From ba33462fe78d40c4e9d4ddfd98d692f56dddee2a Mon Sep 17 00:00:00 2001
From: msyamkumar <msyamkumar@wisc.edu>
Date: Fri, 21 Oct 2022 07:27:46 -0500
Subject: [PATCH] Clearing json files
---
.../demo_lec_19-checkpoint.ipynb | 2815 ----
.../demo_lec_19_template-checkpoint.ipynb | 551 -
.../lec_19_json-checkpoint.ipynb | 497 -
.../lec_19_json_template-checkpoint.ipynb | 472 -
.../lec-19/cs220_survey_data.json | 12898 ---------------
.../lec-19/lecture_cs220_data.json | 12910 ---------------
.../lec-19/major_cs220_data.json | 13094 ----------------
f22/meena_lec_notes/lec-19/numsA.json | 1 -
f22/meena_lec_notes/lec-19/score_history.json | 17 -
.../lec-19/section_cs220_data.json | 12910 ---------------
10 files changed, 56165 deletions(-)
delete mode 100644 f22/meena_lec_notes/lec-19/.ipynb_checkpoints/demo_lec_19-checkpoint.ipynb
delete mode 100644 f22/meena_lec_notes/lec-19/.ipynb_checkpoints/demo_lec_19_template-checkpoint.ipynb
delete mode 100644 f22/meena_lec_notes/lec-19/.ipynb_checkpoints/lec_19_json-checkpoint.ipynb
delete mode 100644 f22/meena_lec_notes/lec-19/.ipynb_checkpoints/lec_19_json_template-checkpoint.ipynb
delete mode 100644 f22/meena_lec_notes/lec-19/cs220_survey_data.json
delete mode 100644 f22/meena_lec_notes/lec-19/lecture_cs220_data.json
delete mode 100644 f22/meena_lec_notes/lec-19/major_cs220_data.json
delete mode 100644 f22/meena_lec_notes/lec-19/numsA.json
delete mode 100644 f22/meena_lec_notes/lec-19/score_history.json
delete mode 100644 f22/meena_lec_notes/lec-19/section_cs220_data.json
diff --git a/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/demo_lec_19-checkpoint.ipynb b/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/demo_lec_19-checkpoint.ipynb
deleted file mode 100644
index 1c17507..0000000
--- a/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/demo_lec_19-checkpoint.ipynb
+++ /dev/null
@@ -1,2815 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Dictionaries 2"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<style>em { color: red; }</style> <style>.container {width:100% !important; }</style>"
- ],
- "text/plain": [
- "<IPython.core.display.HTML object>"
- ]
- },
- "execution_count": 1,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# This cell just makes juypter notebook use the full width of the screen and changes \n",
- "# some of the text to red. You can ignore this cell\n",
- "from IPython.core.display import HTML\n",
- "HTML('<style>em { color: red; }</style> <style>.container {width:100% !important; }</style>')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## If you could choose only one data structure to include in Python: *lists or dictionaries*, which would you choose?"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### List some characteristics of lists - why might you choose to keep *lists*?"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "- indexing - to get data or to update it\n",
- "- slicing - get a sub-sequence\n",
- "- iterate with for loops\n",
- "- string to list and list to string coversion using methods *split* and *join*\n",
- "- csv files are represented using list of lists"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['a', 'b', 'c']"
- ]
- },
- "execution_count": 2,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "L = ['a', 'b', 'c']\n",
- "L"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{0: 'a', 1: 'b', 2: 'c'}"
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "L_dict = {0:'a', 1:'b', 2:'c'}\n",
- "L_dict"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### List some characteristics of dictionaries - why might you choose to keep *dictionaries*?"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "- lookup values using keys \n",
- "- labels can be any (immutable) type (flexibility)\n",
- "- insert and update have same syntax\n",
- "- iterate with for loops"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{'x': 3, 'y': 9}"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "d = {'x': 3, 'y': 9}\n",
- "d"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "x 3\n",
- "y 9\n"
- ]
- }
- ],
- "source": [
- "keys = ['x', 'y']\n",
- "vals = [ 3 , 9 ]\n",
- "\n",
- "for index in range(len(keys)):\n",
- " print(keys[index], vals[index])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Review - Dictionary Methods: len, in, for"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{0: 'zero', 1: 'one', 2: 'two', 3: 'three'}"
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "num_words = {0:\"zero\", 1:\"one\", 2:\"two\", 3:\"three\"}\n",
- "num_words"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "4"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(num_words)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "True\n"
- ]
- }
- ],
- "source": [
- "print(1 in num_words)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "False\n"
- ]
- }
- ],
- "source": [
- "print(\"one\" in num_words)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "0 zero\n",
- "1 one\n",
- "2 two\n",
- "3 three\n"
- ]
- }
- ],
- "source": [
- "for key in num_words:\n",
- " print(key, num_words[key])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Dictionary Methods: keys and values"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[0, 1, 2, 3]"
- ]
- },
- "execution_count": 11,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "list(num_words.keys())"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['zero', 'one', 'two', 'three']"
- ]
- },
- "execution_count": 12,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "list(num_words.values())"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "True\n",
- "False\n",
- "True\n",
- "True\n"
- ]
- }
- ],
- "source": [
- "print(1 in num_words)\n",
- "print(\"one\" in num_words)\n",
- "print(1 in list(num_words.keys()))\n",
- "print(\"one\" in list(num_words.values()))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Dictionary Methods: get and pop"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{0: 'zero', 1: 'one', 2: 'two', 3: 'three'}"
- ]
- },
- "execution_count": 14,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "num_words"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'one'"
- ]
- },
- "execution_count": 15,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "num_words.get(1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {},
- "outputs": [],
- "source": [
- "num_words.get(4) # doesn't get anything"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'three'"
- ]
- },
- "execution_count": 17,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "num_words.pop(3)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{0: 'zero', 1: 'one', 2: 'two'}"
- ]
- },
- "execution_count": 18,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "num_words"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {},
- "outputs": [],
- "source": [
- "# num_words.pop(4) # KeyError"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Default Values with get and pop"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{1: 'st', 2: 'nd', 3: 'rd'}"
- ]
- },
- "execution_count": 20,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "suffix = {1:\"st\", 2:\"nd\", 3:\"rd\"}\n",
- "suffix"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'th'"
- ]
- },
- "execution_count": 21,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "suffix.pop(0, \"th\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'th'"
- ]
- },
- "execution_count": 22,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "suffix.get(4,\"th\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Compute the Average Age of Students per Section"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {},
- "outputs": [],
- "source": [
- "import csv\n",
- "\n",
- "# copied from https://automatetheboringstuff.com/chapter14/\n",
- "def process_csv(filename):\n",
- " exampleFile = open(filename, encoding=\"utf-8\")\n",
- " exampleReader = csv.reader(exampleFile)\n",
- " exampleData = list(exampleReader)\n",
- " exampleFile.close()\n",
- " return exampleData"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Explore the data\n",
- "- separate it into header and data"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 24,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['lecture', 'age', 'major', 'topping']"
- ]
- },
- "execution_count": 24,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "data = process_csv(\"cs220_survey_data.csv\")\n",
- "header = data[0]\n",
- "header"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[['LEC001', '19', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC002', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'Other'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage']]"
- ]
- },
- "execution_count": 25,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "data = data[1:]\n",
- "data[0:5]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Let's write cell function"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "metadata": {},
- "outputs": [],
- "source": [
- "def cell(row_idx, col_name):\n",
- " col_idx = header.index(col_name)\n",
- " val = data[row_idx][col_idx]\n",
- " if val == \"\":\n",
- " return None\n",
- " if col_name in [\"age\", \"num_credits\"]: # Let's assume the dataset contains another column called num_credits\n",
- " return int(val)\n",
- " return val"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Write a function to compute the average age"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 27,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "19.6"
- ]
- },
- "execution_count": 27,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# data is a list of lists, corresponding to header\n",
- "def col_avg(data, col_name):\n",
- " total = 0\n",
- " count = 0\n",
- " for row_idx in range(len(data)):\n",
- " col_data = cell(row_idx, col_name)\n",
- " if col_data != None:\n",
- " total += col_data\n",
- " count += 1\n",
- " return round(total / count, 1)\n",
- " \n",
- "col_avg(data, \"age\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Collect the data into buckets\n",
- "- Write a function called bucketize\n",
- " - input: column name for bucketization\n",
- " - output: buckets -> dict of list of lists"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 28,
- "metadata": {},
- "outputs": [],
- "source": [
- "def bucketize(bucket_column):\n",
- " buckets = {} # Key: column unique value; Value: List of lists (rows with that unique column value)\n",
- " for row in data:\n",
- " year = row[header.index(bucket_column)]\n",
- " if year not in buckets:\n",
- " buckets[year] = []\n",
- " buckets[year].append(row)\n",
- " return buckets"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Bucketize by year"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 29,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{'LEC001': [['LEC001', '19', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC001', '20', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'not sure yet but maybe biology ', 'none (just cheese)'],\n",
- " ['LEC001', '20', 'Engineering', 'basil/spinach'],\n",
- " ['LEC001', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '20', 'Business', 'mushroom'],\n",
- " ['LEC001', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC001', '21', 'Business', 'basil/spinach'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC001', '21', 'Computer Science', 'green pepper'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '18', 'Engineering', 'sausage'],\n",
- " ['LEC001', '23', 'Computer Science', 'tomato'],\n",
- " ['LEC001', '20', 'Engineering', 'sausage'],\n",
- " ['LEC001', '20', 'Engineering', 'green pepper'],\n",
- " ['LEC001', '25', 'Data Science', 'green pepper'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '18', 'Accounting', 'pepperoni'],\n",
- " ['LEC001', '19', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC001', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '22', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '22', 'Business', 'mushroom'],\n",
- " ['LEC001', '20', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC001', '19', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '18', 'Engineering', 'Other'],\n",
- " ['LEC001', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC001', '20', 'Data Science', 'tomato'],\n",
- " ['LEC001', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '30', 'Data Science', 'basil/spinach'],\n",
- " ['LEC001', '35', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '29', 'Engineering', 'mushroom'],\n",
- " ['LEC001', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC001', '18', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '20', 'Biomedical Engineering', 'macaroni/pasta'],\n",
- " ['LEC001', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC001', '18', 'Social Science', 'tomato'],\n",
- " ['LEC001', '20', 'Engineering', 'Other'],\n",
- " ['LEC001', '23', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '20', 'Data Science', 'basil/spinach'],\n",
- " ['LEC001', '18', 'Business', 'mushroom'],\n",
- " ['LEC001', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC001', '22', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '22', 'Natural Science', 'sausage'],\n",
- " ['LEC001', '19', 'Business', 'sausage'],\n",
- " ['LEC001', '18', 'Business', 'basil/spinach'],\n",
- " ['LEC001', '18', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Social Science', 'pineapple'],\n",
- " ['LEC001', '20', 'Economics', 'pineapple'],\n",
- " ['LEC001', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '21', 'Natural Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '20', 'Engineering', 'Other'],\n",
- " ['LEC001', '20', 'Computer Science', 'mushroom'],\n",
- " ['LEC001', '18', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC001', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '19', 'Business', 'mushroom'],\n",
- " ['LEC001', '20', 'Business', 'pepperoni'],\n",
- " ['LEC001', '21', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Business', 'pepperoni'],\n",
- " ['LEC001', '19', 'Computer Science', 'Other'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '22', 'Business', 'green pepper'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'sausage'],\n",
- " ['LEC001', '20', 'Data Science', 'sausage'],\n",
- " ['LEC001', '28', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Computer Science', 'mushroom'],\n",
- " ['LEC001', '22', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Natural Science', 'sausage'],\n",
- " ['LEC001', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC001', '20', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC001', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC001', '22', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Business', 'pineapple'],\n",
- " ['LEC001', '', 'Social Science', 'Other'],\n",
- " ['LEC001', '20', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '20', 'statistics', 'sausage'],\n",
- " ['LEC001', '21', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '21', 'Business', 'pepperoni'],\n",
- " ['LEC001', '19', 'Natural Science', 'macaroni/pasta'],\n",
- " ['LEC001', '20', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC001', '20', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC001', '20', 'Business', 'pepperoni'],\n",
- " ['LEC001', '20', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC001', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '21', 'Public Policy', 'pepperoni'],\n",
- " ['LEC001', '20', 'Business', 'sausage'],\n",
- " ['LEC001', '17', 'Data Science', 'Other'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '20', 'Information Systems', 'Other'],\n",
- " ['LEC001', '18', 'Engineering', 'mushroom'],\n",
- " ['LEC001', '23', 'Business', 'pineapple'],\n",
- " ['LEC001', '20', 'Natural Science', 'green pepper'],\n",
- " ['LEC001', '19', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '18', 'Data Science', 'Other'],\n",
- " ['LEC001', '21', 'Engineering', 'Other'],\n",
- " ['LEC001', '20', 'Business', 'pepperoni'],\n",
- " ['LEC001', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '18', 'Computer Science', 'mushroom'],\n",
- " ['LEC001', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '21', 'STATS', 'basil/spinach'],\n",
- " ['LEC001', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '21', 'Data Science', 'Other'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '23', 'Mechanical Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC001', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '20', 'Business', 'sausage'],\n",
- " ['LEC001', '18', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC001', '20', 'Natural Science', 'Other'],\n",
- " ['LEC001', '20', 'Meteorology or Oceanography', 'basil/spinach'],\n",
- " ['LEC001', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '18', 'Engineering', 'tomato'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'economics', 'none (just cheese)'],\n",
- " ['LEC001', '20', 'Engineering', 'Other'],\n",
- " ['LEC001', '18', 'Social Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'green pepper'],\n",
- " ['LEC001', '22', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Business', 'pepperoni'],\n",
- " ['LEC001', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '18', 'Natural Science', 'none (just cheese)'],\n",
- " ['LEC001', '19', 'Business', 'basil/spinach'],\n",
- " ['LEC001', '20', 'Geography/GIS', 'pineapple'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '20', 'Statistics', 'mushroom'],\n",
- " ['LEC001', '20', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '21', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC001', '18', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '00', 'Data Science', 'Other'],\n",
- " ['LEC001', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC001', '20', 'chemistry', 'pepperoni'],\n",
- " ['LEC001', '18', 'Natural Science', 'pineapple'],\n",
- " ['LEC001', '20', 'Business', 'pepperoni'],\n",
- " ['LEC001', '21', 'Business', 'mushroom'],\n",
- " ['LEC001', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC001', '22', 'Data Science', 'sausage'],\n",
- " ['LEC001', '21', 'Business', 'sausage'],\n",
- " ['LEC001', '17', 'Computer Science', 'Other'],\n",
- " ['LEC001', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '21', 'Natural Science', 'sausage'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'tomato'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '21', 'Engineering', 'basil/spinach'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '22', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '25', 'Social Science', 'Other'],\n",
- " ['LEC001', '20', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '21', 'Data Science', 'basil/spinach'],\n",
- " ['LEC001', '21', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC001', '21', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '00', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '34', 'Data Science', 'tomato'],\n",
- " ['LEC001', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Applied Math', 'pepperoni'],\n",
- " ['LEC001', '19', 'Business', 'sausage'],\n",
- " ['LEC001', '20', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC001', '18', 'Statistics', 'pepperoni'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC001', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '25', 'Natural Science', 'pepperoni'],\n",
- " ['LEC001', '22', 'Computer Science', 'sausage'],\n",
- " ['LEC001', '23', 'Social Science', 'tomato'],\n",
- " ['LEC001', '21', 'Engineering', 'sausage'],\n",
- " ['LEC001', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC001', '22', 'Business', 'mushroom'],\n",
- " ['LEC001', '21', 'Business', 'pepperoni'],\n",
- " ['LEC001', '26', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '22', 'Natural Science', 'sausage'],\n",
- " ['LEC001', '20', 'Engineering', 'sausage'],\n",
- " ['LEC001', '22', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '20', 'Computer Science', 'mushroom'],\n",
- " ['LEC001', '20', 'Natural Science', 'sausage'],\n",
- " ['LEC001', '22', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '27', 'Natural Science', 'pepperoni'],\n",
- " ['LEC001', '22', 'statistics', 'pepperoni'],\n",
- " ['LEC001', '21', 'Natural Science', 'Other'],\n",
- " ['LEC001', '19', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '20', 'Business', 'pepperoni'],\n",
- " ['LEC001', '21', 'Computer Science', 'Other'],\n",
- " ['LEC001', '19', 'Computer Science', 'macaroni/pasta'],\n",
- " ['LEC001', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '20', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '', 'Computer Science', 'Other'],\n",
- " ['LEC001', '19', 'Business', 'basil/spinach'],\n",
- " ['LEC001', '22', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'sausage'],\n",
- " ['LEC001', '21', 'Business', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '25', 'Computer Science', 'mushroom'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '21', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC001', '20', 'Business', 'pineapple'],\n",
- " ['LEC001', '19', 'Data Science', 'tomato'],\n",
- " ['LEC001', '18', 'Engineering', 'sausage'],\n",
- " ['LEC001', '21', 'Business', 'pepperoni'],\n",
- " ['LEC001', '22', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '18', 'Computer Science', 'green pepper'],\n",
- " ['LEC001', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Engineering', 'sausage'],\n",
- " ['LEC001', '20', 'Data Science', 'Other'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'tomato']],\n",
- " 'LEC002': [['LEC002', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC002', '18', 'Social Science', 'sausage'],\n",
- " ['LEC002', '19', 'Business', 'pepperoni'],\n",
- " ['LEC002', '19', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC002', '32', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Computer Science', 'Other'],\n",
- " ['LEC002', '21', 'Natural Science', 'mushroom'],\n",
- " ['LEC002', '21', 'Natural Science', 'sausage'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '18', 'Natural Science', 'mushroom'],\n",
- " ['LEC002', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC002', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '46', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '23', 'Economics', 'pineapple'],\n",
- " ['LEC002', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC002', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC002', '18', 'Engineering', 'Other'],\n",
- " ['LEC002', '19', 'Engineering', 'Other'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '24', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC002', '19', 'Business', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Business', 'sausage'],\n",
- " ['LEC002', '22', 'Psychology', 'pepperoni'],\n",
- " ['LEC002', '20', 'Social Science', 'macaroni/pasta'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Data Science', 'sausage'],\n",
- " ['LEC002', '18', 'Data Science', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC002', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '20', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC002', '19', 'atmospheric and oceanic science', 'pineapple'],\n",
- " ['LEC002', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC002', '24', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '22', 'Neurobio and Econ', 'pineapple'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '20', 'Business', 'sausage'],\n",
- " ['LEC002', '20', 'Business', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '18', 'Computer Science', 'mushroom'],\n",
- " ['LEC002', '18', 'Engineering', 'Other'],\n",
- " ['LEC002', '19', 'Business', 'pineapple'],\n",
- " ['LEC002', '18', 'Data Science', 'Other'],\n",
- " ['LEC002', '19', 'Computer Science', 'pineapple'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '18', 'Undecided', 'pineapple'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Undecided', 'none (just cheese)'],\n",
- " ['LEC002', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '20', 'Social Science', 'sausage'],\n",
- " ['LEC002', '20', 'Engineering', 'tomato'],\n",
- " ['LEC002', '21', 'Geographic Information Systems', 'none (just cheese)'],\n",
