From 11052b28b124233d26303750944b838f83b0cb0e Mon Sep 17 00:00:00 2001
From: Anshul Gupta <ansg191@anshulg.com>
Date: Thu, 22 Feb 2024 16:53:07 -0800
Subject: Adds some formatting

---
 CS105MiniProject.ipynb | 184 ++++++++++++++++++++-----------------------------
 1 file changed, 75 insertions(+), 109 deletions(-)

(limited to 'CS105MiniProject.ipynb')

diff --git a/CS105MiniProject.ipynb b/CS105MiniProject.ipynb
index ffb4fa4..c783024 100644
--- a/CS105MiniProject.ipynb
+++ b/CS105MiniProject.ipynb
@@ -1,65 +1,66 @@
 {
  "cells": [
   {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "daa13044",
+   "cell_type": "markdown",
+   "source": [
+    "<div>\n",
+    "    <h1><center>CS105 Mini-Project</center></h1>\n",
+    "    <p>By: <b>NAMES HERE</b></p>\n",
+    "</div>"
+   ],
    "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/",
-     "height": 614
-    },
-    "id": "daa13044",
-    "outputId": "4d440aaa-1ee7-4771-c526-f55e9458ca8a",
-    "ExecuteTime": {
-     "end_time": "2024-02-23T01:01:41.396867Z",
-     "start_time": "2024-02-23T01:01:40.758392Z"
-    }
+    "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": "              Timestamp What is your current class standing?  \\\n0     2/9/2024 20:12:14                               Senior   \n1     2/9/2024 20:16:34                               Junior   \n2     2/9/2024 20:18:55                               Junior   \n3     2/9/2024 20:24:00                               Senior   \n4     2/9/2024 20:26:16                             Graduate   \n..                  ...                                  ...   \n255  2/14/2024 19:46:28                               Junior   \n256   2/15/2024 0:28:38                                  NaN   \n257   2/15/2024 8:33:45                               Senior   \n258  2/15/2024 16:10:40                            Sophomore   \n259  2/15/2024 16:14:11                            Sophomore   \n\n    Who do you live with?   \\\n0                  Neither   \n1                     Both   \n2                  Friends   \n3                  Neither   \n4                  Neither   \n..                     ...   \n255                Friends   \n256                 Family   \n257                 Family   \n258                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n4                                            Apartment        \n..                                                 ...        \n255                                              House        \n256                                          Apartment        \n257                                              House        \n258                                          Apartment        \n259                                               Dorm        \n\n    How many people live in your household? Do you currently work?  \\\n0                                         6                    Yes   \n1                                         4                     No   \n2                                         4                     No   \n3                                         1                     No   \n4                                         1                    Yes   \n..                                      ...                    ...   \n255                                       5                    Yes   \n256             North District 4 bed 2 bath                     No   \n257                                       9                     No   \n258                                       4                    Yes   \n259      3 (room), 8 (hall), ~70 (building)                     No   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n1                                               NaN   \n2                                               NaN   \n3                                               NaN   \n4                                           10 - 20   \n..                                              ...   \n255                                         10 - 20   \n256                                             NaN   \n257                                           1 - 5   \n258                                          5 - 10   \n259                                             NaN   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n1                             NaN   \n2                             NaN   \n3                             NaN   \n4                      Off-campus   \n..                            ...   \n255                     On-campus   \n256                           NaN   \n257                    Off-campus   \n258                     On-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n1                                                  NaN   \n2                                                  NaN   \n3                                                   No   \n4                                                  Yes   \n..                                                 ...   \n255                                                 No   \n256                                                NaN   \n257                                                 No   \n258                                                 No   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n4                                                   No  \n..                                                 ...  \n255                                                 No  \n256                                                 No  \n257                                                 No  \n258                                                 No  \n259                                                Yes  \n\n[260 rows x 10 columns]",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2/9/2024 20:12:14</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2/9/2024 20:16:34</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2/9/2024 20:18:55</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2/9/2024 20:24:00</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2/9/2024 20:26:16</td>\n      <td>Graduate</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>2/14/2024 19:46:28</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>2/15/2024 0:28:38</td>\n      <td>NaN</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>North District 4 bed 2 bath</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>2/15/2024 8:33:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>1 - 5</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>2/15/2024 16:10:40</td>\n      <td>Sophomore</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>2/15/2024 16:14:11</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3 (room), 8 (hall), ~70 (building)</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>260 rows × 10 columns</p>\n</div>"
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
+   "id": "845bdbd833f03cba"
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "# Data Loading & Preprocessing"
    ],
+   "metadata": {
+    "collapsed": false
+   },
+   "id": "d720609d765d221b"
+  },
+  {
+   "cell_type": "code",
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import pandas as pd\n",
     "import numpy as np\n",
     "\n",
+    "# Load dataframe from data.csv\n",
     "df = pd.read_csv(\"data.csv\")\n",
+    "\n",
+    "# Select relevant columns\n",
     "df = df.iloc[:, [0, 2, 7, 8, 9, 58, 59, 60, 61, 26]]\n",
     "df"
-   ]
+   ],
+   "metadata": {
+    "collapsed": false
+   },
+   "id": "3bea6ea662d6c063"
   },
   {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "29889175",
+   "cell_type": "markdown",
+   "source": [
+    "## Preprocessing"
+   ],
    "metadata": {
-    "id": "29889175",
-    "ExecuteTime": {
-     "end_time": "2024-02-23T01:01:41.409516Z",
-     "start_time": "2024-02-23T01:01:41.398267Z"
-    }
+    "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": "              Timestamp What is your current class standing?  \\\n0     2/9/2024 20:12:14                               Senior   \n1     2/9/2024 20:16:34                               Junior   \n2     2/9/2024 20:18:55                               Junior   \n3     2/9/2024 20:24:00                               Senior   \n4     2/9/2024 20:26:16                             Graduate   \n..                  ...                                  ...   \n255  2/14/2024 19:46:28                               Junior   \n256   2/15/2024 0:28:38                                  NaN   \n257   2/15/2024 8:33:45                               Senior   \n258  2/15/2024 16:10:40                            Sophomore   \n259  2/15/2024 16:14:11                            Sophomore   \n\n    Who do you live with?   \\\n0                  Neither   \n1                     Both   \n2                  Friends   \n3                  Neither   \n4                  Neither   \n..                     ...   \n255                Friends   \n256                 Family   \n257                 Family   \n258                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n4                                            Apartment        \n..                                                 ...        \n255                                              House        \n256                                          Apartment        \n257                                              House        \n258                                          Apartment        \n259                                               Dorm        \n\n     How many people live in your household? Do you currently work?  \\\n0                                          6                    Yes   \n1                                          4                     No   \n2                                          4                     No   \n3                                          1                     No   \n4                                          1                    Yes   \n..                                       ...                    ...   \n255                                        5                    Yes   \n256                                        4                     No   \n257                                        9                     No   \n258                                        4                    Yes   \n259                                        3                     No   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n1                                                 0   \n2                                                 0   \n3                                                 0   \n4                                           10 - 20   \n..                                              ...   \n255                                         10 - 20   \n256                                               0   \n257                                               0   \n258                                          5 - 10   \n259                                               0   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n1                             NaN   \n2                             NaN   \n3                             NaN   \n4                      Off-campus   \n..                            ...   \n255                     On-campus   \n256                           NaN   \n257                    Off-campus   \n258                     On-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n1                                                  NaN   \n2                                                  NaN   \n3                                                  NaN   \n4                                                  Yes   \n..                                                 ...   \n255                                                 No   \n256                                                NaN   \n257                                                NaN   \n258                                                 No   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n4                                                   No  \n..                                                 ...  \n255                                                 No  \n256                                                 No  \n257                                                 No  \n258                                                 No  \n259                                                Yes  \n\n[260 rows x 10 columns]",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2/9/2024 20:12:14</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2/9/2024 20:16:34</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2/9/2024 20:18:55</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2/9/2024 20:24:00</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2/9/2024 20:26:16</td>\n      <td>Graduate</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>2/14/2024 19:46:28</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>2/15/2024 0:28:38</td>\n      <td>NaN</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>2/15/2024 8:33:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>0</td>\n      <td>Off-campus</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>2/15/2024 16:10:40</td>\n      <td>Sophomore</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>2/15/2024 16:14:11</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>260 rows × 10 columns</p>\n</div>"
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "id": "7e69a5a21a9de4ee"
+  },
+  {
+   "cell_type": "code",
+   "outputs": [],
    "source": [
+    "# Fixes empty values\n",
+    "df['Do you currently work?'] = df['Do you currently work?'].fillna('No')\n",
+    "\n",
+    "# Replaces custom text answers with appropriate values\n",
     "df['How many people live in your household?'] = (df['How many people live in your household?']\n",
     "                                                 .fillna(0)\n",
     "                                                 .replace('4 in total', '4')\n",
@@ -70,67 +71,43 @@
     "                                                 .replace('North District 4 bed 2 bath', '4')\n",
     "                                                 .replace('3 (room), 8 (hall), ~70 (building)', '3')\n",
     "                                                 .astype(int))\n",
-    "df.loc[df['Do you currently work?'] == 'No', 'How many hours do you work per week on average?'] = 0\n",
     "df['Who do you live with? '] = df['Who do you live with? '].replace('Family, Friends', 'Both').replace('Family, Friends, Both', 'Both')\n",
+    "# Normalizes non-applicable answers\n",
+    "df.loc[df['Do you currently work?'] == 'No', 'How many hours do you work per week on average?'] = 0\n",
     "df.loc[df['Do you currently work?'] == 'No', 'Do you work in a department related to your major?'] = np.nan\n",
