB,"rgb(147,112,219)"
+Medium Sea Green,#3CB371,"rgb(61,178,112)"
+Medium Slate Blue,#7B68EE,"rgb(122,104,237)"
+Medium Spring Green,#00FA9A,"rgb(0,249,153)"
+Medium Turquoise,#48D1CC,"rgb(71,209,204)"
+Medium Violet Red,#C71585,"rgb(198,20,132)"
+Midnight Blue,#191970,"rgb(25,25,112)"
+Mint Cream,#F5FFFA,"rgb(244,255,249)"
+Misty Rose,#FFE4E1,"rgb(255,226,224)"
+Moccasin,#FFE4B5,"rgb(255,226,181)"
+Navajo White,#FFDEAD,"rgb(255,221,173)"
+Navy Blue,#000080,"rgb(0,0,127)"
+Old Lace,#FDF5E6,"rgb(252,244,229)"
+Olive,#808000,"rgb(127,127,0)"
+Olive Drab,#6B8E23,"rgb(107,142,35)"
+Orange,#FFA500,"rgb(255,165,0)"
+Orange Red,#FF4500,"rgb(255,68,0)"
+Orchid,#DA70D6,"rgb(216,112,214)"
+Pale Goldenrod,#EEE8AA,"rgb(237,232,170)"
+Pale Green,#98FB98,"rgb(153,249,153)"
+Pale Turquoise,#AFEEEE,"rgb(175,237,237)"
+Pale Violet Red,#DB7093,"rgb(219,112,147)"
+Papaya Whip,#FFEFD5,"rgb(255,239,214)"
+Peach Puff,#FFDAB9,"rgb(255,216,186)"
+Peru,#CD853F,"rgb(204,132,63)"
+Pink,#FFC0CB,"rgb(255,191,204)"
+Plum,#DDA0DD,"rgb(221,160,221)"
+Powder Blue,#B0E0E6,"rgb(175,224,229)"
+Purple,#A020F0,"rgb(160,33,239)"
+Web Purple,#800080,"rgb(127,0,127)"
+Rebecca Purple,#663399,"rgb(102,51,153)"
+Red,#FF0000,"rgb(255,0,0)"
+Rosy Brown,#BC8F8F,"rgb(188,142,142)"
+Royal Blue,#4169E1,"rgb(63,104,224)"
+Saddle Brown,#8B4513,"rgb(140,68,17)"
+Salmon,#FA8072,"rgb(249,127,114)"
+Sandy Brown,#F4A460,"rgb(244,163,96)"
+Sea Green,#2E8B57,"rgb(45,140,86)"
+Seashell,#FFF5EE,"rgb(255,244,237)"
+Sienna,#A0522D,"rgb(160,81,45)"
+Silver,#C0C0C0,"rgb(191,191,191)"
+Sky Blue,#87CEEB,"rgb(135,206,234)"
+Slate Blue,#6A5ACD,"rgb(107,89,204)"
+Slate Gray,#708090,"rgb(112,127,142)"
+Snow,#FFFAFA,"rgb(255,249,249)"
+Spring Green,#00FF7F,"rgb(0,255,127)"
+Steel Blue,#4682B4,"rgb(68,130,181)"
+Tan,#D2B48C,"rgb(209,181,140)"
+Teal,#008080,"rgb(0,127,127)"
+Thistle,#D8BFD8,"rgb(216,191,216)"
+Tomato,#FF6347,"rgb(255,99,71)"
+Turquoise,#40E0D0,"rgb(63,224,209)"
+Violet,#EE82EE,"rgb(237,130,237)"
+Wheat,#F5DEB3,"rgb(244,221,178)"
+White,#FFFFFF,"rgb(255,255,255)"
+White Smoke,#F5F5F5,"rgb(244,244,244)"
+Yellow,#FFFF00,"rgb(255,255,0)"
+Yellow Green,#9ACD32,"rgb(153,204,51)"
-- 
GitLab