- " ['LEC002', '21', 'Business', 'mushroom'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC002', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC002', '21', 'Social Science', 'pineapple'],\n",
- " ['LEC002', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '20', 'Social Science', 'basil/spinach'],\n",
- " ['LEC002', '21', 'Social Science', 'none (just cheese)'],\n",
- " ['LEC002', '18', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '20', 'Marketing and Information Systems', 'pepperoni'],\n",
- " ['LEC002', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '26', 'Natural Science', 'sausage'],\n",
- " ['LEC002', '20', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC002', '19', 'Social Science', 'pepperoni'],\n",
- " ['LEC002', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '19', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC002', '21', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '20', 'Business', 'none (just cheese)'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '25', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '21', 'Social Science', 'pepperoni'],\n",
- " ['LEC002', '21', 'Business', 'sausage'],\n",
- " ['LEC002', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'Other'],\n",
- " ['LEC002', '00', 'Engineering', 'Other'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Computer Science', 'mushroom'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '21', 'Data Science', 'Other'],\n",
- " ['LEC002', '20', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '20', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC002', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '20', 'Engineering', 'Other'],\n",
- " ['LEC002', '21', 'Data Science', 'mushroom'],\n",
- " ['LEC002', '20', 'Business', 'tomato'],\n",
- " ['LEC002', '18', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC002', '18', 'Biomedical Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Math', 'none (just cheese)'],\n",
- " ['LEC002', '18', 'Economics', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '20', 'Mathematics', 'sausage'],\n",
- " ['LEC002', '19', 'Data Science', 'sausage'],\n",
- " ['LEC002', '22', 'Business', 'pepperoni'],\n",
- " ['LEC002', '20', 'English Literature', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '18', 'Computer Science', 'Other'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Engineering', 'pineapple'],\n",
- " ['LEC002', '17', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '23', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '22', 'Natural Science', 'Other'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '18', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '19', 'Business', 'none (just cheese)'],\n",
- " ['LEC002', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC002', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '17', 'Natural Science', 'pineapple'],\n",
- " ['LEC002', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '18', 'Business', 'sausage'],\n",
- " ['LEC002', '20', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC002', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '23', 'Data Science', 'green pepper'],\n",
- " ['LEC002', '18', 'Engineering', 'green pepper'],\n",
- " ['LEC002', '26', 'Computer Science', 'pineapple'],\n",
- " ['LEC002', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC002', '22', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'undecided/maybe data science', 'green pepper'],\n",
- " ['LEC002', '20', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC002', '19', 'Data Science', 'Other'],\n",
- " ['LEC002', '26', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC002', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Business', 'sausage'],\n",
- " ['LEC002', '20', 'Data Science', 'sausage'],\n",
- " ['LEC002', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '18', 'Business', 'basil/spinach'],\n",
- " ['LEC002', '18', 'Business', 'mushroom'],\n",
- " ['LEC002', '20', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC002', '24', 'Math', 'tomato'],\n",
- " ['LEC002', '21', 'Data Science', 'mushroom'],\n",
- " ['LEC002', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC002', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'Other'],\n",
- " ['LEC002', '19', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC002', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '18', 'Business', 'sausage'],\n",
- " ['LEC002', '21', 'Data Science', 'sausage'],\n",
- " ['LEC002', '24', 'Natural Science', 'pepperoni'],\n",
- " ['LEC002', '20', 'Genetics', 'sausage'],\n",
- " ['LEC002', '33', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC002', '21', 'Business', 'Other'],\n",
- " ['LEC002', '18', 'Business', 'none (just cheese)'],\n",
- " ['LEC002', '21', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC002', '22', 'Natural Science', 'none (just cheese)'],\n",
- " ['LEC002', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC002', '18', 'Engineering', 'tomato'],\n",
- " ['LEC002', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '21', 'Economics', 'pepperoni'],\n",
- " ['LEC002', '19', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC002', '20', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'Data Science', 'mushroom']],\n",
- " 'LEC003': [['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'Other'],\n",
- " ['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '20', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Psychology/ Pre-law ', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Social Science', 'pepperoni'],\n",
- " ['LEC003', '19', 'Data Science', 'sausage'],\n",
- " ['LEC003', '17', 'Engineering', 'sausage'],\n",
- " ['LEC003', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Computer Science', 'tomato'],\n",
- " ['LEC003', '21', 'Business', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Natural Science', 'none (just cheese)'],\n",
- " ['LEC003', '23', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '21', 'Engineering', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '20', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Business', 'tomato'],\n",
- " ['LEC003', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '18', 'Engineering', 'sausage'],\n",
- " ['LEC003', '20', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '18', 'Data Science', 'mushroom'],\n",
- " ['LEC003', '18', 'Business', 'Other'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '21', 'Data Science', 'mushroom'],\n",
- " ['LEC003', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC003', '21', 'Natural Science', 'mushroom'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '21', 'Computer Science', 'Other'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '20', 'Engineering', 'sausage'],\n",
- " ['LEC003', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC003', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC003', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '22', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Engineering', 'Other'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '18', 'Statistics', 'none (just cheese)'],\n",
- " ['LEC003', '18', 'Engineering', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'pineapple'],\n",
- " ['LEC003', '19', 'mathematics', 'sausage'],\n",
- " ['LEC003', '22', 'Natural Science', 'sausage'],\n",
- " ['LEC003', '18', 'Business', 'mushroom'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '22', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '18', 'AMEP', 'pineapple'],\n",
- " ['LEC003', '21', 'Business', 'none (just cheese)'],\n",
- " ['LEC003', '28', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC003', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC003', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'tomato'],\n",
- " ['LEC003', '23', 'Engineering', 'Other'],\n",
- " ['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '21', 'Natural Science', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC003', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '18', 'Computer Science', 'mushroom'],\n",
- " ['LEC003', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Engineering', 'Other'],\n",
- " ['LEC003', '19', 'Business', 'mushroom'],\n",
- " ['LEC003', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Engineering', 'Other'],\n",
- " ['LEC003', '20', 'Computer Science', 'mushroom'],\n",
- " ['LEC003', '21', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC003', '18', 'Data Science', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '17', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '20', 'undecided', 'basil/spinach'],\n",
- " ['LEC003', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Data Science', 'Other'],\n",
- " ['LEC003', '19', 'Business', 'basil/spinach'],\n",
- " ['LEC003', '19', 'Statistics', 'basil/spinach'],\n",
- " ['LEC003', '20', 'Business', 'none (just cheese)'],\n",
- " ['LEC003', '18', 'Business', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Social Science', 'pineapple'],\n",
- " ['LEC003', '18', 'Engineering', 'Other'],\n",
- " ['LEC003', '25', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC003', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '18', 'Business', 'sausage'],\n",
- " ['LEC003', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC003', '20', 'communication arts', 'mushroom'],\n",
- " ['LEC003', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC003', '18', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '20', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC003', '20', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '18', 'Math', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '18', 'Engineering', 'sausage'],\n",
- " ['LEC003', '20', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC003', '21', 'Natural Science', 'sausage'],\n",
- " ['LEC003', '21', 'Economics with math emphasis', 'basil/spinach'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC003', '17', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC003', '20', 'Engineering', 'sausage'],\n",
- " ['LEC003', '22', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC003', '18', 'Business', 'macaroni/pasta'],\n",
- " ['LEC003', '16', 'Economics with a data science certificate ', 'pineapple'],\n",
- " ['LEC003', '20', 'Natural Science', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '00', 'Natural Science', 'Other'],\n",
- " ['LEC003', '18', 'Business', 'tomato'],\n",
- " ['LEC003', '20', 'Economics', 'pepperoni'],\n",
- " ['LEC003', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '21', 'Computer Science', 'mushroom'],\n",
- " ['LEC003', '17', 'Engineering', 'Other'],\n",
- " ['LEC003', '19', 'Natural Science', 'pepperoni'],\n",
- " ['LEC003', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '21', 'Natural Science', 'sausage'],\n",
- " ['LEC003', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '18', 'math', 'pineapple'],\n",
- " ['LEC003', '18', 'Computer Science', 'tomato'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC003', '30', 'Natural Science', 'pineapple'],\n",
- " ['LEC003', '29', 'Data Science', 'green pepper'],\n",
- " ['LEC003', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '20', 'Mathematics', 'pepperoni'],\n",
- " ['LEC003', '19', 'Social Science', 'basil/spinach'],\n",
- " ['LEC003', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '20', 'Data Science', 'mushroom'],\n",
- " ['LEC003', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '', 'Business', 'green pepper'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '22', 'Engineering', 'sausage'],\n",
- " ['LEC003', '25', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '17', 'Social Science', 'pepperoni'],\n",
- " ['LEC003', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '18', 'Data Science', 'pineapple']],\n",
- " 'LEC004': [['LEC004', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC004', '18', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC004', '20', 'Engineering', 'mushroom'],\n",
- " ['LEC004', '', 'Engineering', 'sausage'],\n",
- " ['LEC004', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '20', 'Data Science', 'sausage'],\n",
- " ['LEC004', '19', 'Data Science', 'Other'],\n",
- " ['LEC004', '21', 'Business', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC004', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC004', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC004', '18', 'Data Science', 'sausage'],\n",
- " ['LEC004', '19', 'Data Science', 'sausage'],\n",
- " ['LEC004', '20', 'Computer Science', 'macaroni/pasta'],\n",
- " ['LEC004', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '18', 'Data Science', 'sausage'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '21', 'Data Science', 'pineapple'],\n",
- " ['LEC004', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Social Science', 'sausage'],\n",
- " ['LEC004', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '20', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '20', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'Other'],\n",
- " ['LEC004', '19', 'Business', 'pineapple'],\n",
- " ['LEC004', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC004', '21', 'Business', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC004', '21', 'Data Science', 'pineapple'],\n",
- " ['LEC004', '21', 'Economics w/ Math Emphasis', 'pepperoni'],\n",
- " ['LEC004', '20', 'Natural Science', 'sausage'],\n",
- " ['LEC004', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC004', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '20', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC004', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC004', '19', 'Business', 'pepperoni'],\n",
- " ['LEC004', '18', 'Business', 'Other'],\n",
- " ['LEC004', '21', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC004', '18', 'Data Science', 'mushroom'],\n",
- " ['LEC004', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Business', 'mushroom'],\n",
- " ['LEC004', '18', 'undecided', 'sausage'],\n",
- " ['LEC004', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Statistics', 'pepperoni'],\n",
- " ['LEC004', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '19', 'Data Science', 'Other'],\n",
- " ['LEC004', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC004', '20', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC004', '22', 'Business', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC004', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC004', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Business', 'pepperoni'],\n",
- " ['LEC004', '00', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '20', 'Natural Science', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '20', 'Natural Science', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'tomato'],\n",
- " ['LEC004', '19', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC004', '20', 'Environmental Sciences ', 'none (just cheese)'],\n",
- " ['LEC004', '20', 'Engineering', 'mushroom'],\n",
- " ['LEC004', '21', 'Natural Science', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Data Science', 'sausage'],\n",
- " ['LEC004', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '22', 'Business', 'sausage'],\n",
- " ['LEC004', '18', 'undecided', 'pepperoni'],\n",
- " ['LEC004', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '24', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC004', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '20', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '27', 'Computer Science', 'sausage'],\n",
- " ['LEC004', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Natural Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '19', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC004', '20', 'Business', 'pepperoni'],\n",
- " ['LEC004', '20', 'Business', 'sausage'],\n",
- " ['LEC004', '21', 'Human Development and Communications', 'basil/spinach'],\n",
- " ['LEC004', '21', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC004', '18', 'Social Science', 'Other'],\n",
- " ['LEC004', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC004', '18', 'Statistics', 'macaroni/pasta'],\n",
- " ['LEC004', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '20', 'Engineering', 'mushroom'],\n",
- " ['LEC004', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Computer Science', 'pineapple'],\n",
- " ['LEC004', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '20', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC004', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC004', '21', 'Data Science', 'mushroom'],\n",
- " ['LEC004', '18', 'journalism', 'pepperoni'],\n",
- " ['LEC004', '21', 'Business', 'pineapple'],\n",
- " ['LEC004', '20', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '17', 'Computer Science', 'sausage'],\n",
- " ['LEC004', '19', 'Business', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '21', 'Data Science', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '20', 'Social Science', 'mushroom'],\n",
- " ['LEC004', '20', 'Business', 'mushroom'],\n",
- " ['LEC004', '18', 'undecided', 'pepperoni'],\n",
- " ['LEC004', '19', 'Computer Science', 'pineapple'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '20', 'Data Science', 'Other'],\n",
- " ['LEC004', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '20', 'Data Science', 'Other'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'sausage'],\n",
- " ['LEC004', '21', 'Natural Science', 'pineapple'],\n",
- " ['LEC004', '19', 'Math and Statistics', 'none (just cheese)'],\n",
- " ['LEC004', '18', 'Business', 'pineapple'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '', 'Data Science', 'sausage'],\n",
- " ['LEC004', '21', 'Natural Science', 'pineapple'],\n",
- " ['LEC004', '22', 'Natural Science', 'pineapple'],\n",
- " ['LEC004', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'green pepper'],\n",
- " ['LEC004', '21', 'Computer Science', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '22', 'Data Science', 'pineapple'],\n",
- " ['LEC004', '22', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '', 'AMEP', 'none (just cheese)'],\n",
- " ['LEC004', '23', 'Natural Science', 'pepperoni'],\n",
- " ['LEC004', '19', 'Business', 'pepperoni'],\n",
- " ['LEC004', '28', 'animal science', 'none (just cheese)'],\n",
- " ['LEC004', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC004', '18', 'Biochem', 'none (just cheese)'],\n",
- " ['LEC004', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '20', 'Social Science', 'sausage'],\n",
- " ['LEC004', '18', 'Engineering', 'sausage'],\n",
- " ['LEC004', '20', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC004', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC004', '', 'Engineering', 'Other'],\n",
- " ['LEC004', '18', 'Business', 'Other'],\n",
- " ['LEC004', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'Other'],\n",
- " ['LEC004', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni']],\n",
- " 'LEC005': [['LEC005', '', 'Computer Science', 'pepperoni'],\n",
- " ['LEC005', '18', 'Business', 'pepperoni'],\n",
- " ['LEC005', '20', 'Engineering', 'tomato'],\n",
- " ['LEC005', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC005', '21', 'Data Science', 'green pepper'],\n",
- " ['LEC005', '20', 'biology', 'tomato'],\n",
- " ['LEC005', '19', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC005', '19', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '20', 'Natural Science', 'mushroom'],\n",
- " ['LEC005', '18', 'Data Science', 'tomato'],\n",
- " ['LEC005', '18', 'Data Science', 'tomato'],\n",
- " ['LEC005', '21', 'Business', 'sausage'],\n",
- " ['LEC005', '20', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC005', '18', 'Undecided', 'Other'],\n",
- " ['LEC005', '20', 'Mathematics', 'pepperoni'],\n",
- " ['LEC005', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC005', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC005', '18', 'Data Science', 'mushroom'],\n",
- " ['LEC005', '21', 'math', 'sausage'],\n",
- " ['LEC005', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '19', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '18', 'Computer Science', 'Other'],\n",
- " ['LEC005', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC005', '31', 'Computer Science', 'pepperoni'],\n",
- " ['LEC005', '18', 'Data Science', 'tomato'],\n",
- " ['LEC005', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '22', 'Engineering', 'mushroom'],\n",
- " ['LEC005', '21', 'Agricultural and Applied Economics', 'sausage'],\n",
- " ['LEC005', '18', 'Computer Science', 'mushroom'],\n",
- " ['LEC005', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '21', 'Social Science', 'basil/spinach'],\n",
- " ['LEC005', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '17', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC005', '19', 'Business', 'pepperoni'],\n",
- " ['LEC005', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC005', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC005', '19', 'Computer Science', 'mushroom'],\n",
- " ['LEC005', '18', 'Computer Science', 'pineapple'],\n",
- " ['LEC005', '18', 'Natural Science', 'sausage'],\n",
- " ['LEC005', '20', 'Computer Science', 'pineapple'],\n",
- " ['LEC005', '23', 'Data Science', 'pepperoni'],\n",
- " ['LEC005', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '21', 'Engineering', 'basil/spinach'],\n",
- " ['LEC005', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC005', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '23', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC005', '24', 'Natural Science', 'pepperoni'],\n",
- " ['LEC005', '21', 'Business', 'tomato'],\n",
- " ['LEC005', '18', 'economics', 'sausage'],\n",
- " ['LEC005', '20', 'Business', 'pineapple'],\n",
- " ['LEC005', '21', 'Business', 'tomato'],\n",
- " ['LEC005', '19', 'Mathematics', 'pepperoni'],\n",
- " ['LEC005', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '20', 'Social Science', 'pepperoni'],\n",
- " ['LEC005', '22', 'Data Science', 'sausage'],\n",
- " ['LEC005', '18', 'Data Science', 'mushroom'],\n",
- " ['LEC005', '19', 'Computer Science', 'mushroom'],\n",
- " ['LEC005', '19', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC005', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '18', 'Computer Science', 'green pepper'],\n",
- " ['LEC005', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '37', 'Data Science', 'green pepper'],\n",
- " ['LEC005', '20', 'Business', 'mushroom'],\n",
- " ['LEC005', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '21', 'Business', 'sausage'],\n",
- " ['LEC005', '21', 'Applied Math Economics ', 'pepperoni'],\n",
- " ['LEC005', '20', 'Information Systems', 'pepperoni'],\n",
- " ['LEC005', '22', 'Computer Science', 'Other'],\n",
- " ['LEC005', '21', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC005', '21', 'Engineering', 'sausage'],\n",
- " ['LEC005', '18', 'Computer Science', 'mushroom'],\n",
- " ['LEC005', '21', 'English and Journalism', 'none (just cheese)'],\n",
- " ['LEC005', '21', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC005', '22', 'Computer Science', 'pepperoni'],\n",
- " ['LEC005', '18', 'Data Science', 'sausage'],\n",
- " ['LEC005', '22', 'Data Science', 'sausage'],\n",
- " ['LEC005', '18', 'Business', 'pepperoni'],\n",
- " ['LEC005', '21', 'Natural Science', 'mushroom'],\n",
- " ['LEC005', '20', 'Engineering', 'sausage'],\n",
- " ['LEC005', '20', 'Data Science', 'mushroom'],\n",
- " ['LEC005', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC005', '22', 'Data Science', 'mushroom'],\n",
- " ['LEC005', '22', 'Data Science', 'pineapple']]}"
- ]
- },
- "execution_count": 29,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "sec_buckets = bucketize(\"lecture\")\n",
- "sec_buckets"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Bucketize by location"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{'Computer Science': [['LEC001', '19', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC003', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Computer Science', 'tomato'],\n",
- " ['LEC002', '18', 'Computer Science', 'Other'],\n",
- " ['LEC004', '20', 'Computer Science', 'macaroni/pasta'],\n",
- " ['LEC001', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC001', '21', 'Computer Science', 'green pepper'],\n",