+    "\n",
     "df"
-   ]
+   ],
+   "metadata": {
+    "collapsed": false
+   },
+   "id": "f71f8085d5f66b0"
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "id": "de4448fd64205d85",
-   "metadata": {
-    "collapsed": false,
-    "ExecuteTime": {
-     "end_time": "2024-02-23T01:01:41.418974Z",
-     "start_time": "2024-02-23T01:01:41.410787Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": "              Timestamp What is your current class standing?  \\\n0     2/9/2024 20:12:14                               Senior   \n4     2/9/2024 20:26:16                             Graduate   \n8     2/9/2024 22:02:49                               Junior   \n9     2/9/2024 22:08:43                               Senior   \n13    2/9/2024 22:15:13                               Junior   \n..                  ...                                  ...   \n246  2/13/2024 19:37:02                             Graduate   \n247  2/13/2024 21:39:14                               Senior   \n252   2/14/2024 9:48:12                               Junior   \n255  2/14/2024 19:46:28                               Junior   \n258  2/15/2024 16:10:40                            Sophomore   \n\n    Who do you live with?   \\\n0                  Neither   \n4                  Neither   \n8                  Friends   \n9                   Family   \n13                  Family   \n..                     ...   \n246                 Family   \n247                Friends   \n252                 Family   \n255                Friends   \n258                 Family   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n4                                            Apartment        \n8                                                House        \n9                                                House        \n13                                           Apartment        \n..                                                 ...        \n246                                              House        \n247                                          Apartment        \n252                                              House        \n255                                              House        \n258                                          Apartment        \n\n     How many people live in your household? Do you currently work?  \\\n0                                          6                    Yes   \n4                                          1                    Yes   \n8                                          6                    Yes   \n9                                          5                    Yes   \n13                                         4                    Yes   \n..                                       ...                    ...   \n246                                        2                    Yes   \n247                                        3                    Yes   \n252                                        5                    Yes   \n255                                        5                    Yes   \n258                                        4                    Yes   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n4                                           10 - 20   \n8                                           10 - 20   \n9                                             1 - 5   \n13                                          10 - 20   \n..                                              ...   \n246                                         10 - 20   \n247                                         20 - 40   \n252                                         20 - 40   \n255                                         10 - 20   \n258                                          5 - 10   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n4                      Off-campus   \n8                       On-campus   \n9                       On-campus   \n13                     Off-campus   \n..                            ...   \n246                     On-campus   \n247                    Off-campus   \n252                    Off-campus   \n255                     On-campus   \n258                     On-campus   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n4                                                  Yes   \n8                                                   No   \n9                                                   No   \n13                                                  No   \n..                                                 ...   \n246                                                Yes   \n247                                                 No   \n252                                                 No   \n255                                                 No   \n258                                                 No   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n4                                                   No  \n8                                                   No  \n9                                                   No  \n13                                                  No  \n..                                                 ...  \n246                                                 No  \n247                                                Yes  \n252                                                 No  \n255                                                 No  \n258                                                 No  \n\n[77 rows x 10 columns]",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2/9/2024 20:12:14</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2/9/2024 20:26:16</td>\n      <td>Graduate</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>2/9/2024 22:02:49</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>2/9/2024 22:08:43</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>1 - 5</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>2/9/2024 22:15:13</td>\n      <td>Junior</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>246</th>\n      <td>2/13/2024 19:37:02</td>\n      <td>Graduate</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>2</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>247</th>\n      <td>2/13/2024 21:39:14</td>\n      <td>Senior</td>\n      <td>Friends</td>\n      <td>Apartment</td>\n      <td>3</td>\n      <td>Yes</td>\n      <td>20 - 40</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>252</th>\n      <td>2/14/2024 9:48:12</td>\n      <td>Junior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>20 - 40</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>2/14/2024 19:46:28</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>2/15/2024 16:10:40</td>\n      <td>Sophomore</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n  </tbody>\n</table>\n<p>77 rows × 10 columns</p>\n</div>"
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Working DataFrame\n",
     "w_df = df[df['Do you currently work?'] == 'Yes']\n",
     "# Not working DataFrame\n",
     "nw_df = df[df['Do you currently work?'] == 'No']\n",
     "w_df"
-   ]
+   ],
+   "metadata": {
+    "collapsed": false
+   },
+   "id": "6c1d9ee7948e6b9a"
   },
   {
    "cell_type": "code",
-   "outputs": [
-    {
-     "data": {
-      "text/plain": "              Timestamp What is your current class standing?  \\\n1     2/9/2024 20:16:34                               Junior   \n2     2/9/2024 20:18:55                               Junior   \n3     2/9/2024 20:24:00                               Senior   \n5     2/9/2024 20:45:09                               Junior   \n6     2/9/2024 21:55:59                            Sophomore   \n..                  ...                                  ...   \n253  2/14/2024 13:45:45                               Senior   \n254  2/14/2024 16:26:06                               Junior   \n256   2/15/2024 0:28:38                                  NaN   \n257   2/15/2024 8:33:45                               Senior   \n259  2/15/2024 16:14:11                            Sophomore   \n\n    Who do you live with?   \\\n1                     Both   \n2                  Friends   \n3                  Neither   \n5                     Both   \n6                  Friends   \n..                     ...   \n253                 Family   \n254                 Family   \n256                 Family   \n257                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n5                                            Apartment        \n6                                            Apartment        \n..                                                 ...        \n253                                              House        \n254                                              House        \n256                                          Apartment        \n257                                              House        \n259                                               Dorm        \n\n     How many people live in your household? Do you currently work?  \\\n1                                          4                     No   \n2                                          4                     No   \n3                                          1                     No   \n5                                          4                     No   \n6                                          4                     No   \n..                                       ...                    ...   \n253                                        6                     No   \n254                                        5                     No   \n256                                        4                     No   \n257                                        9                     No   \n259                                        3                     No   \n\n    How many hours do you work per week on average?  \\\n1                                                 0   \n2                                                 0   \n3                                                 0   \n5                                                 0   \n6                                                 0   \n..                                              ...   \n253                                               0   \n254                                               0   \n256                                               0   \n257                                               0   \n259                                               0   \n\n    Do you work on or off campus?  \\\n1                             NaN   \n2                             NaN   \n3                             NaN   \n5                             NaN   \n6                             NaN   \n..                            ...   \n253                           NaN   \n254                           NaN   \n256                           NaN   \n257                    Off-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n1                                                  NaN   \n2                                                  NaN   \n3                                                  NaN   \n5                                                  NaN   \n6                                                  NaN   \n..                                                 ...   \n253                                                NaN   \n254                                                NaN   \n256                                                NaN   \n257                                                NaN   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n5                                                   No  \n6                                                   No  \n..                                                 ...  \n253                                                 No  \n254                                                Yes  \n256                                                 No  \n257                                                 No  \n259                                                Yes  \n\n[176 rows x 10 columns]",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>2/9/2024 20:16:34</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2/9/2024 20:18:55</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2/9/2024 20:24:00</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2/9/2024 20:45:09</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2/9/2024 21:55:59</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>253</th>\n      <td>2/14/2024 13:45:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>6</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>254</th>\n      <td>2/14/2024 16:26:06</td>\n      <td>Junior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>2/15/2024 0:28:38</td>\n      <td>NaN</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>2/15/2024 8:33:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>0</td>\n      <td>Off-campus</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>2/15/2024 16:14:11</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>176 rows × 10 columns</p>\n</div>"
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "nw_df"
    ],
    "metadata": {
-    "collapsed": false,
-    "ExecuteTime": {
-     "end_time": "2024-02-23T01:01:41.427847Z",
-     "start_time": "2024-02-23T01:01:41.419852Z"
-    }
+    "collapsed": false
    },
-   "id": "5fe8ec7f22878e60",
-   "execution_count": 4
+   "id": "34f69a756f513fb7"
   },
   {
    "cell_type": "markdown",
@@ -144,20 +121,11 @@
    "metadata": {
     "collapsed": false
    },
-   "id": "899d85626b77db20"
+   "id": "d5c1424ddd30ca97"
   },
   {
    "cell_type": "code",
-   "outputs": [
-    {
-     "data": {
-      "text/plain": "<Figure size 800x800 with 1 Axes>",
-      "image/png": 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"
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "\n",
@@ -173,28 +141,26 @@
     "plt.show()\n"
    ],
    "metadata": {
-    "collapsed": false,
-    "ExecuteTime": {
-     "end_time": "2024-02-23T01:01:41.526696Z",
-     "start_time": "2024-02-23T01:01:41.430135Z"
-    }
+    "collapsed": false
    },
-   "id": "bfa40c9e9693481d",
-   "execution_count": 5
+   "id": "da1811cc63b41845"
   },
   {
    "cell_type": "code",
    "outputs": [],
    "source": [],
    "metadata": {
-    "collapsed": false,
-    "ExecuteTime": {
-     "end_time": "2024-02-23T01:01:41.532148Z",
-     "start_time": "2024-02-23T01:01:41.528825Z"
-    }
+    "collapsed": false
+   },
+   "id": "201db70188d3e778"
+  },
+  {
+   "cell_type": "markdown",
+   "source": [],
+   "metadata": {
+    "collapsed": false
    },
-   "id": "9c830283e9b26466",
-   "execution_count": 5
+   "id": "8d65fec230193b72"
   }
  ],
  "metadata": {
-- 
cgit v1.2.3


From 717bd5c3abbc775694a3afa582edacdd8482cdea Mon Sep 17 00:00:00 2001
From: Anshul Gupta <ansg191@anshulg.com>
Date: Thu, 22 Feb 2024 17:13:01 -0800
Subject: More Formattings

---
 CS105MiniProject.ipynb | 140 ++++++++++++++++++++++++++++++++++++++++---------
 1 file changed, 114 insertions(+), 26 deletions(-)

(limited to 'CS105MiniProject.ipynb')

diff --git a/CS105MiniProject.ipynb b/CS105MiniProject.ipynb
index c783024..2f86c48 100644
--- a/CS105MiniProject.ipynb
+++ b/CS105MiniProject.ipynb
@@ -5,6 +5,7 @@
    "source": [
     "<div>\n",
     "    <h1><center>CS105 Mini-Project</center></h1>\n",
+    "    <h2><center>Does who a student is living with effect if and how they work jobs?</center></h2>\n",
     "    <p>By: <b>NAMES HERE</b></p>\n",
     "</div>"
    ],
@@ -25,7 +26,17 @@
   },
   {
    "cell_type": "code",
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "              Timestamp What is your current class standing?  \\\n0     2/9/2024 20:12:14                               Senior   \n1     2/9/2024 20:16:34                               Junior   \n2     2/9/2024 20:18:55                               Junior   \n3     2/9/2024 20:24:00                               Senior   \n4     2/9/2024 20:26:16                             Graduate   \n..                  ...                                  ...   \n255  2/14/2024 19:46:28                               Junior   \n256   2/15/2024 0:28:38                                  NaN   \n257   2/15/2024 8:33:45                               Senior   \n258  2/15/2024 16:10:40                            Sophomore   \n259  2/15/2024 16:14:11                            Sophomore   \n\n    Who do you live with?   \\\n0                  Neither   \n1                     Both   \n2                  Friends   \n3                  Neither   \n4                  Neither   \n..                     ...   \n255                Friends   \n256                 Family   \n257                 Family   \n258                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n4                                            Apartment        \n..                                                 ...        \n255                                              House        \n256                                          Apartment        \n257                                              House        \n258                                          Apartment        \n259                                               Dorm        \n\n    How many people live in your household? Do you currently work?  \\\n0                                         6                    Yes   \n1                                         4                     No   \n2                                         4                     No   \n3                                         1                     No   \n4                                         1                    Yes   \n..                                      ...                    ...   \n255                                       5                    Yes   \n256             North District 4 bed 2 bath                     No   \n257                                       9                     No   \n258                                       4                    Yes   \n259      3 (room), 8 (hall), ~70 (building)                     No   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n1                                               NaN   \n2                                               NaN   \n3                                               NaN   \n4                                           10 - 20   \n..                                              ...   \n255                                         10 - 20   \n256                                             NaN   \n257                                           1 - 5   \n258                                          5 - 10   \n259                                             NaN   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n1                             NaN   \n2                             NaN   \n3                             NaN   \n4                      Off-campus   \n..                            ...   \n255                     On-campus   \n256                           NaN   \n257                    Off-campus   \n258                     On-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n1                                                  NaN   \n2                                                  NaN   \n3                                                   No   \n4                                                  Yes   \n..                                                 ...   \n255                                                 No   \n256                                                NaN   \n257                                                 No   \n258                                                 No   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n4                                                   No  \n..                                                 ...  \n255                                                 No  \n256                                                 No  \n257                                                 No  \n258                                                 No  \n259                                                Yes  \n\n[260 rows x 10 columns]",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2/9/2024 20:12:14</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2/9/2024 20:16:34</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2/9/2024 20:18:55</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2/9/2024 20:24:00</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2/9/2024 20:26:16</td>\n      <td>Graduate</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>2/14/2024 19:46:28</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>2/15/2024 0:28:38</td>\n      <td>NaN</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>North District 4 bed 2 bath</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>2/15/2024 8:33:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>1 - 5</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>2/15/2024 16:10:40</td>\n      <td>Sophomore</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>2/15/2024 16:14:11</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3 (room), 8 (hall), ~70 (building)</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>260 rows × 10 columns</p>\n</div>"
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "%matplotlib inline\n",
     "import pandas as pd\n",
@@ -39,9 +50,14 @@
     "df"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-02-23T01:12:49.045312Z",
+     "start_time": "2024-02-23T01:12:48.152070Z"
+    }
    },
-   "id": "3bea6ea662d6c063"
+   "id": "3bea6ea662d6c063",
+   "execution_count": 1
   },
   {
    "cell_type": "markdown",
@@ -55,7 +71,17 @@
   },
   {
    "cell_type": "code",
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "              Timestamp What is your current class standing?  \\\n0     2/9/2024 20:12:14                               Senior   \n1     2/9/2024 20:16:34                               Junior   \n2     2/9/2024 20:18:55                               Junior   \n3     2/9/2024 20:24:00                               Senior   \n4     2/9/2024 20:26:16                             Graduate   \n..                  ...                                  ...   \n255  2/14/2024 19:46:28                               Junior   \n256   2/15/2024 0:28:38                                  NaN   \n257   2/15/2024 8:33:45                               Senior   \n258  2/15/2024 16:10:40                            Sophomore   \n259  2/15/2024 16:14:11                            Sophomore   \n\n    Who do you live with?   \\\n0                  Neither   \n1                     Both   \n2                  Friends   \n3                  Neither   \n4                  Neither   \n..                     ...   \n255                Friends   \n256                 Family   \n257                 Family   \n258                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n4                                            Apartment        \n..                                                 ...        \n255                                              House        \n256                                          Apartment        \n257                                              House        \n258                                          Apartment        \n259                                               Dorm        \n\n     How many people live in your household? Do you currently work?  \\\n0                                          6                    Yes   \n1                                          4                     No   \n2                                          4                     No   \n3                                          1                     No   \n4                                          1                    Yes   \n..                                       ...                    ...   \n255                                        5                    Yes   \n256                                        4                     No   \n257                                        9                     No   \n258                                        4                    Yes   \n259                                        3                     No   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n1                                                 0   \n2                                                 0   \n3                                                 0   \n4                                           10 - 20   \n..                                              ...   \n255                                         10 - 20   \n256                                               0   \n257                                               0   \n258                                          5 - 10   \n259                                               0   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n1                             NaN   \n2                             NaN   \n3                             NaN   \n4                      Off-campus   \n..                            ...   \n255                     On-campus   \n256                           NaN   \n257                    Off-campus   \n258                     On-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n1                                                  NaN   \n2                                                  NaN   \n3                                                  NaN   \n4                                                  Yes   \n..                                                 ...   \n255                                                 No   \n256                                                NaN   \n257                                                NaN   \n258                                                 No   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n4                                                   No  \n..                                                 ...  \n255                                                 No  \n256                                                 No  \n257                                                 No  \n258                                                 No  \n259                                                Yes  \n\n[260 rows x 10 columns]",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2/9/2024 20:12:14</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2/9/2024 20:16:34</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2/9/2024 20:18:55</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2/9/2024 20:24:00</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2/9/2024 20:26:16</td>\n      <td>Graduate</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>2/14/2024 19:46:28</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>2/15/2024 0:28:38</td>\n      <td>NaN</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>2/15/2024 8:33:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>0</td>\n      <td>Off-campus</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>2/15/2024 16:10:40</td>\n      <td>Sophomore</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>2/15/2024 16:14:11</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>260 rows × 10 columns</p>\n</div>"
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Fixes empty values\n",
     "df['Do you currently work?'] = df['Do you currently work?'].fillna('No')\n",
@@ -79,13 +105,28 @@
     "df"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-02-23T01:12:49.066644Z",
+     "start_time": "2024-02-23T01:12:49.047827Z"
+    }
    },
-   "id": "f71f8085d5f66b0"
+   "id": "f71f8085d5f66b0",
+   "execution_count": 2
   },
   {
    "cell_type": "code",
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "              Timestamp What is your current class standing?  \\\n0     2/9/2024 20:12:14                               Senior   \n4     2/9/2024 20:26:16                             Graduate   \n8     2/9/2024 22:02:49                               Junior   \n9     2/9/2024 22:08:43                               Senior   \n13    2/9/2024 22:15:13                               Junior   \n..                  ...                                  ...   \n246  2/13/2024 19:37:02                             Graduate   \n247  2/13/2024 21:39:14                               Senior   \n252   2/14/2024 9:48:12                               Junior   \n255  2/14/2024 19:46:28                               Junior   \n258  2/15/2024 16:10:40                            Sophomore   \n\n    Who do you live with?   \\\n0                  Neither   \n4                  Neither   \n8                  Friends   \n9                   Family   \n13                  Family   \n..                     ...   \n246                 Family   \n247                Friends   \n252                 Family   \n255                Friends   \n258                 Family   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n4                                            Apartment        \n8                                                House        \n9                                                House        \n13                                           Apartment        \n..                                                 ...        \n246                                              House        \n247                                          Apartment        \n252                                              House        \n255                                              House        \n258                                          Apartment        \n\n     How many people live in your household? Do you currently work?  \\\n0                                          6                    Yes   \n4                                          1                    Yes   \n8                                          6                    Yes   \n9                                          5                    Yes   \n13                                         4                    Yes   \n..                                       ...                    ...   \n246                                        2                    Yes   \n247                                        3                    Yes   \n252                                        5                    Yes   \n255                                        5                    Yes   \n258                                        4                    Yes   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n4                                           10 - 20   \n8                                           10 - 20   \n9                                             1 - 5   \n13                                          10 - 20   \n..                                              ...   \n246                                         10 - 20   \n247                                         20 - 40   \n252                                         20 - 40   \n255                                         10 - 20   \n258                                          5 - 10   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n4                      Off-campus   \n8                       On-campus   \n9                       On-campus   \n13                     Off-campus   \n..                            ...   \n246                     On-campus   \n247                    Off-campus   \n252                    Off-campus   \n255                     On-campus   \n258                     On-campus   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n4                                                  Yes   \n8                                                   No   \n9                                                   No   \n13                                                  No   \n..                                                 ...   \n246                                                Yes   \n247                                                 No   \n252                                                 No   \n255                                                 No   \n258                                                 No   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n4                                                   No  \n8                                                   No  \n9                                                   No  \n13                                                  No  \n..                                                 ...  \n246                                                 No  \n247                                                Yes  \n252                                                 No  \n255                                                 No  \n258                                                 No  \n\n[77 rows x 10 columns]",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2/9/2024 20:12:14</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2/9/2024 20:26:16</td>\n      <td>Graduate</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>2/9/2024 22:02:49</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>2/9/2024 22:08:43</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>1 - 5</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>2/9/2024 22:15:13</td>\n      <td>Junior</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>246</th>\n      <td>2/13/2024 19:37:02</td>\n      <td>Graduate</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>2</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>247</th>\n      <td>2/13/2024 21:39:14</td>\n      <td>Senior</td>\n      <td>Friends</td>\n      <td>Apartment</td>\n      <td>3</td>\n      <td>Yes</td>\n      <td>20 - 40</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>252</th>\n      <td>2/14/2024 9:48:12</td>\n      <td>Junior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>20 - 40</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>2/14/2024 19:46:28</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>2/15/2024 16:10:40</td>\n      <td>Sophomore</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n  </tbody>\n</table>\n<p>77 rows × 10 columns</p>\n</div>"
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Working DataFrame\n",
     "w_df = df[df['Do you currently work?'] == 'Yes']\n",
@@ -94,29 +135,45 @@
     "w_df"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-02-23T01:12:49.084475Z",
+     "start_time": "2024-02-23T01:12:49.068965Z"
+    }
    },
-   "id": "6c1d9ee7948e6b9a"
+   "id": "6c1d9ee7948e6b9a",
+   "execution_count": 3
   },
   {
    "cell_type": "code",
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "              Timestamp What is your current class standing?  \\\n1     2/9/2024 20:16:34                               Junior   \n2     2/9/2024 20:18:55                               Junior   \n3     2/9/2024 20:24:00                               Senior   \n5     2/9/2024 20:45:09                               Junior   \n6     2/9/2024 21:55:59                            Sophomore   \n..                  ...                                  ...   \n253  2/14/2024 13:45:45                               Senior   \n254  2/14/2024 16:26:06                               Junior   \n256   2/15/2024 0:28:38                                  NaN   \n257   2/15/2024 8:33:45                               Senior   \n259  2/15/2024 16:14:11                            Sophomore   \n\n    Who do you live with?   \\\n1                     Both   \n2                  Friends   \n3                  Neither   \n5                     Both   \n6                  Friends   \n..                     ...   \n253                 Family   \n254                 Family   \n256                 Family   \n257                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n5                                            Apartment        \n6                                            Apartment        \n..                                                 ...        \n253                                              House        \n254                                              House        \n256                                          Apartment        \n257                                              House        \n259                                               Dorm        \n\n     How many people live in your household? Do you currently work?  \\\n1                                          4                     No   \n2                                          4                     No   \n3                                          1                     No   \n5                                          4                     No   \n6                                          4                     No   \n..                                       ...                    ...   \n253                                        6                     No   \n254                                        5                     No   \n256                                        4                     No   \n257                                        9                     No   \n259                                        3                     No   \n\n    How many hours do you work per week on average?  \\\n1                                                 0   \n2                                                 0   \n3                                                 0   \n5                                                 0   \n6                                                 0   \n..                                              ...   \n253                                               0   \n254                                               0   \n256                                               0   \n257                                               0   \n259                                               0   \n\n    Do you work on or off campus?  \\\n1                             NaN   \n2                             NaN   \n3                             NaN   \n5                             NaN   \n6                             NaN   \n..                            ...   \n253                           NaN   \n254                           NaN   \n256                           NaN   \n257                    Off-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n1                                                  NaN   \n2                                                  NaN   \n3                                                  NaN   \n5                                                  NaN   \n6                                                  NaN   \n..                                                 ...   \n253                                                NaN   \n254                                                NaN   \n256                                                NaN   \n257                                                NaN   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n5                                                   No  \n6                                                   No  \n..                                                 ...  \n253                                                 No  \n254                                                Yes  \n256                                                 No  \n257                                                 No  \n259                                                Yes  \n\n[183 rows x 10 columns]",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>2/9/2024 20:16:34</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2/9/2024 20:18:55</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2/9/2024 20:24:00</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2/9/2024 20:45:09</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2/9/2024 21:55:59</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>253</th>\n      <td>2/14/2024 13:45:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>6</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>254</th>\n      <td>2/14/2024 16:26:06</td>\n      <td>Junior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>2/15/2024 0:28:38</td>\n      <td>NaN</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>2/15/2024 8:33:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>0</td>\n      <td>Off-campus</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>2/15/2024 16:14:11</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>183 rows × 10 columns</p>\n</div>"
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "nw_df"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-02-23T01:12:49.104996Z",
+     "start_time": "2024-02-23T01:12:49.089572Z"
+    }
    },
-   "id": "34f69a756f513fb7"
+   "id": "34f69a756f513fb7",
+   "execution_count": 4
   },
   {
    "cell_type": "markdown",
    "source": [
-    "<div>\n",
-    "    <h1>CS105 Project</h2>\n",
-    "    <p>Ali Naqvi, ...</p>\n",
-    "    <p>Topic: Does who a student is living with effect if and how they work jobs?</p>\n",
-    "</div>\n"
+    "# Analysis"
    ],
    "metadata": {
     "collapsed": false
@@ -127,10 +184,31 @@
    "cell_type": "code",
    "outputs": [],
    "source": [
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "# Assuming 'df' is your DataFrame\n",
-    "\n",
+    "import matplotlib.pyplot as plt"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-02-23T01:12:49.110581Z",
+     "start_time": "2024-02-23T01:12:49.107274Z"
+    }
+   },
+   "id": "39571411a9ea92e0",
+   "execution_count": 5
+  },
+  {
+   "cell_type": "code",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "<Figure size 800x800 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
     "# Count the number of people who work and don't work\n",
     "work_counts = df['Do you currently work?'].value_counts()\n",
     "\n",
@@ -138,21 +216,31 @@
     "plt.figure(figsize=(8, 8))\n",
     "plt.pie(work_counts, labels=work_counts.index, autopct='%1.1f%%', startangle=90, colors=['lightblue', 'lightcoral'])\n",
     "plt.title('Distribution of People Who Work and Don\\'t Work')\n",
-    "plt.show()\n"
+    "plt.show()"
    ],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-02-23T01:12:49.355506Z",
+     "start_time": "2024-02-23T01:12:49.112753Z"
+    }
    },
-   "id": "da1811cc63b41845"
+   "id": "da1811cc63b41845",
+   "execution_count": 6
   },
   {
    "cell_type": "code",
    "outputs": [],
    "source": [],
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-02-23T01:12:49.360434Z",
+     "start_time": "2024-02-23T01:12:49.357193Z"
+    }
    },
-   "id": "201db70188d3e778"
+   "id": "201db70188d3e778",
+   "execution_count": 6
   },
   {
    "cell_type": "markdown",
-- 
cgit v1.2.3


From fb04ae7d101386baca5987e2f39beb5212aacc17 Mon Sep 17 00:00:00 2001
From: ENathanLe <Nath.wessix@gmail.com>
Date: Thu, 22 Feb 2024 18:04:31 -0800
Subject: Add bar graph and heatmap

---
 CS105MiniProject.ipynb | 131 ++++++++++++++++++++++++++++++-------------------
 1 file changed, 81 insertions(+), 50 deletions(-)