- " ['LEC003', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '23', 'Computer Science', 'tomato'],\n",
- " ['LEC004', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC003', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC004', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC004', '18', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC001', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '21', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC001', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC003', '21', 'Computer Science', 'Other'],\n",
- " ['LEC002', '24', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '18', 'Computer Science', 'mushroom'],\n",
- " ['LEC003', '22', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC003', '18', 'Computer Science', 'pineapple'],\n",
- " ['LEC002', '19', 'Computer Science', 'pineapple'],\n",
- " ['LEC005', '20', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC005', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Computer Science', 'mushroom'],\n",
- " ['LEC003', '18', 'Computer Science', 'mushroom'],\n",
- " ['LEC003', '20', 'Computer Science', 'mushroom'],\n",
- " ['LEC003', '21', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC003', '17', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC003', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC004', '00', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Computer Science', 'Other'],\n",
- " ['LEC004', '19', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC001', '19', 'Computer Science', 'mushroom'],\n",
- " ['LEC004', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '24', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC003', '20', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC001', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC004', '27', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '18', 'Computer Science', 'Other'],\n",
- " ['LEC003', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC001', '22', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC001', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC001', '20', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '18', 'Computer Science', 'mushroom'],\n",
- " ['LEC001', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '20', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC001', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC005', '31', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '21', 'Computer Science', 'sausage'],\n",
- " ['LEC004', '19', 'Computer Science', 'pineapple'],\n",
- " ['LEC004', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '22', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '25', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'Computer Science', 'mushroom'],\n",
- " ['LEC001', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC001', '18', 'Computer Science', 'pineapple'],\n",
- " ['LEC001', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC004', '20', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC002', '18', 'Computer Science', 'Other'],\n",
- " ['LEC002', '17', 'Computer Science', 'pepperoni'],\n",
- " ['LEC005', '18', 'Computer Science', 'mushroom'],\n",
- " ['LEC004', '20', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC003', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '17', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC005', '17', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC005', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '21', 'Computer Science', 'mushroom'],\n",
- " ['LEC002', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '17', 'Computer Science', 'Other'],\n",
- " ['LEC005', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC005', '19', 'Computer Science', 'mushroom'],\n",
- " ['LEC005', '18', 'Computer Science', 'pineapple'],\n",
- " ['LEC002', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC004', '19', 'Computer Science', 'pineapple'],\n",
- " ['LEC002', '26', 'Computer Science', 'pineapple'],\n",
- " ['LEC003', '18', 'Computer Science', 'tomato'],\n",
- " ['LEC005', '20', 'Computer Science', 'pineapple'],\n",
- " ['LEC004', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '22', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Computer Science', 'pineapple'],\n",
- " ['LEC002', '', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC005', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC005', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC002', '20', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC001', '18', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '21', 'Computer Science', 'pineapple'],\n",
- " ['LEC002', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '22', 'Computer Science', 'sausage'],\n",
- " ['LEC004', '21', 'Computer Science', 'sausage'],\n",
- " ['LEC003', '18', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '20', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '19', 'Computer Science', 'mushroom'],\n",
- " ['LEC005', '19', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC001', '20', 'Computer Science', 'mushroom'],\n",
- " ['LEC005', '18', 'Computer Science', 'green pepper'],\n",
- " ['LEC001', '19', 'Computer Science', 'pineapple'],\n",
- " ['LEC002', '33', 'Computer Science', 'basil/spinach'],\n",
- " ['LEC001', '21', 'Computer Science', 'Other'],\n",
- " ['LEC001', '19', 'Computer Science', 'macaroni/pasta'],\n",
- " ['LEC003', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC005', '22', 'Computer Science', 'Other'],\n",
- " ['LEC001', '', 'Computer Science', 'Other'],\n",
- " ['LEC004', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '18', 'Computer Science', 'mushroom'],\n",
- " ['LEC005', '19', 'Computer Science', 'pepperoni'],\n",
- " ['LEC005', '22', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '25', 'Computer Science', 'mushroom'],\n",
- " ['LEC002', '18', 'Computer Science', 'none (just cheese)'],\n",
- " ['LEC005', '19', 'Computer Science', 'sausage'],\n",
- " ['LEC005', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Computer Science', 'green pepper'],\n",
- " ['LEC001', '21', 'Computer Science', 'pepperoni'],\n",
- " ['LEC003', '20', 'Computer Science', 'pepperoni'],\n",
- " ['LEC004', '21', 'Computer Science', 'pepperoni']],\n",
- " 'Engineering': [['LEC002', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'Other'],\n",
- " ['LEC001', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC004', '18', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC001', '20', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '20', 'Engineering', 'mushroom'],\n",
- " ['LEC001', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '20', 'Engineering', 'pineapple'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC004', '18', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '32', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '17', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '20', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '23', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '21', 'Engineering', 'sausage'],\n",
- " ['LEC003', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC001', '18', 'Engineering', 'sausage'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC002', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '20', 'Engineering', 'basil/spinach'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '20', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC002', '46', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'Other'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC001', '20', 'Engineering', 'green pepper'],\n",
- " ['LEC003', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '18', 'Engineering', 'Other'],\n",
- " ['LEC003', '20', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '19', 'Engineering', 'Other'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '24', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '22', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Engineering', 'Other'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '29', 'Engineering', 'mushroom'],\n",
- " ['LEC004', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '20', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC004', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '20', 'Engineering', 'Other'],\n",
- " ['LEC004', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '20', 'Engineering', 'tomato'],\n",
- " ['LEC001', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC001', '22', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Engineering', 'Other'],\n",
- " ['LEC004', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC002', '18', 'Engineering', 'Other'],\n",
- " ['LEC003', '18', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '22', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '28', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'tomato'],\n",
- " ['LEC003', '23', 'Engineering', 'Other'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC004', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC003', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC001', '20', 'Engineering', 'Other'],\n",
- " ['LEC003', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Engineering', 'Other'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Engineering', 'Other'],\n",
- " ['LEC001', '18', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC004', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '18', 'Engineering', 'Other'],\n",
- " ['LEC003', '25', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Engineering', 'tomato'],\n",
- " ['LEC003', '18', 'Engineering', 'sausage'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '20', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC004', '19', 'Engineering', 'tomato'],\n",
- " ['LEC001', '28', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC004', '20', 'Engineering', 'mushroom'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC003', '18', 'Engineering', 'sausage'],\n",
- " ['LEC004', '20', 'Engineering', 'sausage'],\n",
- " ['LEC002', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '20', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC004', '20', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '18', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC001', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '20', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '18', 'Engineering', 'mushroom'],\n",
- " ['LEC001', '21', 'Engineering', 'Other'],\n",
- " ['LEC001', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '21', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC003', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC003', '17', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC003', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC001', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '18', 'Engineering', 'tomato'],\n",
- " ['LEC004', '20', 'Engineering', 'mushroom'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '20', 'Engineering', 'Other'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'green pepper'],\n",
- " ['LEC004', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC001', '18', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC005', '22', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '21', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'Other'],\n",
- " ['LEC002', '00', 'Engineering', 'Other'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '20', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '20', 'Engineering', 'Other'],\n",
- " ['LEC001', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '18', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '18', 'Engineering', 'mushroom'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC003', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC005', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '19', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'mushroom'],\n",
- " ['LEC004', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '17', 'Engineering', 'Other'],\n",
- " ['LEC001', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '19', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'tomato'],\n",
- " ['LEC005', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC004', '20', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC001', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'green pepper'],\n",
- " ['LEC003', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '21', 'Engineering', 'basil/spinach'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '22', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC001', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '18', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '21', 'Engineering', 'basil/spinach'],\n",
- " ['LEC005', '19', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Engineering', 'green pepper'],\n",
- " ['LEC005', '19', 'Engineering', 'sausage'],\n",
- " ['LEC003', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '21', 'Engineering', 'sausage'],\n",
- " ['LEC001', '18', 'Engineering', 'basil/spinach'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'sausage'],\n",
- " ['LEC004', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC004', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '22', 'Engineering', 'basil/spinach'],\n",
- " ['LEC001', '26', 'Engineering', 'pepperoni'],\n",
- " ['LEC002', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '18', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '18', 'Engineering', 'Other'],\n",
- " ['LEC002', '19', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC001', '20', 'Engineering', 'sausage'],\n",
- " ['LEC005', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '22', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '18', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '21', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'pineapple'],\n",
- " ['LEC003', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '22', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'pepperoni'],\n",
- " ['LEC003', '25', 'Engineering', 'pepperoni'],\n",
- " ['LEC005', '21', 'Engineering', 'sausage'],\n",
- " ['LEC003', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC001', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '19', 'Engineering', 'sausage'],\n",
- " ['LEC005', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '20', 'Engineering', 'sausage'],\n",
- " ['LEC004', '18', 'Engineering', 'sausage'],\n",
- " ['LEC001', '21', 'Engineering', 'macaroni/pasta'],\n",
- " ['LEC002', '18', 'Engineering', 'tomato'],\n",
- " ['LEC004', '19', 'Engineering', 'none (just cheese)'],\n",
- " ['LEC004', '', 'Engineering', 'Other'],\n",
- " ['LEC001', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Engineering', 'pepperoni'],\n",
- " ['LEC004', '19', 'Engineering', 'Other'],\n",
- " ['LEC001', '18', 'Engineering', 'sausage'],\n",
- " ['LEC002', '20', 'Engineering', 'sausage'],\n",
- " ['LEC001', '19', 'Engineering', 'tomato'],\n",
- " ['LEC004', '18', 'Engineering', 'pepperoni']],\n",
- " 'Business': [['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC001', '20', 'Business', 'mushroom'],\n",
- " ['LEC004', '21', 'Business', 'sausage'],\n",
- " ['LEC002', '19', 'Business', 'pepperoni'],\n",
- " ['LEC001', '21', 'Business', 'basil/spinach'],\n",
- " ['LEC003', '21', 'Business', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Business', 'tomato'],\n",
- " ['LEC004', '19', 'Business', 'pineapple'],\n",
- " ['LEC004', '21', 'Business', 'sausage'],\n",
- " ['LEC003', '18', 'Business', 'Other'],\n",
- " ['LEC001', '22', 'Business', 'mushroom'],\n",
- " ['LEC002', '19', 'Business', 'pepperoni'],\n",
- " ['LEC002', '19', 'Business', 'sausage'],\n",
- " ['LEC004', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC004', '18', 'Business', 'Other'],\n",
- " ['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC004', '19', 'Business', 'mushroom'],\n",
- " ['LEC002', '20', 'Business', 'sausage'],\n",
- " ['LEC002', '20', 'Business', 'sausage'],\n",
- " ['LEC005', '18', 'Business', 'pepperoni'],\n",
- " ['LEC001', '18', 'Business', 'mushroom'],\n",
- " ['LEC001', '19', 'Business', 'sausage'],\n",
- " ['LEC001', '18', 'Business', 'basil/spinach'],\n",
- " ['LEC002', '19', 'Business', 'pineapple'],\n",
- " ['LEC003', '18', 'Business', 'mushroom'],\n",
- " ['LEC005', '21', 'Business', 'sausage'],\n",
- " ['LEC003', '21', 'Business', 'none (just cheese)'],\n",
- " ['LEC004', '22', 'Business', 'pepperoni'],\n",
- " ['LEC003', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '19', 'Business', 'mushroom'],\n",
- " ['LEC004', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '19', 'Business', 'basil/spinach'],\n",
- " ['LEC003', '20', 'Business', 'none (just cheese)'],\n",
- " ['LEC003', '18', 'Business', 'sausage'],\n",
- " ['LEC001', '19', 'Business', 'mushroom'],\n",
- " ['LEC003', '18', 'Business', 'sausage'],\n",
- " ['LEC001', '20', 'Business', 'pepperoni'],\n",
- " ['LEC001', '18', 'Business', 'pepperoni'],\n",
- " ['LEC001', '22', 'Business', 'green pepper'],\n",
- " ['LEC002', '21', 'Business', 'mushroom'],\n",
- " ['LEC004', '22', 'Business', 'sausage'],\n",
- " ['LEC001', '20', 'Business', 'pineapple'],\n",
- " ['LEC001', '21', 'Business', 'pepperoni'],\n",
- " ['LEC004', '20', 'Business', 'pepperoni'],\n",
- " ['LEC001', '20', 'Business', 'pepperoni'],\n",
- " ['LEC001', '20', 'Business', 'sausage'],\n",
- " ['LEC001', '23', 'Business', 'pineapple'],\n",
- " ['LEC001', '20', 'Business', 'pepperoni'],\n",
- " ['LEC004', '20', 'Business', 'sausage'],\n",
- " ['LEC001', '20', 'Business', 'sausage'],\n",
- " ['LEC002', '20', 'Business', 'none (just cheese)'],\n",
- " ['LEC001', '19', 'Business', 'pepperoni'],\n",
- " ['LEC003', '18', 'Business', 'macaroni/pasta'],\n",
- " ['LEC001', '19', 'Business', 'basil/spinach'],\n",
- " ['LEC002', '21', 'Business', 'sausage'],\n",
- " ['LEC002', '20', 'Business', 'tomato'],\n",
- " ['LEC002', '22', 'Business', 'pepperoni'],\n",
- " ['LEC003', '18', 'Business', 'tomato'],\n",
- " ['LEC001', '20', 'Business', 'pepperoni'],\n",
- " ['LEC004', '21', 'Business', 'pineapple'],\n",
- " ['LEC001', '21', 'Business', 'mushroom'],\n",
- " ['LEC004', '19', 'Business', 'pepperoni'],\n",
- " ['LEC002', '19', 'Business', 'none (just cheese)'],\n",
- " ['LEC005', '19', 'Business', 'pepperoni'],\n",
- " ['LEC001', '21', 'Business', 'sausage'],\n",
- " ['LEC002', '18', 'Business', 'sausage'],\n",
- " ['LEC004', '20', 'Business', 'mushroom'],\n",
- " ['LEC001', '19', 'Business', 'sausage'],\n",
- " ['LEC002', '20', 'Business', 'sausage'],\n",
- " ['LEC004', '18', 'Business', 'pineapple'],\n",
- " ['LEC002', '18', 'Business', 'basil/spinach'],\n",
- " ['LEC002', '18', 'Business', 'mushroom'],\n",
- " ['LEC005', '21', 'Business', 'tomato'],\n",
- " ['LEC001', '22', 'Business', 'mushroom'],\n",
- " ['LEC001', '21', 'Business', 'pepperoni'],\n",
- " ['LEC005', '20', 'Business', 'pineapple'],\n",
- " ['LEC005', '21', 'Business', 'tomato'],\n",
- " ['LEC002', '18', 'Business', 'sausage'],\n",
- " ['LEC004', '19', 'Business', 'pepperoni'],\n",
- " ['LEC005', '20', 'Business', 'mushroom'],\n",
- " ['LEC005', '21', 'Business', 'sausage'],\n",
- " ['LEC003', '', 'Business', 'green pepper'],\n",
- " ['LEC001', '20', 'Business', 'pepperoni'],\n",
- " ['LEC002', '21', 'Business', 'Other'],\n",
- " ['LEC001', '19', 'Business', 'basil/spinach'],\n",
- " ['LEC001', '21', 'Business', 'sausage'],\n",
- " ['LEC002', '18', 'Business', 'none (just cheese)'],\n",
- " ['LEC005', '18', 'Business', 'pepperoni'],\n",
- " ['LEC001', '20', 'Business', 'pineapple'],\n",
- " ['LEC001', '21', 'Business', 'pepperoni'],\n",
- " ['LEC004', '18', 'Business', 'Other']],\n",
- " 'Data Science': [['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC004', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '20', 'Data Science', 'sausage'],\n",
- " ['LEC004', '19', 'Data Science', 'Other'],\n",
- " ['LEC002', '19', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC003', '19', 'Data Science', 'sausage'],\n",
- " ['LEC004', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC003', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC004', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Data Science', 'sausage'],\n",
- " ['LEC004', '19', 'Data Science', 'sausage'],\n",
- " ['LEC004', '18', 'Data Science', 'sausage'],\n",
- " ['LEC004', '21', 'Data Science', 'pineapple'],\n",
- " ['LEC004', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '25', 'Data Science', 'green pepper'],\n",
- " ['LEC002', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC004', '21', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '19', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC003', '18', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC002', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC004', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC003', '21', 'Data Science', 'mushroom'],\n",
- " ['LEC004', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC003', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '19', 'Data Science', 'pineapple'],\n",
- " ['LEC002', '20', 'Data Science', 'sausage'],\n",
- " ['LEC001', '20', 'Data Science', 'tomato'],\n",
- " ['LEC002', '18', 'Data Science', 'sausage'],\n",
- " ['LEC001', '30', 'Data Science', 'basil/spinach'],\n",
- " ['LEC001', '35', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC004', '18', 'Data Science', 'mushroom'],\n",
- " ['LEC002', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'mushroom'],\n",
- " ['LEC002', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC003', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC003', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC003', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '23', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '20', 'Data Science', 'basil/spinach'],\n",
- " ['LEC004', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'sausage'],\n",
- " ['LEC004', '19', 'Data Science', 'Other'],\n",
- " ['LEC005', '21', 'Data Science', 'green pepper'],\n",
- " ['LEC005', '19', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC005', '19', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC002', '18', 'Data Science', 'Other'],\n",
- " ['LEC005', '18', 'Data Science', 'tomato'],\n",
- " ['LEC005', '18', 'Data Science', 'tomato'],\n",
- " ['LEC004', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC004', '20', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC003', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC003', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '18', 'Data Science', 'mushroom'],\n",
- " ['LEC004', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC001', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC003', '18', 'Data Science', 'sausage'],\n",
- " ['LEC003', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC003', '19', 'Data Science', 'Other'],\n",
- " ['LEC003', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '21', 'Data Science', 'sausage'],\n",
- " ['LEC003', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'sausage'],\n",
- " ['LEC001', '20', 'Data Science', 'sausage'],\n",
- " ['LEC003', '20', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC005', '19', 'Data Science', 'pineapple'],\n",
- " ['LEC004', '18', 'Data Science', 'sausage'],\n",
- " ['LEC004', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '22', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC004', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC004', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC005', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '21', 'Data Science', 'mushroom'],\n",
- " ['LEC004', '19', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC001', '17', 'Data Science', 'Other'],\n",
- " ['LEC001', '19', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '18', 'Data Science', 'Other'],\n",
- " ['LEC001', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '21', 'Data Science', 'Other'],\n",