(limited to 'CS105MiniProject.ipynb')

diff --git a/CS105MiniProject.ipynb b/CS105MiniProject.ipynb
index 2f86c48..1859cb7 100644
--- a/CS105MiniProject.ipynb
+++ b/CS105MiniProject.ipynb
@@ -29,10 +29,10 @@
    "outputs": [
     {
      "data": {
-      "text/plain": "              Timestamp What is your current class standing?  \\\n0     2/9/2024 20:12:14                               Senior   \n1     2/9/2024 20:16:34                               Junior   \n2     2/9/2024 20:18:55                               Junior   \n3     2/9/2024 20:24:00                               Senior   \n4     2/9/2024 20:26:16                             Graduate   \n..                  ...                                  ...   \n255  2/14/2024 19:46:28                               Junior   \n256   2/15/2024 0:28:38                                  NaN   \n257   2/15/2024 8:33:45                               Senior   \n258  2/15/2024 16:10:40                            Sophomore   \n259  2/15/2024 16:14:11                            Sophomore   \n\n    Who do you live with?   \\\n0                  Neither   \n1                     Both   \n2                  Friends   \n3                  Neither   \n4                  Neither   \n..                     ...   \n255                Friends   \n256                 Family   \n257                 Family   \n258                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n4                                            Apartment        \n..                                                 ...        \n255                                              House        \n256                                          Apartment        \n257                                              House        \n258                                          Apartment        \n259                                               Dorm        \n\n    How many people live in your household? Do you currently work?  \\\n0                                         6                    Yes   \n1                                         4                     No   \n2                                         4                     No   \n3                                         1                     No   \n4                                         1                    Yes   \n..                                      ...                    ...   \n255                                       5                    Yes   \n256             North District 4 bed 2 bath                     No   \n257                                       9                     No   \n258                                       4                    Yes   \n259      3 (room), 8 (hall), ~70 (building)                     No   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n1                                               NaN   \n2                                               NaN   \n3                                               NaN   \n4                                           10 - 20   \n..                                              ...   \n255                                         10 - 20   \n256                                             NaN   \n257                                           1 - 5   \n258                                          5 - 10   \n259                                             NaN   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n1                             NaN   \n2                             NaN   \n3                             NaN   \n4                      Off-campus   \n..                            ...   \n255                     On-campus   \n256                           NaN   \n257                    Off-campus   \n258                     On-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n1                                                  NaN   \n2                                                  NaN   \n3                                                   No   \n4                                                  Yes   \n..                                                 ...   \n255                                                 No   \n256                                                NaN   \n257                                                 No   \n258                                                 No   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n4                                                   No  \n..                                                 ...  \n255                                                 No  \n256                                                 No  \n257                                                 No  \n258                                                 No  \n259                                                Yes  \n\n[260 rows x 10 columns]",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2/9/2024 20:12:14</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2/9/2024 20:16:34</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2/9/2024 20:18:55</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2/9/2024 20:24:00</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2/9/2024 20:26:16</td>\n      <td>Graduate</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>2/14/2024 19:46:28</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>2/15/2024 0:28:38</td>\n      <td>NaN</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>North District 4 bed 2 bath</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>2/15/2024 8:33:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>1 - 5</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>2/15/2024 16:10:40</td>\n      <td>Sophomore</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>2/15/2024 16:14:11</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3 (room), 8 (hall), ~70 (building)</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>260 rows × 10 columns</p>\n</div>"
+      "text/plain": "    What is your current class standing?  What is your age?  \\\n0                                 Senior                23+   \n1                                 Junior                 20   \n2                                 Junior                23+   \n3                                 Senior                23+   \n4                               Graduate                 22   \n..                                   ...                ...   \n255                               Junior                 21   \n256                                  NaN                 21   \n257                               Senior                 21   \n258                            Sophomore                 21   \n259                            Sophomore                 18   \n\n    Who do you live with?   \\\n0                  Neither   \n1                     Both   \n2                  Friends   \n3                  Neither   \n4                  Neither   \n..                     ...   \n255                Friends   \n256                 Family   \n257                 Family   \n258                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n4                                            Apartment        \n..                                                 ...        \n255                                              House        \n256                                          Apartment        \n257                                              House        \n258                                          Apartment        \n259                                               Dorm        \n\n    How many people live in your household? Do you currently work?  \\\n0                                         6                    Yes   \n1                                         4                     No   \n2                                         4                     No   \n3                                         1                     No   \n4                                         1                    Yes   \n..                                      ...                    ...   \n255                                       5                    Yes   \n256             North District 4 bed 2 bath                     No   \n257                                       9                     No   \n258                                       4                    Yes   \n259      3 (room), 8 (hall), ~70 (building)                     No   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n1                                               NaN   \n2                                               NaN   \n3                                               NaN   \n4                                           10 - 20   \n..                                              ...   \n255                                         10 - 20   \n256                                             NaN   \n257                                           1 - 5   \n258                                          5 - 10   \n259                                             NaN   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n1                             NaN   \n2                             NaN   \n3                             NaN   \n4                      Off-campus   \n..                            ...   \n255                     On-campus   \n256                           NaN   \n257                    Off-campus   \n258                     On-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n1                                                  NaN   \n2                                                  NaN   \n3                                                   No   \n4                                                  Yes   \n..                                                 ...   \n255                                                 No   \n256                                                NaN   \n257                                                 No   \n258                                                 No   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n4                                                   No  \n..                                                 ...  \n255                                                 No  \n256                                                 No  \n257                                                 No  \n258                                                 No  \n259                                                Yes  \n\n[260 rows x 10 columns]",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>What is your current class standing?</th>\n      <th>What is your age?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Junior</td>\n      <td>20</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Junior</td>\n      <td>23+</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Graduate</td>\n      <td>22</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>Junior</td>\n      <td>21</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>NaN</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>North District 4 bed 2 bath</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>Senior</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>1 - 5</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>Sophomore</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>Sophomore</td>\n      <td>18</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3 (room), 8 (hall), ~70 (building)</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>260 rows × 10 columns</p>\n</div>"
      },
-     "execution_count": 1,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -41,23 +41,26 @@
     "%matplotlib inline\n",
     "import pandas as pd\n",
     "import numpy as np\n",
+    "import seaborn as sns\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt\n",
     "\n",
     "# Load dataframe from data.csv\n",
     "df = pd.read_csv(\"data.csv\")\n",
     "\n",
     "# Select relevant columns\n",
-    "df = df.iloc[:, [0, 2, 7, 8, 9, 58, 59, 60, 61, 26]]\n",
+    "df = df.iloc[:, [2, 3, 7, 8, 9, 58, 59, 60, 61, 26]]\n",
     "df"
    ],
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T01:12:49.045312Z",
-     "start_time": "2024-02-23T01:12:48.152070Z"
+     "end_time": "2024-02-23T02:00:29.244799Z",
+     "start_time": "2024-02-23T02:00:28.800749Z"
     }
    },
    "id": "3bea6ea662d6c063",
-   "execution_count": 1
+   "execution_count": 7
   },
   {
    "cell_type": "markdown",
@@ -74,10 +77,10 @@
    "outputs": [
     {
      "data": {
-      "text/plain": "              Timestamp What is your current class standing?  \\\n0     2/9/2024 20:12:14                               Senior   \n1     2/9/2024 20:16:34                               Junior   \n2     2/9/2024 20:18:55                               Junior   \n3     2/9/2024 20:24:00                               Senior   \n4     2/9/2024 20:26:16                             Graduate   \n..                  ...                                  ...   \n255  2/14/2024 19:46:28                               Junior   \n256   2/15/2024 0:28:38                                  NaN   \n257   2/15/2024 8:33:45                               Senior   \n258  2/15/2024 16:10:40                            Sophomore   \n259  2/15/2024 16:14:11                            Sophomore   \n\n    Who do you live with?   \\\n0                  Neither   \n1                     Both   \n2                  Friends   \n3                  Neither   \n4                  Neither   \n..                     ...   \n255                Friends   \n256                 Family   \n257                 Family   \n258                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n4                                            Apartment        \n..                                                 ...        \n255                                              House        \n256                                          Apartment        \n257                                              House        \n258                                          Apartment        \n259                                               Dorm        \n\n     How many people live in your household? Do you currently work?  \\\n0                                          6                    Yes   \n1                                          4                     No   \n2                                          4                     No   \n3                                          1                     No   \n4                                          1                    Yes   \n..                                       ...                    ...   \n255                                        5                    Yes   \n256                                        4                     No   \n257                                        9                     No   \n258                                        4                    Yes   \n259                                        3                     No   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n1                                                 0   \n2                                                 0   \n3                                                 0   \n4                                           10 - 20   \n..                                              ...   \n255                                         10 - 20   \n256                                               0   \n257                                               0   \n258                                          5 - 10   \n259                                               0   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n1                             NaN   \n2                             NaN   \n3                             NaN   \n4                      Off-campus   \n..                            ...   \n255                     On-campus   \n256                           NaN   \n257                    Off-campus   \n258                     On-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n1                                                  NaN   \n2                                                  NaN   \n3                                                  NaN   \n4                                                  Yes   \n..                                                 ...   \n255                                                 No   \n256                                                NaN   \n257                                                NaN   \n258                                                 No   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n4                                                   No  \n..                                                 ...  \n255                                                 No  \n256                                                 No  \n257                                                 No  \n258                                                 No  \n259                                                Yes  \n\n[260 rows x 10 columns]",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2/9/2024 20:12:14</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2/9/2024 20:16:34</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2/9/2024 20:18:55</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2/9/2024 20:24:00</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2/9/2024 20:26:16</td>\n      <td>Graduate</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>2/14/2024 19:46:28</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>2/15/2024 0:28:38</td>\n      <td>NaN</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>2/15/2024 8:33:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>0</td>\n      <td>Off-campus</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>2/15/2024 16:10:40</td>\n      <td>Sophomore</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>2/15/2024 16:14:11</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>260 rows × 10 columns</p>\n</div>"
+      "text/plain": "    What is your current class standing?  What is your age?  \\\n0                                 Senior                23+   \n1                                 Junior                 20   \n2                                 Junior                23+   \n3                                 Senior                23+   \n4                               Graduate                 22   \n..                                   ...                ...   \n255                               Junior                 21   \n256                                  NaN                 21   \n257                               Senior                 21   \n258                            Sophomore                 21   \n259                            Sophomore                 18   \n\n    Who do you live with?   \\\n0                  Neither   \n1                     Both   \n2                  Friends   \n3                  Neither   \n4                  Neither   \n..                     ...   \n255                Friends   \n256                 Family   \n257                 Family   \n258                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n4                                            Apartment        \n..                                                 ...        \n255                                              House        \n256                                          Apartment        \n257                                              House        \n258                                          Apartment        \n259                                               Dorm        \n\n     How many people live in your household? Do you currently work?  \\\n0                                          6                    Yes   \n1                                          4                     No   \n2                                          4                     No   \n3                                          1                     No   \n4                                          1                    Yes   \n..                                       ...                    ...   \n255                                        5                    Yes   \n256                                        4                     No   \n257                                        9                     No   \n258                                        4                    Yes   \n259                                        3                     No   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n1                                                 0   \n2                                                 0   \n3                                                 0   \n4                                           10 - 20   \n..                                              ...   \n255                                         10 - 20   \n256                                               0   \n257                                               0   \n258                                          5 - 10   \n259                                               0   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n1                             NaN   \n2                             NaN   \n3                             NaN   \n4                      Off-campus   \n..                            ...   \n255                     On-campus   \n256                           NaN   \n257                    Off-campus   \n258                     On-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n1                                                  NaN   \n2                                                  NaN   \n3                                                  NaN   \n4                                                  Yes   \n..                                                 ...   \n255                                                 No   \n256                                                NaN   \n257                                                NaN   \n258                                                 No   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n4                                                   No  \n..                                                 ...  \n255                                                 No  \n256                                                 No  \n257                                                 No  \n258                                                 No  \n259                                                Yes  \n\n[260 rows x 10 columns]",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>What is your current class standing?</th>\n      <th>What is your age?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Junior</td>\n      <td>20</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Junior</td>\n      <td>23+</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Graduate</td>\n      <td>22</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>Junior</td>\n      <td>21</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>NaN</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>Senior</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>0</td>\n      <td>Off-campus</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>Sophomore</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>Sophomore</td>\n      <td>18</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>260 rows × 10 columns</p>\n</div>"
      },
-     "execution_count": 2,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -107,22 +110,22 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T01:12:49.066644Z",
-     "start_time": "2024-02-23T01:12:49.047827Z"
+     "end_time": "2024-02-23T02:00:29.279290Z",
+     "start_time": "2024-02-23T02:00:29.247783Z"
     }
    },
    "id": "f71f8085d5f66b0",
-   "execution_count": 2
+   "execution_count": 8
   },
   {
    "cell_type": "code",
    "outputs": [
     {
      "data": {