- " ['LEC001', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC004', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC003', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC005', '18', 'Data Science', 'tomato'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC004', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '22', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Data Science', 'sausage'],\n",
- " ['LEC002', '21', 'Data Science', 'Other'],\n",
- " ['LEC001', '00', 'Data Science', 'Other'],\n",
- " ['LEC002', '20', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '21', 'Data Science', 'mushroom'],\n",
- " ['LEC002', '18', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC002', '19', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC004', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC002', '23', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '21', 'Data Science', 'mushroom'],\n",
- " ['LEC005', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '22', 'Data Science', 'sausage'],\n",
- " ['LEC002', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC005', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC005', '20', 'Data Science', 'pineapple'],\n",
- " ['LEC004', '21', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC003', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC002', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '23', 'Data Science', 'green pepper'],\n",
- " ['LEC001', '18', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '18', 'Data Science', 'basil/spinach'],\n",
- " ['LEC004', '20', 'Data Science', 'Other'],\n",
- " ['LEC002', '20', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC002', '19', 'Data Science', 'Other'],\n",
- " ['LEC001', '21', 'Data Science', 'basil/spinach'],\n",
- " ['LEC001', '21', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC004', '20', 'Data Science', 'Other'],\n",
- " ['LEC001', '00', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '34', 'Data Science', 'tomato'],\n",
- " ['LEC004', '', 'Data Science', 'sausage'],\n",
- " ['LEC005', '23', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '20', 'Data Science', 'sausage'],\n",
- " ['LEC001', '19', 'Data Science', 'sausage'],\n",
- " ['LEC002', '21', 'Data Science', 'mushroom'],\n",
- " ['LEC003', '29', 'Data Science', 'green pepper'],\n",
- " ['LEC005', '23', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC004', '22', 'Data Science', 'pineapple'],\n",
- " ['LEC002', '18', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC003', '20', 'Data Science', 'mushroom'],\n",
- " ['LEC002', '19', 'Data Science', 'macaroni/pasta'],\n",
- " ['LEC005', '22', 'Data Science', 'sausage'],\n",
- " ['LEC005', '18', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '22', 'Data Science', 'pineapple'],\n",
- " ['LEC002', '21', 'Data Science', 'sausage'],\n",
- " ['LEC005', '37', 'Data Science', 'green pepper'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '22', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Data Science', 'sausage'],\n",
- " ['LEC005', '21', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '18', 'Data Science', 'sausage'],\n",
- " ['LEC005', '22', 'Data Science', 'sausage'],\n",
- " ['LEC002', '21', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC005', '20', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC004', '20', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC001', '19', 'Data Science', 'tomato'],\n",
- " ['LEC005', '22', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '22', 'Data Science', 'mushroom'],\n",
- " ['LEC002', '19', 'Data Science', 'none (just cheese)'],\n",
- " ['LEC004', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC003', '18', 'Data Science', 'pineapple'],\n",
- " ['LEC005', '22', 'Data Science', 'pineapple'],\n",
- " ['LEC001', '20', 'Data Science', 'Other'],\n",
- " ['LEC002', '20', 'Data Science', 'pepperoni'],\n",
- " ['LEC002', '19', 'Data Science', 'mushroom'],\n",
- " ['LEC001', '19', 'Data Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Data Science', 'pepperoni']],\n",
- " 'not sure yet but maybe biology ': [['LEC001',\n",
- " '19',\n",
- " 'not sure yet but maybe biology ',\n",
- " 'none (just cheese)']],\n",
- " 'Psychology/ Pre-law ': [['LEC003',\n",
- " '19',\n",
- " 'Psychology/ Pre-law ',\n",
- " 'pepperoni']],\n",
- " 'Social Science': [['LEC002', '18', 'Social Science', 'sausage'],\n",
- " ['LEC003', '19', 'Social Science', 'pepperoni'],\n",
- " ['LEC004', '18', 'Social Science', 'sausage'],\n",
- " ['LEC002', '20', 'Social Science', 'macaroni/pasta'],\n",
- " ['LEC001', '18', 'Social Science', 'tomato'],\n",
- " ['LEC001', '18', 'Social Science', 'pineapple'],\n",
- " ['LEC003', '19', 'Social Science', 'pineapple'],\n",
- " ['LEC002', '20', 'Social Science', 'sausage'],\n",
- " ['LEC002', '21', 'Social Science', 'pineapple'],\n",
- " ['LEC002', '20', 'Social Science', 'basil/spinach'],\n",
- " ['LEC002', '21', 'Social Science', 'none (just cheese)'],\n",
- " ['LEC001', '', 'Social Science', 'Other'],\n",
- " ['LEC004', '18', 'Social Science', 'Other'],\n",
- " ['LEC002', '19', 'Social Science', 'pepperoni'],\n",
- " ['LEC001', '18', 'Social Science', 'pepperoni'],\n",
- " ['LEC002', '21', 'Social Science', 'pepperoni'],\n",
- " ['LEC005', '21', 'Social Science', 'basil/spinach'],\n",
- " ['LEC004', '20', 'Social Science', 'mushroom'],\n",
- " ['LEC001', '25', 'Social Science', 'Other'],\n",
- " ['LEC001', '23', 'Social Science', 'tomato'],\n",
- " ['LEC003', '19', 'Social Science', 'basil/spinach'],\n",
- " ['LEC005', '20', 'Social Science', 'pepperoni'],\n",
- " ['LEC004', '20', 'Social Science', 'sausage'],\n",
- " ['LEC003', '17', 'Social Science', 'pepperoni']],\n",
- " 'Natural Science': [['LEC003', '19', 'Natural Science', 'none (just cheese)'],\n",
- " ['LEC002', '21', 'Natural Science', 'mushroom'],\n",
- " ['LEC002', '21', 'Natural Science', 'sausage'],\n",
- " ['LEC002', '18', 'Natural Science', 'mushroom'],\n",
- " ['LEC004', '20', 'Natural Science', 'sausage'],\n",
- " ['LEC004', '20', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC001', '20', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC003', '21', 'Natural Science', 'mushroom'],\n",
- " ['LEC002', '20', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC001', '22', 'Natural Science', 'sausage'],\n",
- " ['LEC005', '20', 'Natural Science', 'mushroom'],\n",
- " ['LEC003', '22', 'Natural Science', 'sausage'],\n",
- " ['LEC001', '21', 'Natural Science', 'pepperoni'],\n",
- " ['LEC003', '21', 'Natural Science', 'sausage'],\n",
- " ['LEC004', '20', 'Natural Science', 'pepperoni'],\n",
- " ['LEC004', '20', 'Natural Science', 'sausage'],\n",
- " ['LEC004', '21', 'Natural Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Natural Science', 'sausage'],\n",
- " ['LEC003', '21', 'Natural Science', 'sausage'],\n",
- " ['LEC004', '19', 'Natural Science', 'pepperoni'],\n",
- " ['LEC001', '19', 'Natural Science', 'macaroni/pasta'],\n",
- " ['LEC001', '20', 'Natural Science', 'green pepper'],\n",
- " ['LEC002', '26', 'Natural Science', 'sausage'],\n",
- " ['LEC001', '20', 'Natural Science', 'Other'],\n",
- " ['LEC002', '19', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC001', '18', 'Natural Science', 'none (just cheese)'],\n",
- " ['LEC003', '20', 'Natural Science', 'pineapple'],\n",
- " ['LEC001', '18', 'Natural Science', 'pineapple'],\n",
- " ['LEC003', '00', 'Natural Science', 'Other'],\n",
- " ['LEC002', '22', 'Natural Science', 'Other'],\n",
- " ['LEC002', '17', 'Natural Science', 'pineapple'],\n",
- " ['LEC001', '21', 'Natural Science', 'sausage'],\n",
- " ['LEC003', '19', 'Natural Science', 'pepperoni'],\n",
- " ['LEC003', '21', 'Natural Science', 'sausage'],\n",
- " ['LEC005', '18', 'Natural Science', 'sausage'],\n",
- " ['LEC002', '26', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC001', '21', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC003', '30', 'Natural Science', 'pineapple'],\n",
- " ['LEC004', '21', 'Natural Science', 'pineapple'],\n",
- " ['LEC004', '21', 'Natural Science', 'pineapple'],\n",
- " ['LEC004', '22', 'Natural Science', 'pineapple'],\n",
- " ['LEC001', '25', 'Natural Science', 'pepperoni'],\n",
- " ['LEC005', '24', 'Natural Science', 'pepperoni'],\n",
- " ['LEC001', '22', 'Natural Science', 'sausage'],\n",
- " ['LEC004', '23', 'Natural Science', 'pepperoni'],\n",
- " ['LEC001', '20', 'Natural Science', 'sausage'],\n",
- " ['LEC001', '27', 'Natural Science', 'pepperoni'],\n",
- " ['LEC001', '21', 'Natural Science', 'Other'],\n",
- " ['LEC002', '24', 'Natural Science', 'pepperoni'],\n",
- " ['LEC005', '21', 'Natural Science', 'basil/spinach'],\n",
- " ['LEC005', '21', 'Natural Science', 'mushroom'],\n",
- " ['LEC002', '22', 'Natural Science', 'none (just cheese)']],\n",
- " 'Economics': [['LEC002', '23', 'Economics', 'pineapple'],\n",
- " ['LEC001', '20', 'Economics', 'pineapple'],\n",
- " ['LEC002', '18', 'Economics', 'pepperoni'],\n",
- " ['LEC003', '20', 'Economics', 'pepperoni'],\n",
- " ['LEC002', '21', 'Economics', 'pepperoni']],\n",
- " 'Economics w/ Math Emphasis': [['LEC004',\n",
- " '21',\n",
- " 'Economics w/ Math Emphasis',\n",
- " 'pepperoni']],\n",
- " 'Accounting': [['LEC001', '18', 'Accounting', 'pepperoni']],\n",
- " 'Psychology': [['LEC002', '22', 'Psychology', 'pepperoni']],\n",
- " 'atmospheric and oceanic science': [['LEC002',\n",
- " '19',\n",
- " 'atmospheric and oceanic science',\n",
- " 'pineapple']],\n",
- " 'Biomedical Engineering': [['LEC001',\n",
- " '20',\n",
- " 'Biomedical Engineering',\n",
- " 'macaroni/pasta'],\n",
- " ['LEC002', '18', 'Biomedical Engineering', 'sausage']],\n",
- " 'undecided': [['LEC004', '18', 'undecided', 'sausage'],\n",
- " ['LEC003', '20', 'undecided', 'basil/spinach'],\n",
- " ['LEC004', '18', 'undecided', 'pepperoni'],\n",
- " ['LEC004', '18', 'undecided', 'pepperoni']],\n",
- " 'Neurobio and Econ': [['LEC002', '22', 'Neurobio and Econ', 'pineapple']],\n",
- " 'Statistics': [['LEC004', '18', 'Statistics', 'pepperoni'],\n",
- " ['LEC003', '18', 'Statistics', 'none (just cheese)'],\n",
- " ['LEC003', '19', 'Statistics', 'basil/spinach'],\n",
- " ['LEC004', '18', 'Statistics', 'macaroni/pasta'],\n",
- " ['LEC001', '20', 'Statistics', 'mushroom'],\n",
- " ['LEC001', '18', 'Statistics', 'pepperoni']],\n",
- " 'biology': [['LEC005', '20', 'biology', 'tomato']],\n",
- " 'mathematics': [['LEC003', '19', 'mathematics', 'sausage']],\n",
- " 'AMEP': [['LEC003', '18', 'AMEP', 'pineapple'],\n",
- " ['LEC004', '', 'AMEP', 'none (just cheese)']],\n",
- " 'Undecided': [['LEC005', '18', 'Undecided', 'Other'],\n",
- " ['LEC002', '18', 'Undecided', 'pineapple'],\n",
- " ['LEC002', '19', 'Undecided', 'none (just cheese)']],\n",
- " 'Mathematics': [['LEC005', '20', 'Mathematics', 'pepperoni'],\n",
- " ['LEC002', '20', 'Mathematics', 'sausage'],\n",
- " ['LEC003', '20', 'Mathematics', 'pepperoni'],\n",
- " ['LEC005', '19', 'Mathematics', 'pepperoni']],\n",
- " 'math': [['LEC005', '21', 'math', 'sausage'],\n",
- " ['LEC003', '18', 'math', 'pineapple']],\n",
- " 'communication arts': [['LEC003', '20', 'communication arts', 'mushroom']],\n",
- " 'Geographic Information Systems': [['LEC002',\n",
- " '21',\n",
- " 'Geographic Information Systems',\n",
- " 'none (just cheese)']],\n",
- " 'Math': [['LEC003', '18', 'Math', 'pepperoni'],\n",
- " ['LEC002', '20', 'Math', 'none (just cheese)'],\n",
- " ['LEC002', '24', 'Math', 'tomato']],\n",
- " 'Environmental Sciences ': [['LEC004',\n",
- " '20',\n",
- " 'Environmental Sciences ',\n",
- " 'none (just cheese)']],\n",
- " 'Economics with math emphasis': [['LEC003',\n",
- " '21',\n",
- " 'Economics with math emphasis',\n",
- " 'basil/spinach']],\n",
- " 'statistics': [['LEC001', '20', 'statistics', 'sausage'],\n",
- " ['LEC001', '22', 'statistics', 'pepperoni']],\n",
- " 'Public Policy': [['LEC001', '21', 'Public Policy', 'pepperoni']],\n",
- " 'Information Systems': [['LEC001', '20', 'Information Systems', 'Other'],\n",
- " ['LEC005', '20', 'Information Systems', 'pepperoni']],\n",
- " 'Marketing and Information Systems': [['LEC002',\n",
- " '20',\n",
- " 'Marketing and Information Systems',\n",
- " 'pepperoni']],\n",
- " 'STATS': [['LEC001', '21', 'STATS', 'basil/spinach']],\n",
- " 'Mechanical Engineering': [['LEC001',\n",
- " '23',\n",
- " 'Mechanical Engineering',\n",
- " 'pepperoni']],\n",
- " 'Human Development and Communications': [['LEC004',\n",
- " '21',\n",
- " 'Human Development and Communications',\n",
- " 'basil/spinach']],\n",
- " 'Meteorology or Oceanography': [['LEC001',\n",
- " '20',\n",
- " 'Meteorology or Oceanography',\n",
- " 'basil/spinach']],\n",
- " 'economics': [['LEC001', '19', 'economics', 'none (just cheese)'],\n",
- " ['LEC005', '18', 'economics', 'sausage']],\n",
- " 'Economics with a data science certificate ': [['LEC003',\n",
- " '16',\n",
- " 'Economics with a data science certificate ',\n",
- " 'pineapple']],\n",
- " 'Geography/GIS': [['LEC001', '20', 'Geography/GIS', 'pineapple']],\n",
- " 'Agricultural and Applied Economics': [['LEC005',\n",
- " '21',\n",
- " 'Agricultural and Applied Economics',\n",
- " 'sausage']],\n",
- " 'chemistry': [['LEC001', '20', 'chemistry', 'pepperoni']],\n",
- " 'English Literature': [['LEC002', '20', 'English Literature', 'pepperoni']],\n",
- " 'journalism': [['LEC004', '18', 'journalism', 'pepperoni']],\n",
- " 'undecided/maybe data science': [['LEC002',\n",
- " '19',\n",
- " 'undecided/maybe data science',\n",
- " 'green pepper']],\n",
- " 'Math and Statistics': [['LEC004',\n",
- " '19',\n",
- " 'Math and Statistics',\n",
- " 'none (just cheese)']],\n",
- " 'Applied Math': [['LEC001', '18', 'Applied Math', 'pepperoni']],\n",
- " 'animal science': [['LEC004', '28', 'animal science', 'none (just cheese)']],\n",
- " 'Applied Math Economics ': [['LEC005',\n",
- " '21',\n",
- " 'Applied Math Economics ',\n",
- " 'pepperoni']],\n",
- " 'Genetics': [['LEC002', '20', 'Genetics', 'sausage']],\n",
- " 'Biochem': [['LEC004', '18', 'Biochem', 'none (just cheese)']],\n",
- " 'English and Journalism': [['LEC005',\n",
- " '21',\n",
- " 'English and Journalism',\n",
- " 'none (just cheese)']]}"
- ]
- },
- "execution_count": 30,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "major_buckets = bucketize(\"major\")\n",
- "major_buckets"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Write a function to compute the average speed per bucket"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 31,
- "metadata": {},
- "outputs": [],
- "source": [
- "def avg_per_bucket(groups, avg_col_name):\n",
- " averages = {}\n",
- " for bucket_name in groups:\n",
- " bucket_rows = groups[bucket_name]\n",
- " averages[bucket_name] = col_avg(bucket_rows, avg_col_name)\n",
- " return averages"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### What is the *average tornado age* per *section*?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 32,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{'LEC001': 19.6,\n",
- " 'LEC002': 19.7,\n",
- " 'LEC003': 19.7,\n",
- " 'LEC004': 19.7,\n",
- " 'LEC005': 19.6}"
- ]
- },
- "execution_count": 32,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "avg_per_bucket(sec_buckets, \"age\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### What is the *average tornado speed* per *location*?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 33,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{'Computer Science': 19.5,\n",
- " 'Engineering': 19.5,\n",
- " 'Business': 19.3,\n",
- " 'Data Science': 19.7,\n",
- " 'not sure yet but maybe biology ': 19.0,\n",
- " 'Psychology/ Pre-law ': 19.0,\n",
- " 'Social Science': 19.0,\n",
- " 'Natural Science': 19.2,\n",
- " 'Economics': 18.8,\n",
- " 'Economics w/ Math Emphasis': 19.0,\n",
- " 'Accounting': 19.0,\n",
- " 'Psychology': 19.0,\n",
- " 'atmospheric and oceanic science': 19.0,\n",
- " 'Biomedical Engineering': 18.5,\n",
- " 'undecided': 18.8,\n",
- " 'Neurobio and Econ': 19.0,\n",
- " 'Statistics': 19.0,\n",
- " 'biology': 19.0,\n",
- " 'mathematics': 19.0,\n",
- " 'AMEP': 18.5,\n",
- " 'Undecided': 18.7,\n",
- " 'Mathematics': 18.8,\n",
- " 'math': 18.5,\n",
- " 'communication arts': 19.0,\n",
- " 'Geographic Information Systems': 19.0,\n",
- " 'Math': 18.7,\n",
- " 'Environmental Sciences ': 19.0,\n",
- " 'Economics with math emphasis': 19.0,\n",
- " 'statistics': 18.5,\n",
- " 'Public Policy': 19.0,\n",
- " 'Information Systems': 18.5,\n",
- " 'Marketing and Information Systems': 19.0,\n",
- " 'STATS': 19.0,\n",
- " 'Mechanical Engineering': 19.0,\n",
- " 'Human Development and Communications': 19.0,\n",
- " 'Meteorology or Oceanography': 19.0,\n",
- " 'economics': 18.5,\n",
- " 'Economics with a data science certificate ': 19.0,\n",
- " 'Geography/GIS': 19.0,\n",
- " 'Agricultural and Applied Economics': 19.0,\n",
- " 'chemistry': 19.0,\n",
- " 'English Literature': 19.0,\n",
- " 'journalism': 19.0,\n",
- " 'undecided/maybe data science': 19.0,\n",
- " 'Math and Statistics': 19.0,\n",
- " 'Applied Math': 19.0,\n",
- " 'animal science': 19.0,\n",
- " 'Applied Math Economics ': 19.0,\n",
- " 'Genetics': 19.0,\n",
- " 'Biochem': 19.0,\n",
- " 'English and Journalism': 19.0}"
- ]
- },
- "execution_count": 33,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "avg_per_bucket(major_buckets, \"age\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Process a CSV file into a list of dictionaries"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 34,
- "metadata": {},
- "outputs": [],
- "source": [
- "def transform(header, data):\n",
- " dict_list = [] #should be defined outside the for loop, because it stores the entire data\n",
- " \n",
- " for row in data:\n",
- " new_row = {} #should be defined inside the for loop, because it represents one row as a dictionary\n",
- " for i in range(len(header)):\n",
- " new_row[header[i]] = row[i]\n",
- " dict_list.append(new_row)\n",
- " return dict_list\n",
- " \n",
- "transformed_data = transform(header, data)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 35,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{'lecture': 'LEC001',\n",
- " 'age': '19',\n",
- " 'major': 'Computer Science',\n",
- " 'topping': 'basil/spinach'}"
- ]
- },
- "execution_count": 35,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "transformed_data[0]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 36,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'LEC001'"
- ]
- },
- "execution_count": 36,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "transformed_data[0][\"lecture\"]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 37,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'Engineering'"
- ]
- },
- "execution_count": 37,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "transformed_data[1][\"major\"]"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.8.8"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/demo_lec_19_template-checkpoint.ipynb b/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/demo_lec_19_template-checkpoint.ipynb
deleted file mode 100644
index b084cea..0000000
--- a/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/demo_lec_19_template-checkpoint.ipynb
+++ /dev/null
@@ -1,551 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Dictionaries 2"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# This cell just makes juypter notebook use the full width of the screen and changes \n",
- "# some of the text to red. You can ignore this cell\n",
- "from IPython.core.display import HTML\n",
- "HTML('<style>em { color: red; }</style> <style>.container {width:100% !important; }</style>')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## If you could choose only one data structure to include in Python: *lists or dictionaries*, which would you choose?"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### List some characteristics of lists - why might you choose to keep *lists*?"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "- indexing - to get data or to update it\n",
- "- slicing - get a sub-sequence\n",
- "- iterate with for loops\n",
- "- string to list and list to string coversion using methods *split* and *join*\n",
- "- csv files are represented using list of lists"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "L = ['a', 'b', 'c']\n",
- "L"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "L_dict = {0:'a', 1:'b', 2:'c'}\n",
- "L_dict"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### List some characteristics of dictionaries - why might you choose to keep *dictionaries*?"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "- lookup values using keys \n",
- "- labels can be any (immutable) type (flexibility)\n",
- "- insert and update have same syntax\n",
- "- iterate with for loops"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "d = {'x': 3, 'y': 9}\n",
- "d"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "keys = ['x', 'y']\n",
- "vals = [ 3 , 9 ]\n",
- "\n",
- "for index in range(len(keys)):\n",
- " print(keys[index], vals[index])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Review - Dictionary Methods: len, in, for"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "num_words = {0:\"zero\", 1:\"one\", 2:\"two\", 3:\"three\"}\n",
- "num_words"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "len(num_words)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "print(1 in num_words)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "print(\"one\" in num_words)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "for key in num_words:\n",
- " print(key, num_words[key])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Dictionary Methods: keys and values"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "list(num_words.keys())"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "list(num_words.values())"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "print(1 in num_words)\n",
- "print(\"one\" in num_words)\n",
- "print(1 in list(num_words.keys()))\n",
- "print(\"one\" in list(num_words.values()))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Dictionary Methods: get and pop"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "num_words"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "num_words.get(1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "num_words.get(4) # doesn't get anything"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "num_words.pop(3)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "num_words"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# num_words.pop(4) # KeyError"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Default Values with get and pop"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "suffix = {1:\"st\", 2:\"nd\", 3:\"rd\"}\n",
- "suffix"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "suffix.pop(0, \"th\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "suffix.get(4,\"th\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Compute the Average Age of Students per Section"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import csv\n",
- "\n",
- "# copied from https://automatetheboringstuff.com/chapter14/\n",
- "def process_csv(filename):\n",
- " exampleFile = open(filename, encoding=\"utf-8\")\n",
- " exampleReader = csv.reader(exampleFile)\n",
- " exampleData = list(exampleReader)\n",
- " exampleFile.close()\n",
- " return exampleData"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Explore the data\n",
- "- separate it into header and data"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "data = process_csv(\"cs220_survey_data.csv\")\n",
- "header = None\n",
- "header"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "data = None"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Let's write cell function"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "def cell(row_idx, col_name):\n",
- " pass"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Write a function to compute the average age"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# data is a list of lists, corresponding to header\n",
- "def col_avg(data, col_name):\n",
- " pass\n",
- " \n",
- "col_avg(data, \"age\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Collect the data into buckets\n",
- "- Write a function called bucketize\n",
- " - input: column name for bucketization\n",
- " - output: buckets -> dict of list of lists"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Bucketize by year"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "sec_buckets = bucketize(\"lecture\")\n",
- "sec_buckets"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Bucketize by location"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "major_buckets = bucketize(\"major\")\n",
- "major_buckets"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Write a function to compute the average speed per bucket"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "def avg_per_bucket(groups, avg_col_name):\n",
- " pass"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### What is the *average tornado age* per *section*?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "avg_per_bucket(sec_buckets, \"age\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### What is the *average tornado speed* per *location*?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "avg_per_bucket(major_buckets, \"age\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Process a CSV file into a list of dictionaries"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "def transform(header, data):\n",
- " pass\n",
- " \n",
- "transformed_data = transform(header, data)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "transformed_data[0]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "transformed_data[0][\"lecture\"]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "transformed_data[1][\"major\"]"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.8.8"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/lec_19_json-checkpoint.ipynb b/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/lec_19_json-checkpoint.ipynb
deleted file mode 100644
index 0919fe6..0000000
--- a/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/lec_19_json-checkpoint.ipynb
+++ /dev/null
@@ -1,497 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "id": "1d888215",
- "metadata": {},
- "source": [
- "# JSON"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "7ccf358c",
- "metadata": {},
- "source": [
- "### Learning Objectives:\n",
- "- Interpret JSON formatted data and recognize differences between JSON and Python\n",
- "- Deserialize data from JSON for use in Python programs (read)\n",
- "- Serialize data into JSON for long term storage (write) "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "id": "5990f3d6",
- "metadata": {},
- "outputs": [],
- "source": [
- "import csv\n",
- "\n",
- "# TODO: import json module\n",
- "import json"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "id": "5662ace1",
- "metadata": {},
- "outputs": [],
- "source": [
- "# Deserialize\n",
- "def read_json(path):\n",
- " with open(path, encoding = \"utf-8\") as f: # f is a varaible \n",
- " return json.load(f) # f represents data in the JSON file (dict, list, etc)\n",
- " \n",
- "# Serialize\n",
- "def write_json(path, data):\n",
- " with open(path, 'w', encoding = \"utf-8\") as f:\n",
- " json.dump(data, f, indent = 2)"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "a35312c9",
- "metadata": {},
- "source": [
- "### Example 1: Sum of numbers (simple JSON)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "id": "d241dc5c",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Enter the JSON file name: numsA.json\n",
- "<class 'list'>\n",
- "10\n"
- ]
- }
- ],
- "source": [
- "# TODO 1: Create a new \"numsA.json\".\n",
- "# Add the list [1, 2, 3, 4] to \"numsA.json\" file.\n",
- "# Use jupyter notebook to create and edit the new file\n",
- "\n",
- "# TODO 2: Use input built-in function go get JSON file name from user\n",
- "# Read the JSON file using read_json; capture return value into a variable\n",
- "data = read_json(input(\"Enter the JSON file name: \"))\n",
- "\n",
- "# TODO 3: Print type of data returned by function that reads JSON file.\n",
- "print(type(data))\n",
- "\n",
- "# TODO 4: Using Python built-in function sum(...), calculate total of numbers in numsA.json, print the total.\n",
- "print(sum(data))\n",
- "\n",
- "# TODO 5: Create a new JSON file \"numsB.json\" and try out the following data:\n",
- "# [-1, 10, 4,]\n",
- "# Does that work?\n",
- "# Change the data to [-1, 10, 4] and try to run the program by providing input as numsB.json\n",
- "\n",
- "# TODO 6: Create a new JSON file \"simple.json\" and try out the following data.\n",
- "# What kind of error do you get with this?\n",
- "# Fix the error by commenting the line of code that causes the error!\n",
- "# 3.14\n",
- "# True\n",
- "# true\n",
- "# 'hello'\n",
- "# \"hello\"\n"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "e830f23f",
- "metadata": {},
- "source": [
- "### Example 2: Score Tracker"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "id": "10e00558",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Enter player name and score: Viyan 40\n",
- "{'Meena': [20, 10, 10], 'Viyan': [40, 50, 70, 40, 50, 40], 'Rogers': [10, 40]}\n",
- "Average score for Viyan is 48.333333333333336.\n"
- ]
- }
- ],
- "source": [
- "player_details = input(\"Enter player name and score: \")\n",
- "# TODO 1: extract player name and score into variables\n",
- "player_name, player_score = player_details.split(\" \")\n",
- "player_score = int(player_score)\n",
- "\n",
- "# TODO 2: Define an empty \"scores\" dictionary to keep track of players'\n",
- "# scores.\n",
- "# KEY: player name VALUE: player scores list\n",
- "\n",
- "input_file = \"score_history.json\"\n",
- "scores = read_json(input_file) # updated code after TODO 6\n",
- "\n",
- "# TODO 3: Check if player name is a key in the scores dictionary.\n",
- "# If not, create a new key for player name and value as empty list\n",
- "# to keep track of that player's scores.\n",
- "\n",
- "if player_name not in scores:\n",
- " scores[player_name] = []\n",
- "\n",
- "# TODO 4: Add player's score to the player's list in scores dictionary\n",
- "scores[player_name].append(player_score)\n",
- "print(scores)\n",
- "\n",
- "# TODO 5: Create a \"score_history.json\" file and popluate that file with\n",
- "# empty dictionary {}\n",
- "\n",
- "# TODO 6: Read \"score_history.json\" to populate initial \"scores\" dict, \n",
- "# instead of the empty dict created in TODO 2.\n",
- "\n",
- "# TODO 7: Calculate average score for that player\n",
- "print(\"Average score for {} is {}.\".format(player_name, sum(scores[player_name]) / len(scores[player_name])))\n",
- "\n",
- "# TODO 8: At the end of the program, write the updated scores from dict\n",
- "# into the \"score_history.json\" file\n",
- "\n",
- "write_json(input_file, scores)\n",
- "\n",
- "# That's it, now you have a program that helps you keep track \n",
- "# of player scores permanently."
- ]
- },
- {
- "cell_type": "markdown",
- "id": "b920d6e0",
- "metadata": {},
- "source": [
- "### Example 3: Kiva.com Micro-lending site\n",
- "Many Web Sites have APIs that allow you to get their data."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "id": "dc891f5a",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'dict'>\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "{'data': {'lend': {'loans': {'values': [{'name': 'Polikseni',\n",
- " 'description': \"Polikseni is 70 years old and married. She and her husband are both retired and their main income is a retirement pension of $106 a month for Polikseni and disability income for her husband of $289 a month. <br /><br />Polikseni's husband, even though disabled, works in a very small shop as a watchmaker on short hours, just to provide additional income for his family and to feel useful. Polikseni's husband needs constant medical treatment due to his health problems. She requested another loan, which she will use to continue paying for the therapy her husband needs. With a part of the loan, she is going to pay the remainder of the previous loan.\",\n",
- " 'loanAmount': '1325.00',\n",
- " 'geocode': {'city': 'Korce',\n",
- " 'country': {'name': 'Albania',\n",
- " 'region': 'Eastern Europe',\n",
- " 'fundsLentInCountry': 9051250}}},\n",
- " {'name': 'Safarmo',\n",
- " 'description': \"Safarmo is 47 years old. She lives with her husband and her children in Khuroson district. <br /><br />Safarmo is a seamstress. She has been engaged in sewing for 10 years. She learned this activity with help of her mother and elder sister. <br /><br />Safarmo's sewing machine is old and she cannot work well. Her difficulty is lack of money. That’s why she applied for a loan to buy a new modern sewing machine. <br /><br />Safarmo needs your support.\",\n",
- " 'loanAmount': '1075.00',\n",
- " 'geocode': {'city': 'Khuroson',\n",
- " 'country': {'name': 'Tajikistan',\n",
- " 'region': 'Asia',\n",
- " 'fundsLentInCountry': 64243075}}},\n",
- " {'name': 'Elizabeth',\n",
- " 'description': 'Elizabeth is a mom blessed with five lovely children, who are her greatest motivation in life. She lives in the Natuu area of Kenya. Elizabeth is one of the most hardworking women in sub-Saharan Africa. Being a mother and living in a poor country has never been an excuse for Elizabeth, who has practiced mixed farming for the past few years.<br /><br />The cultural expectations in her area contribute to the notion that men should support their families. However, Elizabeth works independently for the success of her children. She perseveres because she wants to provide a better future for them.<br /><br />Elizabeth has always loved farming. She is a very proud farmer and enjoys milking her dairy cows. Elizabeth keeps poultry and grows crops, but she has not been making a good profit because of poor farming inputs. <br /><br />Elizabeth will use this loan to buy farm inputs and purchase high-quality seeds and good fertilizer to improve her crop production. Modern farming requires the use of modern techniques, and, therefore, using high-quality seeds will assure her of a bumper harvest and increased profit levels.<br /><br />Elizabeth is very visionary. Her goal for the season is to boost her crop production over the previous year.',\n",
- " 'loanAmount': '800.00',\n",
- " 'geocode': {'city': 'Matuu',\n",
- " 'country': {'name': 'Kenya',\n",
- " 'region': 'Africa',\n",
- " 'fundsLentInCountry': 120841775}}},\n",
- " {'name': 'Ester',\n",
- " 'description': 'Ester believes that this year is her year of prosperity. Ester is a hardworking, progressive and honest farmer from a very remote village in the Kitale area of Kenya. This area is very fertile, with favorable weather patterns that support farming activities. Ester is happily married and the proud mother of lovely children. Together, they live on a small piece of land that she really treasures. Her primary sources of income are eggs and milk.<br /><br />Although this humble and industrious mother makes a profit, she faces the challenge of not being able to produce enough to meet the readily available market. Therefore, she is seeking funds from Kiva lenders to buy farm inputs such as good fertilizer and good-quality seeds. Through this loan, Ester should double her production, and this will translate into increased income. She then intends to save more money in the future so that she can develop her farming.<br /><br />One objective that Juhudi Kilimo aims at fulfilling is increasing the ease of accessing farm inputs and income-generating assets for farmers. Through the intervention of Juhudi Kilimo and Kiva, inputs such as fertilizers and pesticides have become more accessible to its members than buying a bottle of water. Ester is very optimistic and believes this loan will change her life completely.',\n",
- " 'loanAmount': '275.00',\n",
- " 'geocode': {'city': 'Kitale',\n",
- " 'country': {'name': 'Kenya',\n",
- " 'region': 'Africa',\n",
- " 'fundsLentInCountry': 120841775}}},\n",
- " {'name': 'Cherifa',\n",
- " 'description': 'Cherifa is married, 57 years old with two children. She caters and also sells the local drink. She asks for credit to buy the necessities, in particular bags of anchovies, bags of maize and bundles of firewood. She wants to have enough income to run the house well.',\n",
- " 'loanAmount': '875.00',\n",
- " 'geocode': {'city': 'Agoe',\n",
- " 'country': {'name': 'Togo',\n",
- " 'region': 'Africa',\n",
- " 'fundsLentInCountry': 13719125}}}]}}}}"
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# TODO: read \"kiva.json\"\n",
- "kiva_data = read_json('kiva.json')\n",
- "\n",
- "# TODO: explore the type of the data structure returned by read_json\n",
- "print(type(kiva_data))\n",
- "\n",
- "kiva_data"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "e29310b6",
- "metadata": {},
- "source": [
- "How to explore an unknown JSON?\n",
- "- If you run into a `dict`, try `.keys()` method to look at the keys of the dictionary, then use lookup process to explore further\n",
- "- If you run into a `list`, iterate over the list and print each item"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "id": "31fe630f",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "['data']\n",
- "<class 'dict'>\n"
- ]
- }
- ],
- "source": [
- "print(list(kiva_data.keys()))\n",
- "\n",
- "# TODO: lookup the value corresponding to the key\n",
- "kiva_data[\"data\"]\n",
- "\n",
- "# TODO: you know what to do next ... explore type again\n",
- "print(type(kiva_data[\"data\"]))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "id": "e09b064f",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "['lend']\n",
- "['loans']\n",
- "['values']\n"
- ]
- }
- ],
- "source": [
- "print(list(kiva_data[\"data\"].keys()))\n",
- "print(list(kiva_data[\"data\"][\"lend\"].keys()))\n",
- "print(list(kiva_data[\"data\"][\"lend\"][\"loans\"].keys()))\n",
- "loans_list = kiva_data[\"data\"][\"lend\"][\"loans\"][\"values\"] # actual information: list of loan dictionaries"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "id": "b6cb9c28",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Borrower name: Polikseni\n",
- "Loan amount: $1325.00\n",
- "Country details: {'name': 'Albania', 'region': 'Eastern Europe', 'fundsLentInCountry': 9051250}\n",
- "------------------------------------------------------------------------------------------------\n",
- "Borrower name: Safarmo\n",
- "Loan amount: $1075.00\n",
- "Country details: {'name': 'Tajikistan', 'region': 'Asia', 'fundsLentInCountry': 64243075}\n",
- "------------------------------------------------------------------------------------------------\n",
- "Borrower name: Elizabeth\n",
- "Loan amount: $800.00\n",
- "Country details: {'name': 'Kenya', 'region': 'Africa', 'fundsLentInCountry': 120841775}\n",
- "------------------------------------------------------------------------------------------------\n",
- "Borrower name: Ester\n",
- "Loan amount: $275.00\n",
- "Country details: {'name': 'Kenya', 'region': 'Africa', 'fundsLentInCountry': 120841775}\n",
- "------------------------------------------------------------------------------------------------\n",
- "Borrower name: Cherifa\n",
- "Loan amount: $875.00\n",
- "Country details: {'name': 'Togo', 'region': 'Africa', 'fundsLentInCountry': 13719125}\n",
- "------------------------------------------------------------------------------------------------\n"
- ]
- }
- ],
- "source": [
- "# TODO: iterate over loans_list and print every borrower's name, loan amount and country details\n",
- "\n",
- "for loan_dict in loans_list:\n",
- " borrower_name = loan_dict[\"name\"]\n",
- " print(\"Borrower name:\", borrower_name)\n",
- " loan_amount = loan_dict[\"loanAmount\"]\n",
- " print(\"Loan amount: $\", loan_amount, sep = \"\")\n",
- " country_details = loan_dict[\"geocode\"][\"country\"]\n",
- " print(\"Country details:\", country_details)\n",
- " print(\"------------------------------------------------------------------------------------------------\")"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "26b4c70c",
- "metadata": {},
- "source": [
- "### Let's write student information dataset into various JSON files"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "id": "c120d0eb",
- "metadata": {},
- "outputs": [],
- "source": [
- "# inspired by https://automatetheboringstuff.com/2e/chapter16/\n",
- "def process_csv(filename):\n",
- " exampleFile = open(filename, encoding=\"utf-8\") \n",
- " exampleReader = csv.reader(exampleFile) \n",
- " exampleData = list(exampleReader) \n",
- " exampleFile.close() \n",
- " return exampleData\n",
- "\n",
- "survey_data = process_csv('cs220_survey_data.csv')\n",
- "cs220_header = survey_data[0]\n",
- "cs220_data = survey_data[1:]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "id": "47cb92e9",
- "metadata": {},
- "outputs": [],
- "source": [
- "def cell(row_idx, col_name):\n",
- " \"\"\"\n",
- " Returns the data value (cell) corresponding to the row index and \n",
- " the column name of a CSV file.\n",
- " \"\"\"\n",
- " col_idx = cs220_header.index(col_name) \n",
- " val = cs220_data[row_idx][col_idx] \n",
- " \n",
- " # handle missing values, by returning None\n",
- " if val == '':\n",
- " return None\n",
- " \n",
- " # handle type conversions\n",
- " if col_name in [\"Age\",]:\n",
- " return int(val)\n",
- " \n",
- " return val"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "id": "9a84cfb8",
- "metadata": {},
- "outputs": [],
- "source": [
- "# Let's bucketize the data\n",
- "buckets = dict() # Key: unique bucketize column value; Value: list of lists (rows having that unique column value)\n",
- "\n",
- "def bucketize(bucket_column):\n",
- " \"\"\"\n",
- " generates and returns bucketized data based on bucket_column\n",
- " \"\"\"\n",
- " # Key: unique bucketize column value; Value: list of lists (rows having that unique column value)\n",
- " buckets = dict()\n",
- " for row_idx in range(len(cs220_data)):\n",
- " col_value = cell(row_idx, bucket_column)\n",
- " if col_value not in buckets:\n",
- " buckets[col_value] = []\n",
- " buckets[col_value].append(cs220_data[row_idx])\n",
- " \n",
- " return buckets\n",
- "\n",
- "# TODO: create section based buckets and store result into sec_buckets\n",
- "sec_buckets = bucketize(\"Lecture\")\n",
- "\n",
- "# TODO: What is the type of sec_buckets? A __dict____ of ___list of lists______\n",
- "\n",
- "# TODO: write sec_buckets into a JSON file called \"section_cs220_data.json\"\n",
- "write_json(\"section_cs220_data.json\", sec_buckets)\n",
- "\n",
- "# TODO: create primary major based buckets and store result into major_buckets\n",
- "major_buckets = bucketize(\"Primary major\")\n",
- "\n",
- "# TODO: write major_buckets into a JSON file called \"major_cs220_data.json\"\n",
- "write_json(\"major_cs220_data.json\", major_buckets)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "id": "f36a584a",
- "metadata": {},
- "outputs": [],
- "source": [
- "def transform(header, data):\n",
- " \"\"\"\n",
- " Transform data into a list of dictionaries\n",
- " \"\"\"\n",
- " dict_list = [] #should be defined outside the for loop, because it stores the entire data\n",
- " \n",
- " for row in cs220_data:\n",
- " new_row = {} #should be defined inside the for loop, because it represents one row as a dictionary\n",
- " for i in range(len(cs220_header)):\n",
- " new_row[cs220_header[i]] = row[i]\n",
- " dict_list.append(new_row)\n",
- " return dict_list\n",
- " \n",
- "transformed_data = transform(cs220_header, cs220_data)\n",
- "\n",
- "# TODO: What is the type of transformed_data? A __list____ of ___dictionaries______\n",
- "\n",
- "# TODO: write transformed_data into a JSON file called \"cs220_survey_data.json\"\n",
- "write_json(\"cs220_survey_data.json\", transformed_data)"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3 (ipykernel)",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.9.7"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/lec_19_json_template-checkpoint.ipynb b/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/lec_19_json_template-checkpoint.ipynb
deleted file mode 100644
index 4ba274f..0000000
--- a/f22/meena_lec_notes/lec-19/.ipynb_checkpoints/lec_19_json_template-checkpoint.ipynb
+++ /dev/null
@@ -1,472 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "id": "1d888215",
- "metadata": {},
- "source": [
- "# JSON"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "7ccf358c",
- "metadata": {},
- "source": [
- "### Learning Objectives:\n",
- "- Interpret JSON formatted data and recognize differences between JSON and Python\n",
- "- Deserialize data from JSON for use in Python programs (read)\n",
- "- Serialize data into JSON for long term storage (write) "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "id": "5990f3d6",
- "metadata": {},
- "outputs": [],
- "source": [
- "import csv\n",
- "\n",
- "# TODO: import json module\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "id": "5662ace1",
- "metadata": {},
- "outputs": [],
- "source": [
- "# Deserialize\n",
- "def read_json(path):\n",
- " with open(path, encoding = \"utf-8\") as f: # f is a varaible \n",
- " return json.load(f) # f represents data in the JSON file (dict, list, etc)\n",
- " \n",
- "# Serialize\n",
- "def write_json(path, data):\n",
- " with open(path, 'w', encoding = \"utf-8\") as f:\n",
- " json.dump(data, f, indent = 2)"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "a35312c9",
- "metadata": {},
- "source": [
- "### Example 1: Sum of numbers (simple JSON)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "id": "d241dc5c",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Enter the JSON file name: numsA.json\n",
- "<class 'list'>\n",
- "10\n"
- ]
- }
- ],
- "source": [
- "# TODO 1: Create a new \"numsA.json\".\n",
- "# Add the list [1, 2, 3, 4] to \"numsA.json\" file.\n",
- "# Use jupyter notebook to create and edit the new file\n",
- "\n",
- "# TODO 2: Use input built-in function go get JSON file name from user\n",
- "# Read the JSON file using read_json; capture return value into a variable\n",
- "\n",
- "# TODO 3: Print type of data returned by function that reads JSON file.\n",
- "\n",
- "# TODO 4: Using Python built-in function sum(...), calculate total of numbers in numsA.json, print the total.\n",
- "\n",
- "# TODO 5: Create a new JSON file \"numsB.json\" and try out the following data:\n",
- "# [-1, 10, 4,]\n",
- "# Does that work?\n",
- "# Change the data to [-1, 10, 4] and try to run the program by providing input as numsB.json\n",
- "\n",
- "# TODO 6: Create a new JSON file \"simple.json\" and try out the following data.\n",
- "# What kind of error do you get with this?\n",
- "# Fix the error by commenting the line of code that causes the error!\n",
- "# 3.14\n",
- "# True\n",
- "# true\n",
- "# 'hello'\n",
- "# \"hello\"\n"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "e830f23f",
- "metadata": {},
- "source": [
- "### Example 2: Score Tracker"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "id": "10e00558",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Enter player name and score: Viyan 40\n",
- "{'Meena': [20, 10, 10], 'Viyan': [40, 50, 70, 40, 50, 40], 'Rogers': [10, 40]}\n",
- "Average score for Viyan is 48.333333333333336.\n"
- ]
- }
- ],
- "source": [
- "player_details = input(\"Enter player name and score: \")\n",
- "# TODO 1: extract player name and score into variables\n",
- "\n",
- "\n",
- "# TODO 2: Define an empty \"scores\" dictionary to keep track of players'\n",
- "# scores.\n",
- "# KEY: player name VALUE: player scores list\n",
- "\n",
- "input_file = \"score_history.json\"\n",
- "\n",
- "\n",
- "# TODO 3: Check if player name is a key in the scores dictionary.\n",
- "# If not, create a new key for player name and value as empty list\n",
- "# to keep track of that player's scores.\n",
- "\n",
- "\n",
- "\n",
- "# TODO 4: Add player's score to the player's list in scores dictionary\n",
- "\n",
- "\n",
- "# TODO 5: Create a \"score_history.json\" file and popluate that file with\n",
- "# empty dictionary {}\n",
- "\n",
- "# TODO 6: Read \"score_history.json\" to populate initial \"scores\" dict, \n",
- "# instead of the empty dict created in TODO 2.\n",
- "\n",
- "# TODO 7: Calculate average score for that player\n",
- "# print(\"Average score for {} is {}.\"???)\n",
- "\n",
- "# TODO 8: At the end of the program, write the updated scores from dict\n",
- "# into the \"score_history.json\" file\n",
- "\n",
- "# That's it, now you have a program that helps you keep track \n",
- "# of player scores permanently."