-      "text/plain": "              Timestamp What is your current class standing?  \\\n0     2/9/2024 20:12:14                               Senior   \n4     2/9/2024 20:26:16                             Graduate   \n8     2/9/2024 22:02:49                               Junior   \n9     2/9/2024 22:08:43                               Senior   \n13    2/9/2024 22:15:13                               Junior   \n..                  ...                                  ...   \n246  2/13/2024 19:37:02                             Graduate   \n247  2/13/2024 21:39:14                               Senior   \n252   2/14/2024 9:48:12                               Junior   \n255  2/14/2024 19:46:28                               Junior   \n258  2/15/2024 16:10:40                            Sophomore   \n\n    Who do you live with?   \\\n0                  Neither   \n4                  Neither   \n8                  Friends   \n9                   Family   \n13                  Family   \n..                     ...   \n246                 Family   \n247                Friends   \n252                 Family   \n255                Friends   \n258                 Family   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n4                                            Apartment        \n8                                                House        \n9                                                House        \n13                                           Apartment        \n..                                                 ...        \n246                                              House        \n247                                          Apartment        \n252                                              House        \n255                                              House        \n258                                          Apartment        \n\n     How many people live in your household? Do you currently work?  \\\n0                                          6                    Yes   \n4                                          1                    Yes   \n8                                          6                    Yes   \n9                                          5                    Yes   \n13                                         4                    Yes   \n..                                       ...                    ...   \n246                                        2                    Yes   \n247                                        3                    Yes   \n252                                        5                    Yes   \n255                                        5                    Yes   \n258                                        4                    Yes   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n4                                           10 - 20   \n8                                           10 - 20   \n9                                             1 - 5   \n13                                          10 - 20   \n..                                              ...   \n246                                         10 - 20   \n247                                         20 - 40   \n252                                         20 - 40   \n255                                         10 - 20   \n258                                          5 - 10   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n4                      Off-campus   \n8                       On-campus   \n9                       On-campus   \n13                     Off-campus   \n..                            ...   \n246                     On-campus   \n247                    Off-campus   \n252                    Off-campus   \n255                     On-campus   \n258                     On-campus   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n4                                                  Yes   \n8                                                   No   \n9                                                   No   \n13                                                  No   \n..                                                 ...   \n246                                                Yes   \n247                                                 No   \n252                                                 No   \n255                                                 No   \n258                                                 No   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n4                                                   No  \n8                                                   No  \n9                                                   No  \n13                                                  No  \n..                                                 ...  \n246                                                 No  \n247                                                Yes  \n252                                                 No  \n255                                                 No  \n258                                                 No  \n\n[77 rows x 10 columns]",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2/9/2024 20:12:14</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2/9/2024 20:26:16</td>\n      <td>Graduate</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>2/9/2024 22:02:49</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>2/9/2024 22:08:43</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>1 - 5</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>2/9/2024 22:15:13</td>\n      <td>Junior</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>246</th>\n      <td>2/13/2024 19:37:02</td>\n      <td>Graduate</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>2</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>247</th>\n      <td>2/13/2024 21:39:14</td>\n      <td>Senior</td>\n      <td>Friends</td>\n      <td>Apartment</td>\n      <td>3</td>\n      <td>Yes</td>\n      <td>20 - 40</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>252</th>\n      <td>2/14/2024 9:48:12</td>\n      <td>Junior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>20 - 40</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>2/14/2024 19:46:28</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>2/15/2024 16:10:40</td>\n      <td>Sophomore</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n  </tbody>\n</table>\n<p>77 rows × 10 columns</p>\n</div>"
+      "text/plain": "    What is your current class standing?  What is your age?  \\\n0                                 Senior                23+   \n4                               Graduate                 22   \n8                                 Junior                 20   \n9                                 Senior                 22   \n13                                Junior                 21   \n..                                   ...                ...   \n246                             Graduate                23+   \n247                               Senior                 21   \n252                               Junior                 20   \n255                               Junior                 21   \n258                            Sophomore                 21   \n\n    Who do you live with?   \\\n0                  Neither   \n4                  Neither   \n8                  Friends   \n9                   Family   \n13                  Family   \n..                     ...   \n246                 Family   \n247                Friends   \n252                 Family   \n255                Friends   \n258                 Family   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n4                                            Apartment        \n8                                                House        \n9                                                House        \n13                                           Apartment        \n..                                                 ...        \n246                                              House        \n247                                          Apartment        \n252                                              House        \n255                                              House        \n258                                          Apartment        \n\n     How many people live in your household? Do you currently work?  \\\n0                                          6                    Yes   \n4                                          1                    Yes   \n8                                          6                    Yes   \n9                                          5                    Yes   \n13                                         4                    Yes   \n..                                       ...                    ...   \n246                                        2                    Yes   \n247                                        3                    Yes   \n252                                        5                    Yes   \n255                                        5                    Yes   \n258                                        4                    Yes   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n4                                           10 - 20   \n8                                           10 - 20   \n9                                             1 - 5   \n13                                          10 - 20   \n..                                              ...   \n246                                         10 - 20   \n247                                         20 - 40   \n252                                         20 - 40   \n255                                         10 - 20   \n258                                          5 - 10   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n4                      Off-campus   \n8                       On-campus   \n9                       On-campus   \n13                     Off-campus   \n..                            ...   \n246                     On-campus   \n247                    Off-campus   \n252                    Off-campus   \n255                     On-campus   \n258                     On-campus   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n4                                                  Yes   \n8                                                   No   \n9                                                   No   \n13                                                  No   \n..                                                 ...   \n246                                                Yes   \n247                                                 No   \n252                                                 No   \n255                                                 No   \n258                                                 No   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n4                                                   No  \n8                                                   No  \n9                                                   No  \n13                                                  No  \n..                                                 ...  \n246                                                 No  \n247                                                Yes  \n252                                                 No  \n255                                                 No  \n258                                                 No  \n\n[77 rows x 10 columns]",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>What is your current class standing?</th>\n      <th>What is your age?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Graduate</td>\n      <td>22</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>Junior</td>\n      <td>20</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Senior</td>\n      <td>22</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>1 - 5</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>Junior</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>246</th>\n      <td>Graduate</td>\n      <td>23+</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>2</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>247</th>\n      <td>Senior</td>\n      <td>21</td>\n      <td>Friends</td>\n      <td>Apartment</td>\n      <td>3</td>\n      <td>Yes</td>\n      <td>20 - 40</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>252</th>\n      <td>Junior</td>\n      <td>20</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>20 - 40</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>Junior</td>\n      <td>21</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>Sophomore</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n  </tbody>\n</table>\n<p>77 rows × 10 columns</p>\n</div>"
      },
-     "execution_count": 3,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -137,22 +140,22 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T01:12:49.084475Z",
-     "start_time": "2024-02-23T01:12:49.068965Z"
+     "end_time": "2024-02-23T02:00:29.308973Z",
+     "start_time": "2024-02-23T02:00:29.282289Z"
     }
    },
    "id": "6c1d9ee7948e6b9a",
-   "execution_count": 3
+   "execution_count": 9
   },
   {
    "cell_type": "code",
    "outputs": [
     {
      "data": {
-      "text/plain": "              Timestamp What is your current class standing?  \\\n1     2/9/2024 20:16:34                               Junior   \n2     2/9/2024 20:18:55                               Junior   \n3     2/9/2024 20:24:00                               Senior   \n5     2/9/2024 20:45:09                               Junior   \n6     2/9/2024 21:55:59                            Sophomore   \n..                  ...                                  ...   \n253  2/14/2024 13:45:45                               Senior   \n254  2/14/2024 16:26:06                               Junior   \n256   2/15/2024 0:28:38                                  NaN   \n257   2/15/2024 8:33:45                               Senior   \n259  2/15/2024 16:14:11                            Sophomore   \n\n    Who do you live with?   \\\n1                     Both   \n2                  Friends   \n3                  Neither   \n5                     Both   \n6                  Friends   \n..                     ...   \n253                 Family   \n254                 Family   \n256                 Family   \n257                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n5                                            Apartment        \n6                                            Apartment        \n..                                                 ...        \n253                                              House        \n254                                              House        \n256                                          Apartment        \n257                                              House        \n259                                               Dorm        \n\n     How many people live in your household? Do you currently work?  \\\n1                                          4                     No   \n2                                          4                     No   \n3                                          1                     No   \n5                                          4                     No   \n6                                          4                     No   \n..                                       ...                    ...   \n253                                        6                     No   \n254                                        5                     No   \n256                                        4                     No   \n257                                        9                     No   \n259                                        3                     No   \n\n    How many hours do you work per week on average?  \\\n1                                                 0   \n2                                                 0   \n3                                                 0   \n5                                                 0   \n6                                                 0   \n..                                              ...   \n253                                               0   \n254                                               0   \n256                                               0   \n257                                               0   \n259                                               0   \n\n    Do you work on or off campus?  \\\n1                             NaN   \n2                             NaN   \n3                             NaN   \n5                             NaN   \n6                             NaN   \n..                            ...   \n253                           NaN   \n254                           NaN   \n256                           NaN   \n257                    Off-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n1                                                  NaN   \n2                                                  NaN   \n3                                                  NaN   \n5                                                  NaN   \n6                                                  NaN   \n..                                                 ...   \n253                                                NaN   \n254                                                NaN   \n256                                                NaN   \n257                                                NaN   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n5                                                   No  \n6                                                   No  \n..                                                 ...  \n253                                                 No  \n254                                                Yes  \n256                                                 No  \n257                                                 No  \n259                                                Yes  \n\n[183 rows x 10 columns]",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Timestamp</th>\n      <th>What is your current class standing?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>2/9/2024 20:16:34</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2/9/2024 20:18:55</td>\n      <td>Junior</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2/9/2024 20:24:00</td>\n      <td>Senior</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2/9/2024 20:45:09</td>\n      <td>Junior</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2/9/2024 21:55:59</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>253</th>\n      <td>2/14/2024 13:45:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>6</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>254</th>\n      <td>2/14/2024 16:26:06</td>\n      <td>Junior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>2/15/2024 0:28:38</td>\n      <td>NaN</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>2/15/2024 8:33:45</td>\n      <td>Senior</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>0</td>\n      <td>Off-campus</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>2/15/2024 16:14:11</td>\n      <td>Sophomore</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>183 rows × 10 columns</p>\n</div>"
+      "text/plain": "    What is your current class standing?  What is your age?  \\\n1                                 Junior                 20   \n2                                 Junior                23+   \n3                                 Senior                23+   \n5                                 Junior                 21   \n6                              Sophomore                 19   \n..                                   ...                ...   \n253                               Senior                 21   \n254                               Junior                 19   \n256                                  NaN                 21   \n257                               Senior                 21   \n259                            Sophomore                 18   \n\n    Who do you live with?   \\\n1                     Both   \n2                  Friends   \n3                  Neither   \n5                     Both   \n6                  Friends   \n..                     ...   \n253                 Family   \n254                 Family   \n256                 Family   \n257                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n5                                            Apartment        \n6                                            Apartment        \n..                                                 ...        \n253                                              House        \n254                                              House        \n256                                          Apartment        \n257                                              House        \n259                                               Dorm        \n\n     How many people live in your household? Do you currently work?  \\\n1                                          4                     No   \n2                                          4                     No   \n3                                          1                     No   \n5                                          4                     No   \n6                                          4                     No   \n..                                       ...                    ...   \n253                                        6                     No   \n254                                        5                     No   \n256                                        4                     No   \n257                                        9                     No   \n259                                        3                     No   \n\n    How many hours do you work per week on average?  \\\n1                                                 0   \n2                                                 0   \n3                                                 0   \n5                                                 0   \n6                                                 0   \n..                                              ...   \n253                                               0   \n254                                               0   \n256                                               0   \n257                                               0   \n259                                               0   \n\n    Do you work on or off campus?  \\\n1                             NaN   \n2                             NaN   \n3                             NaN   \n5                             NaN   \n6                             NaN   \n..                            ...   \n253                           NaN   \n254                           NaN   \n256                           NaN   \n257                    Off-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n1                                                  NaN   \n2                                                  NaN   \n3                                                  NaN   \n5                                                  NaN   \n6                                                  NaN   \n..                                                 ...   \n253                                                NaN   \n254                                                NaN   \n256                                                NaN   \n257                                                NaN   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n5                                                   No  \n6                                                   No  \n..                                                 ...  \n253                                                 No  \n254                                                Yes  \n256                                                 No  \n257                                                 No  \n259                                                Yes  \n\n[183 rows x 10 columns]",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>What is your current class standing?</th>\n      <th>What is your age?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>Junior</td>\n      <td>20</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Junior</td>\n      <td>23+</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Junior</td>\n      <td>21</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Sophomore</td>\n      <td>19</td>\n      <td>Friends</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>253</th>\n      <td>Senior</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>6</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>254</th>\n      <td>Junior</td>\n      <td>19</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>NaN</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>Senior</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>0</td>\n      <td>Off-campus</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>Sophomore</td>\n      <td>18</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>183 rows × 10 columns</p>\n</div>"
      },
-     "execution_count": 4,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -163,12 +166,12 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T01:12:49.104996Z",
-     "start_time": "2024-02-23T01:12:49.089572Z"
+     "end_time": "2024-02-23T02:00:29.333356Z",
+     "start_time": "2024-02-23T02:00:29.313068Z"
     }
    },
    "id": "34f69a756f513fb7",
-   "execution_count": 4
+   "execution_count": 10
   },
   {
    "cell_type": "markdown",
@@ -180,29 +183,13 @@
    },
    "id": "d5c1424ddd30ca97"
   },
-  {
-   "cell_type": "code",
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "ExecuteTime": {
-     "end_time": "2024-02-23T01:12:49.110581Z",
-     "start_time": "2024-02-23T01:12:49.107274Z"
-    }
-   },
-   "id": "39571411a9ea92e0",
-   "execution_count": 5
-  },
   {
    "cell_type": "code",
    "outputs": [
     {
      "data": {
       "text/plain": "<Figure size 800x800 with 1 Axes>",
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
@@ -221,26 +208,44 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T01:12:49.355506Z",
-     "start_time": "2024-02-23T01:12:49.112753Z"
+     "end_time": "2024-02-23T02:00:29.477781Z",
+     "start_time": "2024-02-23T02:00:29.336352Z"
     }
    },
    "id": "da1811cc63b41845",
-   "execution_count": 6
+   "execution_count": 11
   },
   {
    "cell_type": "code",
-   "outputs": [],
-   "source": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "<Figure size 800x800 with 2 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.subplots(figsize=(8, 8))\n",
+    "df_2dhist = pd.DataFrame({\n",
+    "    x_label: grp['Do you currently work?'].value_counts()\n",
+    "    for x_label, grp in df.groupby('Do you currently live in a house, apartnment, or dorm? ')\n",
+    "})\n",
+    "sns.heatmap(df_2dhist, cmap='viridis')\n",
+    "plt.xlabel('Do you currently live in a house, apartnment, or dorm? ')\n",
+    "_ = plt.ylabel('Do you currently work?')"
+   ],
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T01:12:49.360434Z",
-     "start_time": "2024-02-23T01:12:49.357193Z"
+     "end_time": "2024-02-23T02:00:29.790484Z",
+     "start_time": "2024-02-23T02:00:29.479779Z"
     }
    },
    "id": "201db70188d3e778",
-   "execution_count": 6
+   "execution_count": 12
   },
   {
    "cell_type": "markdown",
@@ -249,6 +254,32 @@
     "collapsed": false
    },
    "id": "8d65fec230193b72"
+  },
+  {
+   "cell_type": "code",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df.groupby('Do you currently live in a house, apartnment, or dorm? ').size().plot(kind='barh', color=sns.palettes.mpl_palette('Dark2'))\n",
+    "plt.gca().spines[['top', 'right',]].set_visible(False)"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "ExecuteTime": {
+     "end_time": "2024-02-23T02:00:30.015262Z",
+     "start_time": "2024-02-23T02:00:29.792483Z"
+    }
+   },
+   "id": "5e460707e32c4a2a",
+   "execution_count": 13
   }
  ],
  "metadata": {
-- 
cgit v1.2.3