- ]
- },
- {
- "cell_type": "markdown",
- "id": "b920d6e0",
- "metadata": {},
- "source": [
- "### Example 3: Kiva.com Micro-lending site\n",
- "Many Web Sites have APIs that allow you to get their data."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "id": "dc891f5a",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'dict'>\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "{'data': {'lend': {'loans': {'values': [{'name': 'Polikseni',\n",
- " 'description': \"Polikseni is 70 years old and married. She and her husband are both retired and their main income is a retirement pension of $106 a month for Polikseni and disability income for her husband of $289 a month. <br /><br />Polikseni's husband, even though disabled, works in a very small shop as a watchmaker on short hours, just to provide additional income for his family and to feel useful. Polikseni's husband needs constant medical treatment due to his health problems. She requested another loan, which she will use to continue paying for the therapy her husband needs. With a part of the loan, she is going to pay the remainder of the previous loan.\",\n",
- " 'loanAmount': '1325.00',\n",
- " 'geocode': {'city': 'Korce',\n",
- " 'country': {'name': 'Albania',\n",
- " 'region': 'Eastern Europe',\n",
- " 'fundsLentInCountry': 9051250}}},\n",
- " {'name': 'Safarmo',\n",
- " 'description': \"Safarmo is 47 years old. She lives with her husband and her children in Khuroson district. <br /><br />Safarmo is a seamstress. She has been engaged in sewing for 10 years. She learned this activity with help of her mother and elder sister. <br /><br />Safarmo's sewing machine is old and she cannot work well. Her difficulty is lack of money. That’s why she applied for a loan to buy a new modern sewing machine. <br /><br />Safarmo needs your support.\",\n",
- " 'loanAmount': '1075.00',\n",
- " 'geocode': {'city': 'Khuroson',\n",
- " 'country': {'name': 'Tajikistan',\n",
- " 'region': 'Asia',\n",
- " 'fundsLentInCountry': 64243075}}},\n",
- " {'name': 'Elizabeth',\n",
- " 'description': 'Elizabeth is a mom blessed with five lovely children, who are her greatest motivation in life. She lives in the Natuu area of Kenya. Elizabeth is one of the most hardworking women in sub-Saharan Africa. Being a mother and living in a poor country has never been an excuse for Elizabeth, who has practiced mixed farming for the past few years.<br /><br />The cultural expectations in her area contribute to the notion that men should support their families. However, Elizabeth works independently for the success of her children. She perseveres because she wants to provide a better future for them.<br /><br />Elizabeth has always loved farming. She is a very proud farmer and enjoys milking her dairy cows. Elizabeth keeps poultry and grows crops, but she has not been making a good profit because of poor farming inputs. <br /><br />Elizabeth will use this loan to buy farm inputs and purchase high-quality seeds and good fertilizer to improve her crop production. Modern farming requires the use of modern techniques, and, therefore, using high-quality seeds will assure her of a bumper harvest and increased profit levels.<br /><br />Elizabeth is very visionary. Her goal for the season is to boost her crop production over the previous year.',\n",
- " 'loanAmount': '800.00',\n",
- " 'geocode': {'city': 'Matuu',\n",
- " 'country': {'name': 'Kenya',\n",
- " 'region': 'Africa',\n",
- " 'fundsLentInCountry': 120841775}}},\n",
- " {'name': 'Ester',\n",
- " 'description': 'Ester believes that this year is her year of prosperity. Ester is a hardworking, progressive and honest farmer from a very remote village in the Kitale area of Kenya. This area is very fertile, with favorable weather patterns that support farming activities. Ester is happily married and the proud mother of lovely children. Together, they live on a small piece of land that she really treasures. Her primary sources of income are eggs and milk.<br /><br />Although this humble and industrious mother makes a profit, she faces the challenge of not being able to produce enough to meet the readily available market. Therefore, she is seeking funds from Kiva lenders to buy farm inputs such as good fertilizer and good-quality seeds. Through this loan, Ester should double her production, and this will translate into increased income. She then intends to save more money in the future so that she can develop her farming.<br /><br />One objective that Juhudi Kilimo aims at fulfilling is increasing the ease of accessing farm inputs and income-generating assets for farmers. Through the intervention of Juhudi Kilimo and Kiva, inputs such as fertilizers and pesticides have become more accessible to its members than buying a bottle of water. Ester is very optimistic and believes this loan will change her life completely.',\n",
- " 'loanAmount': '275.00',\n",
- " 'geocode': {'city': 'Kitale',\n",
- " 'country': {'name': 'Kenya',\n",
- " 'region': 'Africa',\n",
- " 'fundsLentInCountry': 120841775}}},\n",
- " {'name': 'Cherifa',\n",
- " 'description': 'Cherifa is married, 57 years old with two children. She caters and also sells the local drink. She asks for credit to buy the necessities, in particular bags of anchovies, bags of maize and bundles of firewood. She wants to have enough income to run the house well.',\n",
- " 'loanAmount': '875.00',\n",
- " 'geocode': {'city': 'Agoe',\n",
- " 'country': {'name': 'Togo',\n",
- " 'region': 'Africa',\n",
- " 'fundsLentInCountry': 13719125}}}]}}}}"
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# TODO: read \"kiva.json\"\n",
- "\n",
- "# TODO: explore the type of the data structure returned by read_json\n"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "e29310b6",
- "metadata": {},
- "source": [
- "How to explore an unknown JSON?\n",
- "- If you run into a `dict`, try `.keys()` method to look at the keys of the dictionary, then use lookup process to explore further\n",
- "- If you run into a `list`, iterate over the list and print each item"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "id": "31fe630f",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "['data']\n",
- "<class 'dict'>\n"
- ]
- }
- ],
- "source": [
- "\n",
- "\n",
- "# TODO: lookup the value corresponding to the key data\n",
- "\n",
- "# TODO: you know what to do next ... explore type again\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "id": "e09b064f",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "['lend']\n",
- "['loans']\n",
- "['values']\n"
- ]
- }
- ],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "id": "b6cb9c28",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Borrower name: Polikseni\n",
- "Loan amount: $1325.00\n",
- "Country details: {'name': 'Albania', 'region': 'Eastern Europe', 'fundsLentInCountry': 9051250}\n",
- "------------------------------------------------------------------------------------------------\n",
- "Borrower name: Safarmo\n",
- "Loan amount: $1075.00\n",
- "Country details: {'name': 'Tajikistan', 'region': 'Asia', 'fundsLentInCountry': 64243075}\n",
- "------------------------------------------------------------------------------------------------\n",
- "Borrower name: Elizabeth\n",
- "Loan amount: $800.00\n",
- "Country details: {'name': 'Kenya', 'region': 'Africa', 'fundsLentInCountry': 120841775}\n",
- "------------------------------------------------------------------------------------------------\n",
- "Borrower name: Ester\n",
- "Loan amount: $275.00\n",
- "Country details: {'name': 'Kenya', 'region': 'Africa', 'fundsLentInCountry': 120841775}\n",
- "------------------------------------------------------------------------------------------------\n",
- "Borrower name: Cherifa\n",
- "Loan amount: $875.00\n",
- "Country details: {'name': 'Togo', 'region': 'Africa', 'fundsLentInCountry': 13719125}\n",
- "------------------------------------------------------------------------------------------------\n"
- ]
- }
- ],
- "source": [
- "# TODO: iterate over loans_list and print every borrower's name, loan amount and country details\n",
- "\n",
- "???\n",
- " \n",
- " print(\"Borrower name:\", borrower_name)\n",
- "\n",
- " print(\"Loan amount: $\", loan_amount, sep = \"\")\n",
- "\n",
- " print(\"Country details:\", country_details)\n",
- " print(\"------------------------------------------------------------------------------------------------\")"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "26b4c70c",
- "metadata": {},
- "source": [
- "### Let's write student information dataset into various JSON files"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "id": "c120d0eb",
- "metadata": {},
- "outputs": [],
- "source": [
- "# inspired by https://automatetheboringstuff.com/2e/chapter16/\n",
- "def process_csv(filename):\n",
- " exampleFile = open(filename, encoding=\"utf-8\") \n",
- " exampleReader = csv.reader(exampleFile) \n",
- " exampleData = list(exampleReader) \n",
- " exampleFile.close() \n",
- " return exampleData\n",
- "\n",
- "survey_data = process_csv('cs220_survey_data.csv')\n",
- "cs220_header = survey_data[0]\n",
- "cs220_data = survey_data[1:]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "id": "47cb92e9",
- "metadata": {},
- "outputs": [],
- "source": [
- "def cell(row_idx, col_name):\n",
- " \"\"\"\n",
- " Returns the data value (cell) corresponding to the row index and \n",
- " the column name of a CSV file.\n",
- " \"\"\"\n",
- " col_idx = cs220_header.index(col_name) \n",
- " val = cs220_data[row_idx][col_idx] \n",
- " \n",
- " # handle missing values, by returning None\n",
- " if val == '':\n",
- " return None\n",
- " \n",
- " # handle type conversions\n",
- " if col_name in [\"Age\",]:\n",
- " return int(val)\n",
- " \n",
- " return val"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "id": "9a84cfb8",
- "metadata": {},
- "outputs": [],
- "source": [
- "# Let's bucketize the data\n",
- "buckets = dict() # Key: unique bucketize column value; Value: list of lists (rows having that unique column value)\n",
- "\n",
- "def bucketize(bucket_column):\n",
- " \"\"\"\n",
- " generates and returns bucketized data based on bucket_column\n",
- " \"\"\"\n",
- " # Key: unique bucketize column value; Value: list of lists (rows having that unique column value)\n",
- " buckets = dict()\n",
- " for row_idx in range(len(cs220_data)):\n",
- " col_value = cell(row_idx, bucket_column)\n",
- " if col_value not in buckets:\n",
- " buckets[col_value] = []\n",
- " buckets[col_value].append(cs220_data[row_idx])\n",
- " \n",
- " return buckets\n",
- "\n",
- "# TODO: create section based buckets and store result into sec_buckets\n",
- "\n",
- "# TODO: What is the type of sec_buckets? A ______ of _________\n",
- "\n",
- "# TODO: write sec_buckets into a JSON file called \"section_cs220_data.json\"\n",
- "\n",
- "# TODO: create primary major based buckets and store result into major_buckets\n",
- "\n",
- "# TODO: write major_buckets into a JSON file called \"major_cs220_data.json\"\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "id": "f36a584a",
- "metadata": {},
- "outputs": [],
- "source": [
- "def transform(header, data):\n",
- " \"\"\"\n",
- " Transform data into a list of dictionaries\n",
- " \"\"\"\n",
- " dict_list = [] #should be defined outside the for loop, because it stores the entire data\n",
- " \n",
- " for row in cs220_data:\n",
- " new_row = {} #should be defined inside the for loop, because it represents one row as a dictionary\n",
- " for i in range(len(cs220_header)):\n",
- " new_row[cs220_header[i]] = row[i]\n",
- " dict_list.append(new_row)\n",
- " return dict_list\n",
- " \n",
- "transformed_data = transform(cs220_header, cs220_data)\n",
- "\n",
- "# TODO: What is the type of transformed_data? A ______ of _________\n",
- "\n",
- "# TODO: write transformed_data into a JSON file called \"cs220_survey_data.json\"\n"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3 (ipykernel)",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.9.7"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/f22/meena_lec_notes/lec-19/cs220_survey_data.json b/f22/meena_lec_notes/lec-19/cs220_survey_data.json
deleted file mode 100644
index c8776f2..0000000
--- a/f22/meena_lec_notes/lec-19/cs220_survey_data.json
+++ /dev/null
@@ -1,12898 +0,0 @@
-[
- {
- "Lecture": "LEC001",
- "Age": "22",
- "Major": "Engineering: Biomedical",
- "Zip Code": "53703",
- "Latitude": "43.073051",
- "Longitude": "-89.40123",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "neither",
- "Runner": "No",
- "Sleep habit": "no preference",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC006",
- "Age": "",
- "Major": "Undecided",
- "Zip Code": "53706",
- "Latitude": "43.073051",
- "Longitude": "-89.40123",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "neither",
- "Runner": "No",
- "Sleep habit": "no preference",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC004",
- "Age": "18",
- "Major": "Engineering: Industrial",
- "Zip Code": "53715",
- "Latitude": "43.073051",
- "Longitude": "-89.40123",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "neither",
- "Runner": "No",
- "Sleep habit": "no preference",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC005",
- "Age": "",
- "Major": "Undecided",
- "Zip Code": "53706",
- "Latitude": "43.073051",
- "Longitude": "-89.40123",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "neither",
- "Runner": "No",
- "Sleep habit": "no preference",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC002",
- "Age": "",
- "Major": "Undecided",
- "Zip Code": "53706",
- "Latitude": "43.073051",
- "Longitude": "-89.40123",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "neither",
- "Runner": "No",
- "Sleep habit": "no preference",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC004",
- "Age": "18",
- "Major": "Engineering: Other|Engineering: Computer",
- "Zip Code": "53706",
- "Latitude": "43.073051",
- "Longitude": "-89.40123",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "neither",
- "Runner": "No",
- "Sleep habit": "no preference",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC003",
- "Age": "",
- "Major": "Undecided",
- "Zip Code": "53706",
- "Latitude": "43.073051",
- "Longitude": "-89.40123",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "neither",
- "Runner": "No",
- "Sleep habit": "no preference",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC003",
- "Age": "18",
- "Major": "Data Science",
- "Zip Code": "53715",
- "Latitude": "43.073051",
- "Longitude": "-89.40123",
- "Pizza topping": "pineapple",
- "Pet preference": "cat",
- "Runner": "Yes",
- "Sleep habit": "no preference",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC006",
- "Age": "18",
- "Major": "Data Science",
- "Zip Code": "53706",
- "Latitude": "35.4",
- "Longitude": "119.11",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "dog",
- "Runner": "No",
- "Sleep habit": "night owl",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC006",
- "Age": "18",
- "Major": "Mathematics/AMEP",
- "Zip Code": "53706",
- "Latitude": "44",
- "Longitude": "-93",
- "Pizza topping": "pepperoni",
- "Pet preference": "dog",
- "Runner": "No",
- "Sleep habit": "night owl",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC002",
- "Age": "21",
- "Major": "Engineering: Other",
- "Zip Code": "53703",
- "Latitude": "24.713552",
- "Longitude": "46.675297",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "cat",
- "Runner": "Yes",
- "Sleep habit": "night owl",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC003",
- "Age": "19",
- "Major": "Data Science",
- "Zip Code": "53705",
- "Latitude": "24.6806",
- "Longitude": "46.57936",
- "Pizza topping": "pineapple",
- "Pet preference": "cat",
- "Runner": "No",
- "Sleep habit": "early bird",
- "Procrastinator": "No"
- },
- {
- "Lecture": "LEC004",
- "Age": "24",
- "Major": "Economics",
- "Zip Code": "53703",
- "Latitude": "43",
- "Longitude": "-89",
- "Pizza topping": "pineapple",
- "Pet preference": "cat",
- "Runner": "Yes",
- "Sleep habit": "early bird",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC003",
- "Age": "18",
- "Major": "Data Science",
- "Zip Code": "53706",
- "Latitude": "36.102371",
- "Longitude": "-115.174553",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "dog",
- "Runner": "No",
- "Sleep habit": "night owl",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC006",
- "Age": "22",
- "Major": "Psychology",
- "Zip Code": "53703",
- "Latitude": "31.78",
- "Longitude": "119.95",
- "Pizza topping": "mushroom",
- "Pet preference": "cat",
- "Runner": "No",
- "Sleep habit": "night owl",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC005",
- "Age": "20",
- "Major": "Data Science",
- "Zip Code": "53705",
- "Latitude": "37.8",
- "Longitude": "112.5",
- "Pizza topping": "pepperoni",
- "Pet preference": "cat",
- "Runner": "Yes",
- "Sleep habit": "night owl",
- "Procrastinator": "Yes"
- },
- {
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- "Pet preference": "dog",
- "Runner": "No",
- "Sleep habit": "night owl",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC004",
- "Age": "20",
- "Major": "Engineering: Biomedical",
- "Zip Code": "53715",
- "Latitude": "30.328227",
- "Longitude": "-86.136975",
- "Pizza topping": "pepperoni",
- "Pet preference": "dog",
- "Runner": "Yes",
- "Sleep habit": "no preference",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC004",
- "Age": "21",
- "Major": "Science: Biology/Life",
- "Zip Code": "53703",
- "Latitude": "41.385063",
- "Longitude": "2.173404",
- "Pizza topping": "macaroni/pasta",
- "Pet preference": "dog",
- "Runner": "No",
- "Sleep habit": "night owl",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC003",
- "Age": "18",
- "Major": "Mathematics/AMEP",
- "Zip Code": "53706",
- "Latitude": "42.99571",
- "Longitude": "-90",
- "Pizza topping": "sausage",
- "Pet preference": "dog",
- "Runner": "Yes",
- "Sleep habit": "night owl",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC004",
- "Age": "19",
- "Major": "Engineering: Mechanical",
- "Zip Code": "53703",
- "Latitude": "41.385063",
- "Longitude": "2.173404",
- "Pizza topping": "sausage",
- "Pet preference": "dog",
- "Runner": "Yes",
- "Sleep habit": "night owl",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC001",
- "Age": "",
- "Major": "Engineering: Industrial",
- "Zip Code": "53706",
- "Latitude": "40.7128",
- "Longitude": "74.006",
- "Pizza topping": "pepperoni",
- "Pet preference": "dog",
- "Runner": "No",
- "Sleep habit": "early bird",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC005",
- "Age": "18",
- "Major": "Psychology",
- "Zip Code": "53706",
- "Latitude": "9.167414",
- "Longitude": "77.876747",
- "Pizza topping": "mushroom",
- "Pet preference": "cat",
- "Runner": "No",
- "Sleep habit": "early bird",
- "Procrastinator": "No"
- },
- {
- "Lecture": "LEC003",
- "Age": "19",
- "Major": "Engineering: Industrial",
- "Zip Code": "53715",
- "Latitude": "24.713552",
- "Longitude": "46.675297",
- "Pizza topping": "basil/spinach",
- "Pet preference": "neither",
- "Runner": "Yes",
- "Sleep habit": "early bird",
- "Procrastinator": "Maybe"
- },
- {
- "Lecture": "LEC001",
- "Age": "18",
- "Major": "Undecided",
- "Zip Code": "53706",
- "Latitude": "44.8341",
- "Longitude": "87.377",
- "Pizza topping": "basil/spinach",
- "Pet preference": "dog",
- "Runner": "No",
- "Sleep habit": "no preference",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC003",
- "Age": "19",
- "Major": "Engineering: Mechanical",
- "Zip Code": "53705",
- "Latitude": "46.589146",
- "Longitude": "-112.039108",
- "Pizza topping": "none (just cheese)",
- "Pet preference": "cat",
- "Runner": "No",
- "Sleep habit": "night owl",
- "Procrastinator": "Yes"
- },
- {
- "Lecture": "LEC001",
- "Age": "20",
- "Major": "Economics",
- "Zip Code": "53703",
- "Latitude": "39.631506",
- "Longitude": "118.143239",
- "Pizza topping": "pineapple",
- "Pet preference": "dog",
- "Runner": "No",
- "Sleep habit": "night owl",
- "Procrastinator": "Maybe"
- }
-]
\ No newline at end of file
diff --git a/f22/meena_lec_notes/lec-19/lecture_cs220_data.json b/f22/meena_lec_notes/lec-19/lecture_cs220_data.json
deleted file mode 100644
index de596de..0000000
--- a/f22/meena_lec_notes/lec-19/lecture_cs220_data.json
+++ /dev/null
@@ -1,12910 +0,0 @@
-{
- "LEC001": [
- [
- "LEC001",
- "22",
- "Engineering: Biomedical",
- "53703",
- "43.073051",
- "-89.40123",
- "none (just cheese)",
- "neither",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "",
- "Mathematics/AMEP",
- "53706",
- "31.230391",
- "121.473701",
- "basil/spinach",
- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Economics (Mathematical Emphasis)",
- "53703",
- "48.86",
- "2.3522",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53703",
- "24.7",
- "46.7",
- "mushroom",
- "dog",
- "Yes",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "23",
- "Computer Science",
- "53711",
- "43.073929",
- "-89.385239",
- "sausage",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "22",
- "Engineering: Mechanical",
- "53719",
- "43.073051",
- "-89.40123",
- "none (just cheese)",
- "cat",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Computer Science",
- "53706",
- "26.2992",
- "87.2625",
- "mushroom",
- "dog",
- "Yes",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "24",
- "Business: Information Systems",
- "53703",
- "43.073051",
- "-89.40123",
- "macaroni/pasta",
- "cat",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "",
- "Computer Science",
- "53715",
- "34.052235",
- "-118.243683",
- "green pepper",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "26",
- "Engineering: Mechanical",
- "53703",
- "41.902782",
- "12.496365",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "25",
- "Economics",
- "53703",
- "40.712776",
- "-74.005974",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Computer Science",
- "53706",
- "48.855709",
- "2.29889",
- "pepperoni",
- "cat",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "21",
- "Computer Science",
- "53715",
- "16.306652",
- "80.436539",
- "Other",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Industrial",
- "53715",
- "30.733315",
- "76.779419",
- "green pepper",
- "cat",
- "No",
- "no preference",
- "Yes"
- ],
- [
- "LEC001",
- "20",
- "Economics (Mathematical Emphasis)",
- "53703",
- "43.073929",
- "-89.385239",
- "macaroni/pasta",
- "cat",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "21",
- "Business: Finance",
- "53711",
- "43.073929",
- "-89.385239",
- "pepperoni",
- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "19",
- "Computer Science",
- "53703",
- "51.507351",
- "-0.127758",
- "sausage",
- "cat",
- "Yes",
- "no preference",
- "Yes"
- ],
- [
- "LEC001",
- "21",
- "Science: Biology/Life",
- "53703",
- "36",
- "117",
- "macaroni/pasta",
- "dog",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Other",
- "53706",
- "41.902782",
- "12.496365",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Industrial",
- "53706",
- "19.655041",
- "-101.169891",
- "pepperoni",
- "dog",
- "Yes",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Business: Actuarial",
- "53703",
- "42.28",
- "-83.74",
- "mushroom",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Business: Information Systems",
- "53703",
- "39.481655",
- "-106.038353",
- "macaroni/pasta",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "20",
- "Business: Other|Business: Accounting",
- "53703",
- "31.230391",
- "121.473701",
- "pepperoni",
- "cat",
- "Yes",
- "no preference",
- "No"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53706",
- "35.142441",
- "-223.154297",
- "green pepper",
- "neither",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "",
- "Engineering: Mechanical",
- "53715",
- "19.8968",
- "155.5828",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "21",
- "Computer Science",
- "53703",
- "43.21518",
- "-87.94241",
- "pepperoni",
- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "22",
- "Engineering: Mechanical",
- "53703",
- "47.497913",
- "19.040236",
- "pepperoni",
- "dog",
- "No",
- "no preference",
- "No"
- ],
- [
- "LEC001",
- "20",
- "Business andministration",
- "53703",
- "37.389091",
- "-5.984459",
- "pineapple",
- "dog",
- "Yes",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Computer Science",
- "53703",
- "40.7128",
- "74.006",
- "pepperoni",
- "dog",
- "Yes",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "22",
- "Engineering: Mechanical",
- "53726",
- "36.97447",
- "122.02899",
- "pepperoni",
- "dog",
- "No",
- "no preference",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Data Science",
- "53703",
- "41",
- "87",
- "sausage",
- "dog",
- "No",
- "no preference",
- "No"
- ],
- [
- "LEC001",
- "20",
- "Science: Other|Environmental Science",
- "53715",
- "41.878113",
- "-87.629799",
- "green pepper",
- "cat",
- "No",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "24",
- "Economics",
- "53703",
- "40",
- "-90",
- "pineapple",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "",
- "Data Science",
- "53706",
- "40.416775",
- "-3.70379",
- "none (just cheese)",
- "dog",
- "Yes",
- "no preference",
- "Yes"
- ],
- [
- "LEC001",
- "37",
- "Data Science",
- "53718",
- "43.073051",
- "-89.40123",
- "green pepper",
- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "21",
- "Data Science",
- "53703",
- "30.572351",
- "121.776761",
- "pepperoni",
- "cat",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "22",
- "consumer behavior and marketplace studies",
- "53715",
- "43.653225",
- "-79.383186",
- "mushroom",
- "cat",
- "Yes",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "20",
- "Computer Science",
- "53715",
- "41",
- "-87",
- "Other",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "17",
- "Statistics",
- "53715",
- "43.0722",
- "89.4008",
- "pineapple",
- "dog",
- "No",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Economics",
- "53715",
- "27.99942",
- "120.66682",
- "pepperoni",
- "dog",
- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "19",
- "Mathematics/AMEP",
- "53711",
- "45.85038",
- "-84.616989",
- "pineapple",
- "cat",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "23",
- "Economics",
- "53703",
- "43.07348",
- "-89.38089",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "29",
- "Business: Other|Technology Strategy/ Product Management",
- "53705",
- "37.386051",
- "-122.083855",
- "Other",
- "cat",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Biomedical",
- "53715",
- "43.073051",
- "-89.40123",
- "sausage",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Data Science",
- "53703",
- "23.885942",
- "45.079163",
- "mushroom",
- "neither",
- "No",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "30",
- "Business: Other",
- "53705",
- "43.07175",
- "-89.46498",
- "pineapple",
- "cat",
- "No",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "20",
- "Business: Other|Consumer Behavior and Marketplace Studies",
- "53703",
- "40.76078",
- "-111.891045",
- "green pepper",
- "dog",
- "Yes",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "21",
- "Data Science",
- "53705",
- "40.712776",
- "-74.005974",
- "pepperoni",
- "cat",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53715",
- "43",
- "-90",
- "sausage",
- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Business: Information Systems",
- "53711",
- "34.385204",
- "132.455292",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
- "LEC001",
- "22",
- "International Studies",
- "53703",
- "48.13913",
- "11.58022",
- "none (just cheese)",
- "cat",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Other",
- "53715",
- "38.331581",
- "-75.086159",
- "macaroni/pasta",
- "dog",
- "No",
- "no preference",
- "Yes"
- ],
- [
- "LEC001",
- "21",
- "Data Science",
- "53703",
- "41.00824",
- "28.978359",
- "pepperoni",
- "cat",
- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53706",
- "43.77195",
- "-88.43383",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Economics",
- "53726",
- "42.92",
- "-87.96",
- "pepperoni",
- "dog",
- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53715",
- "29.424122",
- "-98.493629",
- "mushroom",
- "dog",
- "Yes",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Agricultural and Applied Economics",
- "53703",
- "-22.932924",
- "-47.073845",
- "pineapple",
- "cat",
- "Yes",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "25",
- "Medicine",
- "53703",
- "48.38203",
- "-123.537827",
- "basil/spinach",
- "dog",
- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "20",
- "Business: Other|Real Estate",
- "53703",
- "51.5",
- "0.128",
- "mushroom",
- "dog",
- "Yes",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "19",
- "Computer Science",
- "53706",
- "40",
- "-74",
- "pepperoni",
- "cat",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Data Science",
- "53715",
- "40.712776",
- "-74.005974",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "24",
- "Engineering: Industrial",
- "53705",
- "13.100485",
- "77.594009",
- "none (just cheese)",
- "dog",
- "Yes",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "28",
- "Science: Biology/Life",
- "53703",
- "7.190708",
- "125.455338",
- "sausage",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Industrial",
- "53715",
- "47.606209",
- "-122.332069",
- "pepperoni",
- "cat",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "17",
- "Computer Science",
- "53726",
- "21.027763",
- "105.83416",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
- "LEC001",
- "20",
- "Business: Information Systems",
- "53711",
- "45.046799",
- "-87.298149",
- "sausage",
- "cat",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53715",
- "64.126518",
- "-21.817438",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "20",
- "Computer Science",
- "53715",
- "20.880947",
- "-156.681862",
- "sausage",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53703",
- "-37.813629",
- "144.963058",
- "sausage",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "21",
- "Mathematics/AMEP",
- "53703",
- "34.29006",
- "108.932941",
- "basil/spinach",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53562",
- "43.096851",
- "-89.511528",
- "sausage",
- "dog",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "",
- "Computer Science",
- "53715",
- "31.469279",
- "119.765621",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "21",
- "Science: Chemistry",
- "53715",
- "38.892059",
- "-77.019913",
- "pepperoni",
- "neither",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Data Science",
- "53703",
- "24.713552",
- "46.675297",
- "none (just cheese)",
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- "pepperoni",
- "cat",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC003",
- "18",
- "Mathematics/AMEP",
- "53706",
- "42.99571",
- "-90",
- "sausage",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC003",
- "19",
- "Engineering: Industrial",
- "53715",
- "24.713552",
- "46.675297",
- "basil/spinach",
- "neither",
- "Yes",
- "early bird",
- "Maybe"
- ],
- [
- "LEC003",
- "19",
- "Engineering: Mechanical",
- "53705",
- "46.589146",
- "-112.039108",
- "none (just cheese)",
- "cat",
- "No",
- "night owl",
- "Yes"
- ]
- ]
-}
\ No newline at end of file
diff --git a/f22/meena_lec_notes/lec-19/major_cs220_data.json b/f22/meena_lec_notes/lec-19/major_cs220_data.json
deleted file mode 100644
index a1a5270..0000000
--- a/f22/meena_lec_notes/lec-19/major_cs220_data.json
+++ /dev/null
@@ -1,13094 +0,0 @@
-{
- "Engineering: Biomedical": [
- [
- "LEC001",
- "22",
- "Engineering: Biomedical",
- "53703",
- "43.073051",
- "-89.40123",
- "none (just cheese)",
- "neither",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC006",
- "18",
- "Engineering: Biomedical",
- "53051",
- "33.6846",
- "117.8265",
- "pepperoni",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC004",
- "20",
- "Engineering: Biomedical",
- "53715",
- "43.0707",
- "12.6196",
- "tater tots",
- "dog",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC004",
- "19",
- "Engineering: Biomedical",
- "53715",
- "41.878113",
- "-87.629799",
- "mushroom",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC005",
- "18",
- "Engineering: Biomedical",
- "53593",
- "43.073051",
- "-89.40123",
- "green pepper",
- "cat",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC002",
- "19",
- "Engineering: Biomedical",
- "53706",
- "48.494904",
- "-113.979034",
- "macaroni/pasta",
- "cat",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC004",
- "",
- "Engineering: Biomedical",
- "53715",
- "41.385063",
- "2.173404",
- "pepperoni",
- "dog",
- "Yes",
- "no preference",
- "No"
- ],
- [
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- "Engineering: Biomedical",
- "53706",
- "46.818188",
- "8.227512",
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- "dog",
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- ],
- [
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- "Engineering: Biomedical",
- "53703",
- "31.046051",
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- "Other",
- "dog",
- "No",
- "night owl",
- "Maybe"
- ],
- [
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- "18",
- "Engineering: Biomedical",
- "53715",
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- "sausage",
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- "early bird",
- "Yes"
- ],
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- "No",
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- ],
- [
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- "Engineering: Biomedical",
- "53706",
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- "144.96",
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- "Yes",
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- ],
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- "Engineering: Biomedical",
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- "early bird",
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- "night owl",
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- ],
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- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
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- "Engineering: Biomedical",
- "53706",
- "45.17099",
- "-87.16494",
- "Other",
- "dog",
- "No",
- "night owl",
- "Maybe"
- ],
- [
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- "18",
- "Engineering: Biomedical",
- "53706",
- "33.501324",
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- "pineapple",
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- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC002",
- "17",
- "Engineering: Biomedical",
- "53706",
- "39.5755",
- "-106.100403",
- "pepperoni",
- "dog",
- "Yes",
- "night owl",
- "Maybe"
- ],
- [
- "LEC005",
- "20",
- "Engineering: Biomedical",
- "53703",
- "47.497913",
- "19.040236",
- "Other",
- "cat",
- "Yes",
- "night owl",
- "No"
- ],
- [
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- "18",
- "Engineering: Biomedical",
- "53706",
- "21.161907",
- "-86.851524",
- "none (just cheese)",
- "dog",
- "No",
- "early bird",
- "Maybe"
- ],
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- "20",
- "Engineering: Biomedical",
- "53703",
- "43.07393",
- "-89.38524",
- "sausage",
- "dog",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Engineering: Biomedical",
- "53715",
- "45.983964",
- "9.262161",
- "sausage",
- "dog",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC005",
- "18",
- "Engineering: Biomedical",
- "53715",
- "46.58276",
- "7.08058",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "No"
- ],
- [
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- "20",
- "Engineering: Biomedical",
- "53715",
- "28.538336",
- "-81.379234",
- "sausage",
- "cat",
- "No",
- "night owl",
- "Maybe"
- ],
- [
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- "Engineering: Biomedical",
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- "basil/spinach",
- "dog",
- "No",
- "night owl",
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- ],
- [
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- "53711",
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- "87.6298",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
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- "",
- "Engineering: Biomedical",
- "53715",
- "41.878113",
- "-87.629799",
- "pepperoni",
- "dog",
- "Yes",
- "night owl",
- "No"
- ],
- [
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- "Engineering: Biomedical",
- "53703",
- "48.8566",
- "2.3522",
- "mushroom",
- "cat",
- "Yes",
- "night owl",
- "Maybe"
- ],
- [
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- "Engineering: Biomedical",
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- "-33.86882",
- "151.20929",
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- "dog",
- "No",
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- ],
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- "45.440845",
- "12.315515",
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- "Yes"
- ],
- [
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- "33.684566",
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- "Yes",
- "early bird",
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- ],
- [
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- "42.361145",
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- "macaroni/pasta",
- "dog",
- "No",
- "night owl",
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- ],
- [
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- "Engineering: Biomedical",
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- "-89.385239",
- "basil/spinach",
- "dog",
- "No",
- "early bird",
- "No"
- ],
- [
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- "53703",
- "41.198496",
- "0.773436",
- "pepperoni",
- "dog",
- "No",
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- "Yes"
- ],
- [
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- "21",
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- "44.513317",
- "-88.013298",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "No"
- ],
- [
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- "19",
- "Engineering: Biomedical",
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- "51.1784",
- "115.5708",
- "pineapple",
- "dog",
- "Yes",
- "night owl",
- "No"
- ],
- [
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- "Engineering: Biomedical",
- "53715",
- "40.63",
- "14.6",
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- "dog",
- "No",
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- "Maybe"
- ],
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- "53701",
- "43.038902",
- "-87.906471",
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- "No",
- "night owl",
- "No"
- ],
- [
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- "117.161087",
- "pepperoni",
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- "no preference",
- "Yes"
- ],
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- "53703",
- "41.878113",
- "-87.629799",
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- "dog",
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- "no preference",
- "Yes"
- ],
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- "Engineering: Biomedical",
- "53706",
- "45.4894",
- "93.2476",
- "mushroom",
- "cat",
- "No",
- "night owl",
- "No"
- ],
- [
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- "basil/spinach",
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- "No"
- ],
- [
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- "30.328227",
- "-86.136975",
- "pepperoni",
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- "Yes",
- "no preference",
- "Maybe"
- ]
- ],
- "Undecided": [
- [
- "LEC006",
- "",
- "Undecided",
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- "43.073051",
- "-89.40123",