From f1ab15f183091097e8966cff67ae9ce22d22e2c4 Mon Sep 17 00:00:00 2001
From: Anshul Gupta <ansg191@anshulg.com>
Date: Thu, 22 Feb 2024 18:11:58 -0800
Subject: Resets execution & timestamps

---
 CS105MiniProject.ipynb | 56 +++++++++++++++++++++++++-------------------------
 1 file changed, 28 insertions(+), 28 deletions(-)

(limited to 'CS105MiniProject.ipynb')

diff --git a/CS105MiniProject.ipynb b/CS105MiniProject.ipynb
index 1859cb7..818356f 100644
--- a/CS105MiniProject.ipynb
+++ b/CS105MiniProject.ipynb
@@ -32,7 +32,7 @@
       "text/plain": "    What is your current class standing?  What is your age?  \\\n0                                 Senior                23+   \n1                                 Junior                 20   \n2                                 Junior                23+   \n3                                 Senior                23+   \n4                               Graduate                 22   \n..                                   ...                ...   \n255                               Junior                 21   \n256                                  NaN                 21   \n257                               Senior                 21   \n258                            Sophomore                 21   \n259                            Sophomore                 18   \n\n    Who do you live with?   \\\n0                  Neither   \n1                     Both   \n2                  Friends   \n3                  Neither   \n4                  Neither   \n..                     ...   \n255                Friends   \n256                 Family   \n257                 Family   \n258                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n4                                            Apartment        \n..                                                 ...        \n255                                              House        \n256                                          Apartment        \n257                                              House        \n258                                          Apartment        \n259                                               Dorm        \n\n    How many people live in your household? Do you currently work?  \\\n0                                         6                    Yes   \n1                                         4                     No   \n2                                         4                     No   \n3                                         1                     No   \n4                                         1                    Yes   \n..                                      ...                    ...   \n255                                       5                    Yes   \n256             North District 4 bed 2 bath                     No   \n257                                       9                     No   \n258                                       4                    Yes   \n259      3 (room), 8 (hall), ~70 (building)                     No   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n1                                               NaN   \n2                                               NaN   \n3                                               NaN   \n4                                           10 - 20   \n..                                              ...   \n255                                         10 - 20   \n256                                             NaN   \n257                                           1 - 5   \n258                                          5 - 10   \n259                                             NaN   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n1                             NaN   \n2                             NaN   \n3                             NaN   \n4                      Off-campus   \n..                            ...   \n255                     On-campus   \n256                           NaN   \n257                    Off-campus   \n258                     On-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n1                                                  NaN   \n2                                                  NaN   \n3                                                   No   \n4                                                  Yes   \n..                                                 ...   \n255                                                 No   \n256                                                NaN   \n257                                                 No   \n258                                                 No   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n4                                                   No  \n..                                                 ...  \n255                                                 No  \n256                                                 No  \n257                                                 No  \n258                                                 No  \n259                                                Yes  \n\n[260 rows x 10 columns]",
       "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>What is your current class standing?</th>\n      <th>What is your age?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Junior</td>\n      <td>20</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Junior</td>\n      <td>23+</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Graduate</td>\n      <td>22</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>Junior</td>\n      <td>21</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>NaN</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>North District 4 bed 2 bath</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>Senior</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>1 - 5</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>Sophomore</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>Sophomore</td>\n      <td>18</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3 (room), 8 (hall), ~70 (building)</td>\n      <td>No</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>260 rows × 10 columns</p>\n</div>"
      },
-     "execution_count": 7,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -55,12 +55,12 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:00:29.244799Z",
-     "start_time": "2024-02-23T02:00:28.800749Z"
+     "end_time": "2024-02-23T02:10:58.731970Z",
+     "start_time": "2024-02-23T02:10:58.699969Z"
     }
    },
    "id": "3bea6ea662d6c063",
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+   "execution_count": 1
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   {
    "cell_type": "markdown",
@@ -80,7 +80,7 @@
       "text/plain": "    What is your current class standing?  What is your age?  \\\n0                                 Senior                23+   \n1                                 Junior                 20   \n2                                 Junior                23+   \n3                                 Senior                23+   \n4                               Graduate                 22   \n..                                   ...                ...   \n255                               Junior                 21   \n256                                  NaN                 21   \n257                               Senior                 21   \n258                            Sophomore                 21   \n259                            Sophomore                 18   \n\n    Who do you live with?   \\\n0                  Neither   \n1                     Both   \n2                  Friends   \n3                  Neither   \n4                  Neither   \n..                     ...   \n255                Friends   \n256                 Family   \n257                 Family   \n258                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n4                                            Apartment        \n..                                                 ...        \n255                                              House        \n256                                          Apartment        \n257                                              House        \n258                                          Apartment        \n259                                               Dorm        \n\n     How many people live in your household? Do you currently work?  \\\n0                                          6                    Yes   \n1                                          4                     No   \n2                                          4                     No   \n3                                          1                     No   \n4                                          1                    Yes   \n..                                       ...                    ...   \n255                                        5                    Yes   \n256                                        4                     No   \n257                                        9                     No   \n258                                        4                    Yes   \n259                                        3                     No   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n1                                                 0   \n2                                                 0   \n3                                                 0   \n4                                           10 - 20   \n..                                              ...   \n255                                         10 - 20   \n256                                               0   \n257                                               0   \n258                                          5 - 10   \n259                                               0   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n1                             NaN   \n2                             NaN   \n3                             NaN   \n4                      Off-campus   \n..                            ...   \n255                     On-campus   \n256                           NaN   \n257                    Off-campus   \n258                     On-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n1                                                  NaN   \n2                                                  NaN   \n3                                                  NaN   \n4                                                  Yes   \n..                                                 ...   \n255                                                 No   \n256                                                NaN   \n257                                                NaN   \n258                                                 No   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n4                                                   No  \n..                                                 ...  \n255                                                 No  \n256                                                 No  \n257                                                 No  \n258                                                 No  \n259                                                Yes  \n\n[260 rows x 10 columns]",
       "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>What is your current class standing?</th>\n      <th>What is your age?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Junior</td>\n      <td>20</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Junior</td>\n      <td>23+</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Graduate</td>\n      <td>22</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>Junior</td>\n      <td>21</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>NaN</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>Senior</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>0</td>\n      <td>Off-campus</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>Sophomore</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>Sophomore</td>\n      <td>18</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>260 rows × 10 columns</p>\n</div>"
      },
-     "execution_count": 8,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -110,12 +110,12 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:00:29.279290Z",
-     "start_time": "2024-02-23T02:00:29.247783Z"
+     "end_time": "2024-02-23T02:10:58.744774Z",
+     "start_time": "2024-02-23T02:10:58.732815Z"
     }
    },
    "id": "f71f8085d5f66b0",
-   "execution_count": 8
+   "execution_count": 2
   },
   {
    "cell_type": "code",
@@ -125,7 +125,7 @@
       "text/plain": "    What is your current class standing?  What is your age?  \\\n0                                 Senior                23+   \n4                               Graduate                 22   \n8                                 Junior                 20   \n9                                 Senior                 22   \n13                                Junior                 21   \n..                                   ...                ...   \n246                             Graduate                23+   \n247                               Senior                 21   \n252                               Junior                 20   \n255                               Junior                 21   \n258                            Sophomore                 21   \n\n    Who do you live with?   \\\n0                  Neither   \n4                  Neither   \n8                  Friends   \n9                   Family   \n13                  Family   \n..                     ...   \n246                 Family   \n247                Friends   \n252                 Family   \n255                Friends   \n258                 Family   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n0                                                House        \n4                                            Apartment        \n8                                                House        \n9                                                House        \n13                                           Apartment        \n..                                                 ...        \n246                                              House        \n247                                          Apartment        \n252                                              House        \n255                                              House        \n258                                          Apartment        \n\n     How many people live in your household? Do you currently work?  \\\n0                                          6                    Yes   \n4                                          1                    Yes   \n8                                          6                    Yes   \n9                                          5                    Yes   \n13                                         4                    Yes   \n..                                       ...                    ...   \n246                                        2                    Yes   \n247                                        3                    Yes   \n252                                        5                    Yes   \n255                                        5                    Yes   \n258                                        4                    Yes   \n\n    How many hours do you work per week on average?  \\\n0                                            5 - 10   \n4                                           10 - 20   \n8                                           10 - 20   \n9                                             1 - 5   \n13                                          10 - 20   \n..                                              ...   \n246                                         10 - 20   \n247                                         20 - 40   \n252                                         20 - 40   \n255                                         10 - 20   \n258                                          5 - 10   \n\n    Do you work on or off campus?  \\\n0                      Off-campus   \n4                      Off-campus   \n8                       On-campus   \n9                       On-campus   \n13                     Off-campus   \n..                            ...   \n246                     On-campus   \n247                    Off-campus   \n252                    Off-campus   \n255                     On-campus   \n258                     On-campus   \n\n    Do you work in a department related to your major?  \\\n0                                                   No   \n4                                                  Yes   \n8                                                   No   \n9                                                   No   \n13                                                  No   \n..                                                 ...   \n246                                                Yes   \n247                                                 No   \n252                                                 No   \n255                                                 No   \n258                                                 No   \n\n    Do you have roommates that are part of your major?  \n0                                                   No  \n4                                                   No  \n8                                                   No  \n9                                                   No  \n13                                                  No  \n..                                                 ...  \n246                                                 No  \n247                                                Yes  \n252                                                 No  \n255                                                 No  \n258                                                 No  \n\n[77 rows x 10 columns]",
       "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>What is your current class standing?</th>\n      <th>What is your age?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Graduate</td>\n      <td>22</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>Junior</td>\n      <td>20</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>6</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Senior</td>\n      <td>22</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>1 - 5</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>Junior</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>246</th>\n      <td>Graduate</td>\n      <td>23+</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>2</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>Yes</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>247</th>\n      <td>Senior</td>\n      <td>21</td>\n      <td>Friends</td>\n      <td>Apartment</td>\n      <td>3</td>\n      <td>Yes</td>\n      <td>20 - 40</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>252</th>\n      <td>Junior</td>\n      <td>20</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>20 - 40</td>\n      <td>Off-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>255</th>\n      <td>Junior</td>\n      <td>21</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>5</td>\n      <td>Yes</td>\n      <td>10 - 20</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>258</th>\n      <td>Sophomore</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>Yes</td>\n      <td>5 - 10</td>\n      <td>On-campus</td>\n      <td>No</td>\n      <td>No</td>\n    </tr>\n  </tbody>\n</table>\n<p>77 rows × 10 columns</p>\n</div>"
      },
-     "execution_count": 9,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -140,12 +140,12 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:00:29.308973Z",
-     "start_time": "2024-02-23T02:00:29.282289Z"
+     "end_time": "2024-02-23T02:10:58.754973Z",
+     "start_time": "2024-02-23T02:10:58.746452Z"
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    "id": "6c1d9ee7948e6b9a",
-   "execution_count": 9
+   "execution_count": 3
   },
   {
    "cell_type": "code",
@@ -155,7 +155,7 @@
       "text/plain": "    What is your current class standing?  What is your age?  \\\n1                                 Junior                 20   \n2                                 Junior                23+   \n3                                 Senior                23+   \n5                                 Junior                 21   \n6                              Sophomore                 19   \n..                                   ...                ...   \n253                               Senior                 21   \n254                               Junior                 19   \n256                                  NaN                 21   \n257                               Senior                 21   \n259                            Sophomore                 18   \n\n    Who do you live with?   \\\n1                     Both   \n2                  Friends   \n3                  Neither   \n5                     Both   \n6                  Friends   \n..                     ...   \n253                 Family   \n254                 Family   \n256                 Family   \n257                 Family   \n259                Friends   \n\n    Do you currently live in a house, apartnment, or dorm?   \\\n1                                            Apartment        \n2                                                House        \n3                                            Apartment        \n5                                            Apartment        \n6                                            Apartment        \n..                                                 ...        \n253                                              House        \n254                                              House        \n256                                          Apartment        \n257                                              House        \n259                                               Dorm        \n\n     How many people live in your household? Do you currently work?  \\\n1                                          4                     No   \n2                                          4                     No   \n3                                          1                     No   \n5                                          4                     No   \n6                                          4                     No   \n..                                       ...                    ...   \n253                                        6                     No   \n254                                        5                     No   \n256                                        4                     No   \n257                                        9                     No   \n259                                        3                     No   \n\n    How many hours do you work per week on average?  \\\n1                                                 0   \n2                                                 0   \n3                                                 0   \n5                                                 0   \n6                                                 0   \n..                                              ...   \n253                                               0   \n254                                               0   \n256                                               0   \n257                                               0   \n259                                               0   \n\n    Do you work on or off campus?  \\\n1                             NaN   \n2                             NaN   \n3                             NaN   \n5                             NaN   \n6                             NaN   \n..                            ...   \n253                           NaN   \n254                           NaN   \n256                           NaN   \n257                    Off-campus   \n259                           NaN   \n\n    Do you work in a department related to your major?  \\\n1                                                  NaN   \n2                                                  NaN   \n3                                                  NaN   \n5                                                  NaN   \n6                                                  NaN   \n..                                                 ...   \n253                                                NaN   \n254                                                NaN   \n256                                                NaN   \n257                                                NaN   \n259                                                NaN   \n\n    Do you have roommates that are part of your major?  \n1                                                  Yes  \n2                                                   No  \n3                                                   No  \n5                                                   No  \n6                                                   No  \n..                                                 ...  \n253                                                 No  \n254                                                Yes  \n256                                                 No  \n257                                                 No  \n259                                                Yes  \n\n[183 rows x 10 columns]",