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- "neither",
- "No",
- "no preference",
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- ],
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- "53706",
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- "-89.40123",
- "none (just cheese)",
- "neither",
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- [
- "LEC002",
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- "Undecided",
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- "43.073051",
- "-89.40123",
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- "neither",
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- "no preference",
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- "53706",
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- "none (just cheese)",
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- ],
- [
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- "18",
- "Undecided",
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- "38.56247",
- "-121.70411",
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- "night owl",
- "Yes"
- ],
- [
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- "48.775845",
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- "30.5723",
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- "No",
- "night owl",
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- ],
- [
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- "18",
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- "41.256538",
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- ],
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- [
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- "43.073051",
- "-89.40123",
- "pineapple",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
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- "62.2001",
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- [
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- ],
- [
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- "-92.100487",
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- "cat",
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- "no preference",
- "Yes"
- ],
- [
- "LEC005",
- "18",
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- "43.073929",
- "-89.385239",
- "sausage",
- "dog",
- "Yes",
- "early bird",
- "Yes"
- ],
- [
- "LEC003",
- "18",
- "Undecided",
- "53706",
- "43.2967",
- "87.9876",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC004",
- "18",
- "Undecided",
- "53706",
- "39.3823",
- "87.2971",
- "sausage",
- "dog",
- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC004",
- "18",
- "Undecided",
- "53706",
- "26.452",
- "-81.9481",
- "pepperoni",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC005",
- "18",
- "Undecided",
- "53706",
- "55.676098",
- "12.568337",
- "pepperoni",
- "dog",
- "Yes",
- "night owl",
- "No"
- ],
- [
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- "18",
- "Undecided",
- "53706",
- "43.038902",
- "-87.906471",
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- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
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- "11.255814",
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- "No",
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- ],
- [
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- "19",
- "Undecided",
- "53715",
- "43.041069",
- "-87.909416",
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- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "18",
- "Undecided",
- "53706",
- "44.8341",
- "87.377",
- "basil/spinach",
- "dog",
- "No",
- "no preference",
- "Yes"
- ]
- ],
- "Engineering: Industrial": [
- [
- "LEC004",
- "18",
- "Engineering: Industrial",
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- "43.073051",
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- ],
- [
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- "78.486671",
- "mushroom",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
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- "18",
- "Engineering: Industrial",
- "53715",
- "30.733315",
- "76.779419",
- "green pepper",
- "cat",
- "No",
- "no preference",
- "Yes"
- ],
- [
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- "Engineering: Industrial",
- "53706",
- "55.953251",
- "-3.188267",
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- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC002",
- "19",
- "Engineering: Industrial",
- "53703",
- "41.878",
- "-87.63",
- "pepperoni",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Industrial",
- "53706",
- "19.655041",
- "-101.169891",
- "pepperoni",
- "dog",
- "Yes",
- "no preference",
- "Maybe"
- ],
- [
- "LEC005",
- "19",
- "Engineering: Industrial",
- "53703",
- "22.2255",
- "-159.4835",
- "pepperoni",
- "cat",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC004",
- "18",
- "Engineering: Industrial",
- "53706",
- "41.878113",
- "41.878113",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC003",
- "18",
- "Engineering: Industrial",
- "53706",
- "18.92421",
- "-99.221565",
- "green pepper",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC002",
- "20",
- "Engineering: Industrial",
- "53703",
- "44.389",
- "12.9908",
- "sausage",
- "dog",
- "No",
- "early bird",
- "Maybe"
- ],
- [
- "LEC004",
- "21",
- "Engineering: Industrial",
- "53703",
- "37.94048",
- "-78.63664",
- "Other",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
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- "18",
- "Engineering: Industrial",
- "53715",
- "40.712776",
- "-74.005974",
- "pineapple",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC006",
- "20",
- "Engineering: Industrial",
- "53703",
- "42.102901",
- "-88.368896",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC002",
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- "Engineering: Industrial",
- "53726",
- "43.038902",
- "-87.906471",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC006",
- "19",
- "Engineering: Industrial",
- "60540",
- "41.878113",
- "-87.629799",
- "none (just cheese)",
- "dog",
- "No",
- "night owl",
- "No"
- ],
- [
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- "Engineering: Industrial",
- "53705",
- "35.084385",
- "-106.650421",
- "pineapple",
- "cat",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC005",
- "19",
- "Engineering: Industrial",
- "53703",
- "42.03992",
- "87.67732",
- "sausage",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC003",
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- "Business analytics": [
- [
- "LEC001",
- "",
- "Business analytics",
- "53705",
- "45.50169",
- "-73.567253",
- "pineapple",
- "cat",
- "No",
- "no preference",
- "No"
- ]
- ],
- "Legal Studies": [
- [
- "LEC004",
- "20",
- "Legal Studies",
- "53703",
- "20.798363",
- "-156.331924",
- "green pepper",
- "dog",
- "No",
- "early bird",
- "No"
- ]
- ],
- "Journalism: Strategic Comm./Advertising": [
- [
- "LEC004",
- "20",
- "Journalism: Strategic Comm./Advertising",
- "53703",
- "43.073051",
- "-89.40123",
- "Other",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ]
- ],
- "Master of Public Affairs": [
- [
- "LEC004",
- "26",
- "Master of Public Affairs",
- "53715",
- "48.118145",
- "-123.43074",
- "basil/spinach",
- "dog",
- "Yes",
- "early bird",
- "Yes"
- ]
- ],
- "Environment & Resources": [
- [
- "LEC004",
- "27",
- "Environment & Resources",
- "53703",
- "37.389091",
- "-5.984459",
- "mushroom",
- "dog",
- "No",
- "night owl",
- "Maybe"
- ]
- ],
- "Environmental Studies": [
- [
- "LEC004",
- "18",
- "Environmental Studies",
- "53703",
- "42.360081",
- "-71.058884",
- "pineapple",
- "cat",
- "No",
- "no preference",
- "Maybe"
- ]
- ]
-}
\ No newline at end of file
diff --git a/f22/meena_lec_notes/lec-19/numsA.json b/f22/meena_lec_notes/lec-19/numsA.json
deleted file mode 100644
index 12bae17..0000000
--- a/f22/meena_lec_notes/lec-19/numsA.json
+++ /dev/null
@@ -1 +0,0 @@
-[1, 2, 3, 4]
diff --git a/f22/meena_lec_notes/lec-19/score_history.json b/f22/meena_lec_notes/lec-19/score_history.json
deleted file mode 100644
index 55563a2..0000000
--- a/f22/meena_lec_notes/lec-19/score_history.json
+++ /dev/null
@@ -1,17 +0,0 @@
-{
- "Meena": [
- 10,
- 20,
- 10
- ],
- "Viyan": [
- 40,
- 50,
- 70,
- 70
- ],
- "Rogers": [
- 10,
- 40
- ]
-}
\ No newline at end of file
diff --git a/f22/meena_lec_notes/lec-19/section_cs220_data.json b/f22/meena_lec_notes/lec-19/section_cs220_data.json
deleted file mode 100644
index de596de..0000000
--- a/f22/meena_lec_notes/lec-19/section_cs220_data.json
+++ /dev/null
@@ -1,12910 +0,0 @@
-{
- "LEC001": [
- [
- "LEC001",
- "22",
- "Engineering: Biomedical",
- "53703",
- "43.073051",
- "-89.40123",
- "none (just cheese)",
- "neither",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "",
- "Mathematics/AMEP",
- "53706",
- "31.230391",
- "121.473701",
- "basil/spinach",
- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Economics (Mathematical Emphasis)",
- "53703",
- "48.86",
- "2.3522",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53703",
- "24.7",
- "46.7",
- "mushroom",
- "dog",
- "Yes",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "23",
- "Computer Science",
- "53711",
- "43.073929",
- "-89.385239",
- "sausage",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "22",
- "Engineering: Mechanical",
- "53719",
- "43.073051",
- "-89.40123",
- "none (just cheese)",
- "cat",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Computer Science",
- "53706",
- "26.2992",
- "87.2625",
- "mushroom",
- "dog",
- "Yes",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "24",
- "Business: Information Systems",
- "53703",
- "43.073051",
- "-89.40123",
- "macaroni/pasta",
- "cat",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "",
- "Computer Science",
- "53715",
- "34.052235",
- "-118.243683",
- "green pepper",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "26",
- "Engineering: Mechanical",
- "53703",
- "41.902782",
- "12.496365",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "25",
- "Economics",
- "53703",
- "40.712776",
- "-74.005974",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Computer Science",
- "53706",
- "48.855709",
- "2.29889",
- "pepperoni",
- "cat",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "21",
- "Computer Science",
- "53715",
- "16.306652",
- "80.436539",
- "Other",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Industrial",
- "53715",
- "30.733315",
- "76.779419",
- "green pepper",
- "cat",
- "No",
- "no preference",
- "Yes"
- ],
- [
- "LEC001",
- "20",
- "Economics (Mathematical Emphasis)",
- "53703",
- "43.073929",
- "-89.385239",
- "macaroni/pasta",
- "cat",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "21",
- "Business: Finance",
- "53711",
- "43.073929",
- "-89.385239",
- "pepperoni",
- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "19",
- "Computer Science",
- "53703",
- "51.507351",
- "-0.127758",
- "sausage",
- "cat",
- "Yes",
- "no preference",
- "Yes"
- ],
- [
- "LEC001",
- "21",
- "Science: Biology/Life",
- "53703",
- "36",
- "117",
- "macaroni/pasta",
- "dog",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Other",
- "53706",
- "41.902782",
- "12.496365",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Industrial",
- "53706",
- "19.655041",
- "-101.169891",
- "pepperoni",
- "dog",
- "Yes",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Business: Actuarial",
- "53703",
- "42.28",
- "-83.74",
- "mushroom",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Business: Information Systems",
- "53703",
- "39.481655",
- "-106.038353",
- "macaroni/pasta",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "20",
- "Business: Other|Business: Accounting",
- "53703",
- "31.230391",
- "121.473701",
- "pepperoni",
- "cat",
- "Yes",
- "no preference",
- "No"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53706",
- "35.142441",
- "-223.154297",
- "green pepper",
- "neither",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "",
- "Engineering: Mechanical",
- "53715",
- "19.8968",
- "155.5828",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "21",
- "Computer Science",
- "53703",
- "43.21518",
- "-87.94241",
- "pepperoni",
- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "22",
- "Engineering: Mechanical",
- "53703",
- "47.497913",
- "19.040236",
- "pepperoni",
- "dog",
- "No",
- "no preference",
- "No"
- ],
- [
- "LEC001",
- "20",
- "Business andministration",
- "53703",
- "37.389091",
- "-5.984459",
- "pineapple",
- "dog",
- "Yes",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Computer Science",
- "53703",
- "40.7128",
- "74.006",
- "pepperoni",
- "dog",
- "Yes",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "22",
- "Engineering: Mechanical",
- "53726",
- "36.97447",
- "122.02899",
- "pepperoni",
- "dog",
- "No",
- "no preference",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Data Science",
- "53703",
- "41",
- "87",
- "sausage",
- "dog",
- "No",
- "no preference",
- "No"
- ],
- [
- "LEC001",
- "20",
- "Science: Other|Environmental Science",
- "53715",
- "41.878113",
- "-87.629799",
- "green pepper",
- "cat",
- "No",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "24",
- "Economics",
- "53703",
- "40",
- "-90",
- "pineapple",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "",
- "Data Science",
- "53706",
- "40.416775",
- "-3.70379",
- "none (just cheese)",
- "dog",
- "Yes",
- "no preference",
- "Yes"
- ],
- [
- "LEC001",
- "37",
- "Data Science",
- "53718",
- "43.073051",
- "-89.40123",
- "green pepper",
- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "21",
- "Data Science",
- "53703",
- "30.572351",
- "121.776761",
- "pepperoni",
- "cat",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "22",
- "consumer behavior and marketplace studies",
- "53715",
- "43.653225",
- "-79.383186",
- "mushroom",
- "cat",
- "Yes",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "20",
- "Computer Science",
- "53715",
- "41",
- "-87",
- "Other",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "17",
- "Statistics",
- "53715",
- "43.0722",
- "89.4008",
- "pineapple",
- "dog",
- "No",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Economics",
- "53715",
- "27.99942",
- "120.66682",
- "pepperoni",
- "dog",
- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "19",
- "Mathematics/AMEP",
- "53711",
- "45.85038",
- "-84.616989",
- "pineapple",
- "cat",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "23",
- "Economics",
- "53703",
- "43.07348",
- "-89.38089",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "29",
- "Business: Other|Technology Strategy/ Product Management",
- "53705",
- "37.386051",
- "-122.083855",
- "Other",
- "cat",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Biomedical",
- "53715",
- "43.073051",
- "-89.40123",
- "sausage",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Data Science",
- "53703",
- "23.885942",
- "45.079163",
- "mushroom",
- "neither",
- "No",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "30",
- "Business: Other",
- "53705",
- "43.07175",
- "-89.46498",
- "pineapple",
- "cat",
- "No",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "20",
- "Business: Other|Consumer Behavior and Marketplace Studies",
- "53703",
- "40.76078",
- "-111.891045",
- "green pepper",
- "dog",
- "Yes",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "21",
- "Data Science",
- "53705",
- "40.712776",
- "-74.005974",
- "pepperoni",
- "cat",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53715",
- "43",
- "-90",
- "sausage",
- "dog",
- "No",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Business: Information Systems",
- "53711",
- "34.385204",
- "132.455292",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
- "LEC001",
- "22",
- "International Studies",
- "53703",
- "48.13913",
- "11.58022",
- "none (just cheese)",
- "cat",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Other",
- "53715",
- "38.331581",
- "-75.086159",
- "macaroni/pasta",
- "dog",
- "No",
- "no preference",
- "Yes"
- ],
- [
- "LEC001",
- "21",
- "Data Science",
- "53703",
- "41.00824",
- "28.978359",
- "pepperoni",
- "cat",
- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53706",
- "43.77195",
- "-88.43383",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Economics",
- "53726",
- "42.92",
- "-87.96",
- "pepperoni",
- "dog",
- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53715",
- "29.424122",
- "-98.493629",
- "mushroom",
- "dog",
- "Yes",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "20",
- "Agricultural and Applied Economics",
- "53703",
- "-22.932924",
- "-47.073845",
- "pineapple",
- "cat",
- "Yes",
- "early bird",
- "Maybe"
- ],
- [
- "LEC001",
- "25",
- "Medicine",
- "53703",
- "48.38203",
- "-123.537827",
- "basil/spinach",
- "dog",
- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "20",
- "Business: Other|Real Estate",
- "53703",
- "51.5",
- "0.128",
- "mushroom",
- "dog",
- "Yes",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "19",
- "Computer Science",
- "53706",
- "40",
- "-74",
- "pepperoni",
- "cat",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Data Science",
- "53715",
- "40.712776",
- "-74.005974",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "24",
- "Engineering: Industrial",
- "53705",
- "13.100485",
- "77.594009",
- "none (just cheese)",
- "dog",
- "Yes",
- "no preference",
- "Maybe"
- ],
- [
- "LEC001",
- "28",
- "Science: Biology/Life",
- "53703",
- "7.190708",
- "125.455338",
- "sausage",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Industrial",
- "53715",
- "47.606209",
- "-122.332069",
- "pepperoni",
- "cat",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "17",
- "Computer Science",
- "53726",
- "21.027763",
- "105.83416",
- "pepperoni",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
- "LEC001",
- "20",
- "Business: Information Systems",
- "53711",
- "45.046799",
- "-87.298149",
- "sausage",
- "cat",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53715",
- "64.126518",
- "-21.817438",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "20",
- "Computer Science",
- "53715",
- "20.880947",
- "-156.681862",
- "sausage",
- "dog",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53703",
- "-37.813629",
- "144.963058",
- "sausage",
- "dog",
- "Yes",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "21",
- "Mathematics/AMEP",
- "53703",
- "34.29006",
- "108.932941",
- "basil/spinach",
- "dog",
- "No",
- "early bird",
- "Yes"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53562",
- "43.096851",
- "-89.511528",
- "sausage",
- "dog",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "",
- "Computer Science",
- "53715",
- "31.469279",
- "119.765621",
- "pepperoni",
- "dog",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "21",
- "Science: Chemistry",
- "53715",
- "38.892059",
- "-77.019913",
- "pepperoni",
- "neither",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Data Science",
- "53703",
- "24.713552",
- "46.675297",
- "none (just cheese)",
- "neither",
- "No",
- "night owl",
- "Yes"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Biomedical",
- "53706",
- "33.501324",
- "-111.925278",
- "pineapple",
- "dog",
- "Yes",
- "early bird",
- "No"
- ],
- [
- "LEC001",
- "19",
- "Science: Biology/Life",
- "53706",
- "20.788602",
- "-156.003662",
- "green pepper",
- "dog",
- "Yes",
- "no preference",
- "No"
- ],
- [
- "LEC001",
- "18",
- "Engineering: Mechanical",
- "53703",
- "23.885942",
- "45.079163",
- "Other",
- "cat",
- "No",
- "night owl",
- "Maybe"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Industrial",
- "53705",
- "41.878113",
- "-87.629799",
- "tater tots",
- "cat",
- "No",
- "night owl",
- "No"
- ],
- [
- "LEC001",
- "19",
- "Engineering: Mechanical",
- "53703",
- "44.977753",
- "-93.265015",
- "Other",
- "cat",
- "Yes",
- "early bird",
- "No"
- ],
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-}
\ No newline at end of file
--
GitLab