       "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>What is your current class standing?</th>\n      <th>What is your age?</th>\n      <th>Who do you live with?</th>\n      <th>Do you currently live in a house, apartnment, or dorm?</th>\n      <th>How many people live in your household?</th>\n      <th>Do you currently work?</th>\n      <th>How many hours do you work per week on average?</th>\n      <th>Do you work on or off campus?</th>\n      <th>Do you work in a department related to your major?</th>\n      <th>Do you have roommates that are part of your major?</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>Junior</td>\n      <td>20</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Junior</td>\n      <td>23+</td>\n      <td>Friends</td>\n      <td>House</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Senior</td>\n      <td>23+</td>\n      <td>Neither</td>\n      <td>Apartment</td>\n      <td>1</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Junior</td>\n      <td>21</td>\n      <td>Both</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Sophomore</td>\n      <td>19</td>\n      <td>Friends</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>253</th>\n      <td>Senior</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>6</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>254</th>\n      <td>Junior</td>\n      <td>19</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>5</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n    <tr>\n      <th>256</th>\n      <td>NaN</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>Apartment</td>\n      <td>4</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>257</th>\n      <td>Senior</td>\n      <td>21</td>\n      <td>Family</td>\n      <td>House</td>\n      <td>9</td>\n      <td>No</td>\n      <td>0</td>\n      <td>Off-campus</td>\n      <td>NaN</td>\n      <td>No</td>\n    </tr>\n    <tr>\n      <th>259</th>\n      <td>Sophomore</td>\n      <td>18</td>\n      <td>Friends</td>\n      <td>Dorm</td>\n      <td>3</td>\n      <td>No</td>\n      <td>0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Yes</td>\n    </tr>\n  </tbody>\n</table>\n<p>183 rows × 10 columns</p>\n</div>"
      },
-     "execution_count": 10,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -166,12 +166,12 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:00:29.333356Z",
-     "start_time": "2024-02-23T02:00:29.313068Z"
+     "end_time": "2024-02-23T02:10:58.763694Z",
+     "start_time": "2024-02-23T02:10:58.755858Z"
     }
    },
    "id": "34f69a756f513fb7",
-   "execution_count": 10
+   "execution_count": 4
   },
   {
    "cell_type": "markdown",
@@ -189,7 +189,7 @@
     {
      "data": {
       "text/plain": "<Figure size 800x800 with 1 Axes>",
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Zm2++qXA4fNAuzoF+j+FwWGvWrNH555+vKVOm9J43YcKE3rFWHR0d/da6bNky7dq1S3V1dZL+0xIpSUuXLtV7773X2+1ZWlqqxYsXy+Vyac+ePdq4caNWrVqlnJycPjWefvrpB318+xur+dJLL2nFihVavny5Hn/8cSUmJvZbt6Te8b2S5PP51NTUpOOPP16Sep8v/d3+iSeeqObm5t7HqKfmj7/ORnLJoZ4Wy573tqefflrHHXdcn99/WlqavvjFL6q8vFxbt27t8/NXXHFFnzHGJ554oiQN+NoeivT0dM2fP7/3+dvU1KTt27f3eV70PH8/+ugjNTY29mn1DQQCuvbaa+Vw/Ocj/Atf+IIyMjIO6Koe6D34lltu0Te+8Q394he/0Pe///0Ru4+IPgS+ONbV1dUnXH3cf/3Xf2np0qW6+uqrVVBQoEsvvVSPPPLIkMJfUVHRkCZoTJ8+vc/3hmFo2rRpQx6/NlQVFRUqLCw84PHoGWhfUVHR5/jkyZMPuI7s7Gy1trYOeDvTp0/v80bd3+0MxeLFi7V27Vo9//zzeuONN9TU1KS//OUvSk5OVmNjo9ra2vT73/++NxT2fPV8GDQ0NAyrxo//ziRpxowZ/f7OduzYIdM0NX369APq2bZtW28th2IYhpYsWdI7Vq9nZuu0adMk9Q18Bxv/1GOg32NjY6O8Xq9mzpx5wHmzZs1SJBIZcMzh/uP42tratGXLlt6xhEuWLFEoFNL69etVVlamPXv29J7f8zgf6rabmprk8Xj6HD/iiCMOWoPP59PZZ5+to48+Wo888sigX5MtLS36xje+oYKCAiUnJysvL6/3Ntrb2w84/+OPZ3Z2tiT1Pp4VFRVyOBx9Qvah7uNw9YxJ7HktV1RUHPIx7Ll8fwPdh5GybNmy3rF6b7zxRu+sbmnv8+Kdd96R3+8/4Pl7qOeF2+3WlClTDrg//b0Hv/LKK/rud7+r7373u4zbiwPM0o1T1dXVam9v7/2APJjk5GS9+uqreumll/TUU0/p2Wef1cMPP6xTTz1Va9askdPpHPB29m8hGCmHWsA3HA4PqqaRcKjbMQ8yrmmsjBs3TqeddtpBL+sJ6Z/97GcPuvabtLflaKxEIhEZhqFnnnnmoI/lYBYKXrZsmf71r3/pgw8+6NNqJu39wPz2t7+tmpoavf766yosLOzTQtdjLH6P+4/X6pkdecIJJ0ja+zubPn26Xn/99d7geDgzMQ/1ektMTNRZZ52lJ598Us8+++ygF9y95JJL9MYbb+jb3/62FixYoLS0NEUiEZ155pkH/cMvGl4XmzdvVn5+vjIyMob182N1H5YtW6a77rpLpaWleuONNzRv3rze5/2SJUvk9/v19ttv6/XXX5fL5eoNg0PV33vwnDlz1NbWptWrV+tLX/rSIf9ggD0Q+OLU6tWrJUkrVqzo9zyHw6Hly5dr+fLl+uUvf6mbb75Z//u//6uXXnpJp5122ojvnrBjx44+35umqZ07d/YJI9nZ2Qcd1F9RUdHnQ30otRUXF+v5559XZ2dnn1a+Dz/8sPfykVBcXKz3339fkUikTwvaSN/Ox/XMiAyHw4cMhcOt8eO/M2lvN1R/O5lMnTpVpmnqiCOOGPZ6c/sHqdLS0j7dggsXLlRiYqJefvllrVu3TmedddawbiMvL08pKSkHXbPxww8/lMPh0KRJk/q9jvz8/N5Ql5qaqtmzZ/cOl5D+0xpZXV0tp9PZGwZ7HudD3fa4ceMGveyKYRj661//qvPOO08XX3yxnnnmmYPOkt9fa2urXnjhBd1444364Q9/2Hv8YL/vwSouLlYkEtGuXbv6tFCN1JqYb775pnbt2tVnyZbi4uJDPoY9lx+u4bwP7v/8ffPNN/vMIC8sLFRxcbFKS0tVWlqqo48+uvePhf2fF/u/3wUCAZWVlQ34+t7fuHHj9Oijj2rZsmVavnx57x9HsCe6dOPQiy++qB//+Mc64ogj+p191tLScsCxBQsWSNq7tIKk3g+cgWZVDtZf/vKXPuMKH330Ue3Zs0crV67sPTZ16lS99dZbCgQCvcf+/e9/H9C1NpTazjrrLIXDYf3617/uc7xnR4T9b/9wnHXWWaqrq9PDDz/ceywUCumuu+5SWlqaTj755BG5nY9zOp268MIL9dhjjx10yZTGxsZh1/jEE0+opqam9/v169dr3bp1/T5mn/rUp+R0OnXjjTce0HJimuaAs50l6dhjj1VSUpL++te/qqampk8LX2Jioo455hj95je/OWCZk6FwOp0644wz9OSTT/bpoq6vr9eDDz6oZcuWDaoladmyZdq4caPWrFlzwG4fS5Ys0ZtvvqnXXntN8+fP7/2DY8KECVqwYIHuv//+Ps/hzZs3a82aNUMOsW63W48//rgWLVqkc845R+vXr+/3/J6Wro//fvaf0T1UPc+JX/3qVyN2nT0qKiq0atUqud3uPt2TZ511ltavX68333yz95jH49Hvf/97lZSUDGmty0PpCWNDeR/sWU/yhRde0IYNGw76vHjiiSe0ffv2Ps/f0047TW63W7/61a/6/G7+9Kc/qb29fcgznidOnKjnn39e3d3dOv300wf12kNsooXP5p555hl9+OGHCoVCqq+v14svvqi1a9equLhY//znP5WUlHTIn73pppv06quv6uyzz1ZxcbEaGhp09913a+LEib1vQFOnTlVWVpZ+97vfKT09XampqVq8ePGwuwZycnK0bNkyXXHFFaqvr9cdd9yhadOm9Vli4uqrr9ajjz6qM888U5dccol27dqlBx544IBxQUOp7ZxzztEnPvEJ/e///q/Ky8t11FFHac2aNXryySd17bXXHnDdw/XFL35R99xzj1atWqV33nlHJSUlevTRR1VaWqo77rij3zGVh+vnP/+5XnrpJS1evFhf+MIXNHv2bLW0tOjdd9/V888/3xvwh1rjtGnTtGzZMn35y1+W3+/XHXfcodzcXH3nO985ZC1Tp07VT37yE11//fUqLy/X+eefr/T0dJWVlekf//iHvvjFL+q6667r9/643W4tWrRIr732mhITEw/YiWTJkiW67bbbJB1eN+lPfvKT3vUov/KVr8jlcumee+6R3+8/YL23Q1m2bJnuvfdevf3227rmmmsOqLO9vV3t7e29u+H0uPXWW7Vy5UqdcMIJuuqqq9Td3a277rpLmZmZw9p3Njk5Wf/+97916qmnauXKlXrllVc0d+7cg56bkZGhk046SbfccouCwaCKioq0Zs2aPus6DtWCBQt02WWX6e6771Z7e7uWLFmiF154od917g7m3Xff1QMPPKBIJKK2tja9/fbbeuyxx2QYhlavXt2nR+B//ud/9NBDD2nlypX6+te/rpycHN1///0qKyvTY489dsBY1eFITk7W7Nmz9fDDD2vGjBnKycnR3LlzD/nY9li2bFlvb8vH14hcsmSJHnrood7zeuTl5en666/XjTfeqDPPPFPnnnuutm/frrvvvluLFi06YEHqwZg2bZrWrFmjU045RStWrNCLL7447C5xRDErpgZj9PUsy9Lz5Xa7zfHjx5unn366eeedd/ZZ/qPHx5fOeOGFF8zzzjvPLCwsNN1ut1lYWGhedtll5kcffdTn55588klz9uzZpsvl6rMMysknn2zOmTPnoPUdalmWhx56yLz++uvN/Px8Mzk52Tz77LPNioqKA37+tttuM4uKiszExERz6dKl5oYNGw64zv5q+/iyLKa5d6mGb37zm2ZhYaGZkJBgTp8+3bz11lvNSCTS5zxJ5jXXXHNATYdaLubj6uvrzSuuuMIcN26c6Xa7zXnz5h106ZihLssymHPr6+vNa665xpw0aZKZkJBgjh8/3ly+fLn5+9//fsg17r9Exm233WZOmjTJTExMNE888URz06ZNfc79+HOrx2OPPWYuW7bMTE1NNVNTU80jjzzSvOaaa8zt27cP6n5ff/31piRzyZIlB1z2+OOPm5LM9PR0MxQKHXD5UH6P7777rrlixQozLS3NTElJMT/xiU+Yb7zxxqBqNE3T3L59e+9r8eOvn0gkYmZlZZmSzIcffviAn33++efNpUuXmsnJyWZGRoZ5zjnnmFu3bu1zTs/je7AllPZflqVHU1OTOXv2bHP8+PHmjh07Dll3dXW1ecEFF5hZWVlmZmamefHFF5u1tbUHLEFyqNvveR8qKyvrPdbd3W1+/etfN3Nzc83U1FTznHPOMauqqoa0LEvPl8vlMnNycszFixeb119//UHfK0zTNHft2mVedNFFZlZWlpmUlGQed9xx5r///e8+5/S8B/39738/6G0e7DW6vzfeeMNcuHCh6Xa7B71Eyz333NO7HNXHvfvuu733s76+/oDLf/3rX5tHHnmkmZCQYBYUFJhf/vKXzdbW1j7n9PcefLD3jHXr1vUuN3SwJXkQ2wzTtHCUOYCYVV5eriOOOEK33nrrgK1xAABrMYYPAADA5gh8AAAANkfgAwAAsDnG8AEAANgcLXwAAAA2R+ADAACwOQIfAACAzRH4AAAAbI7ABwAAYHMEPgAAAJsj8AEAANgcgQ8AAMDmCHwAAAA2R+ADAACwOQIfAACAzRH4AAAAbI7ABwAAYHMEPgAAAJsj8AEAANgcgQ8AAMDmCHwAAAA2R+ADAACwOQIfAACAzRH4AAAAbI7ABwAAYHMEPgAAAJsj8AEAANgcgQ8AAMDmCHwAAAA2R+ADAACwOQIfAACAzRH4AAAAbI7ABwAAYHMEPgAAAJsj8AEAANgcgQ8AAMDmCHwAAAA2R+ADAACwOQIfAACAzRH4AAAAbI7ABwAAYHMEPgAAAJsj8AEAANgcgQ8AAMDmCHwAAAA2R+ADAACwOQIfAACAzRH4AAAAbI7ABwAAYHMEPgAAAJsj8AEAANgcgQ8AAMDmCHwAAAA2R+ADAACwOQIfAACAzRH4AAAAbI7ABwAAYHMEPgAAAJsj8AEAANgcgQ8AAMDmCHwAAAA2R+ADAACwOQIfAACAzRH4AAAAbI7ABwAAYHMEPgAAAJsj8AEAANgcgQ8AAMDmXFYXAACHIxwxFYhEFAxHFAibCkYiMk3JlLnvX8k0zb3/SjJNqWjXNsnhkAzjP1/7vjecThlJSTISE6XExN7/G06nxfcUAIaPwAcgKpimqe5QRP7wvvAWiSgQjigYNhXY931PqPvP96bCpjnk28r597+HXqDL9Z/w1xMIe75PTJSRnCxHerocmZkyMjP3/uviLRZAdODdCMCYiZimPIGwuoIheYJhdQX2/uvZ9+/Qo9sYCoVkdnXJ7Ooa9I8Yqan/CYAZGXL0BMGef1NTZRjGKBYNAHsR+ACMqFDElCcQ2i/UheUJhuQJhOUNha0ub0yZHo/CHo9UW3vwE5zOvSFw3Dg58/PlKCiQs6BAjtxcGQ6GWAMYOQQ+AMPmCYbU2h1Uq2/vV2cgJH84YnVZsSMcVqSlRZGWFoU++ug/x53OvSGwoOA/QTA/X46MDOtqBRDTCHwABsUfjqjVF+gT8Ah3oyQcVqS+XpH6egX3O2wkJfWGP2dBgZxFRXIUFNAtDGBABD4ABwhHTLX5gmrxBXrDnScYX92x0cj0+RSuqFC4ouI/BxMT5Zo0Sc7Jk+WaPFnOoiImiwA4AO8KANQVCKnJG1CLL6hWX0Ad/lB0T6DAf/j9Cu3cqdDOnfJLktMpZ2Hh3vC3LwQaSUlWVwnAYgQ+IA6FIqYavX7Ve/Z+0XpnI+GwwlVVCldVSaWlkmHIkZ+/txWwuFiuyZMZCwjEIQIfECc6/SHVeXyq9/jV1B1QhCa8+GCaitTXK1BfL23YIEly5OcrYcYMuWbMkHPiRMYAAnGAwAfYVCgSUYM3oPouv+q9fnlpxcM+kYYG+Rsa5H/9dRkpKXJNn743AE6dundBaQC2Q+ADbKTdH+ztpm2mFQ+DYHq9Cm7apOCmTZLTKVdxsVwzZihh5kw5srKsLg/ACDFMcxj7EgGICqZpqrk7qKrObtV1+dQdYpmUwVj+t99bXUJMcOTl/afrd9Ikun6BGEYLHxCDOv0hVXZ0q6qzm65ajJpIY6P8jY3yl5bKSE1Vwty5cs+fL2dhodWlARgiAh8QI3yhsKo7fKrs6FabPzjwDwAjyPR4FFi3ToF16+QYN04J8+fLPX++HJmZVpcGYBDo0gWiWCgSUW2nT5UdPjV6/ayNN0Lo0h05zpISuefPV8Ls2Uz4AKIYgQ+IMqZpqt7rV1V7t2q7/ArzEh1xBL5R4HIpYeZMJcyfL9e0aTIcDqsrArAfunSBKNHqC6iyo1vVHT72qEXsCYUU3LJFwS1b9o73mzNHCUcdJRfj/YCoQOADLBSOmKrs6NauVo86AiGrywFGhOnxKLB+vQLr18s5YYLcixcrYe5cGU6n1aUBcYsuXcACvlBYu9q8Km/z0ppnAbp0x56Rmir3woVyH3usHOnpVpcDxB0CHzCG2nxB7Wz1qLqzm0WRLUTgs5DDoYQ5c+RevFiuoiKrqwHiBl26wCgzTVN7uvza2epRU3fA6nIAa0UiCn7wgYIffCBnUdHe7t7Zs+nuBUYZLXzAKAlGIqpo3zs+z8PiyFGFFr7oYqSlyX3ssXu7e1NTrS4HsCUCHzDCPMGQdrV6Vd7uVYh+26hE4ItSTqcS5s5V4gknyFlQYHU1gK3QpQuMkCZvQDtbPdrT5WOBZGA4wmEFN21ScNMmuY48UkknnSTnhAlWVwXYAoEPOEzN3QFtaexkfB4wgkIffqiuDz+Ua8YMJZ50EhM8gMNE4AOGqd0f1JbGTtV5/FaXAthW6KOPFProI7mmTlXiySfLNWmS1SUBMYnABwxRVyCkrU2dqu70WV0KEDdCu3YptGvX3uB36qns4AEMEYEPGKTuYFjbmrtU0e5ljB5gkd7gN3Omkj7xCSZ3AINE4AMG4A9H9FFzl3a1eVgsGYgSoe3b1bV9uxLmzFHiKafIOW6c1SUBUY3ABxxCMBLRzhaPdrR6WF4FiFLBLVsU3LpV7qOPVuLy5XKkpFhdEhCVCHzAx4Qjpna3ebS9xaMA+9wC0c80FXj3XQW2blXSSSfJfdxx7NwBfAyBD9jHNE2Vt3frw+ZOdYcIekDM8fnkW7NGgXfeUdKKFUqYPt3qioCoQeADtHfR5E0N7Wr3h6wuBcBhijQ3y/vgg3JNm6akFSsY3weIwIc45wuFtbmxU5Ud3VaXAmCEhXbuVNfu3XIvWqSkU06RkZRkdUmAZQh8iEumaWpXm1fbmjoVZEIGYF+RiALr1in4wQdK/MQn5F64UIZhWF0VMOYIfIg7zd6ANtJ9C8QV0+uV76mnFNiwQclnnilXSYnVJQFjisCHuOEPR/RBQwfdt0Aci9TXy3P//UqYO1dJZ54pR2qq1SUBY4LAh7hQ2e7VB42d8rPMCgBJwc2bFdq9W0krV8o9d67V5QCjjsAHW/MEQnqvvl0N3oDVpQCIMqbXq+7HHlNwyxYln3WWHOnpVpcEjBoCH2wpYpra2eLRtuYuhU0mZQA4tNCHH6qrvFxJK1bIvWCB1eUAo4LAB9tp9QX1bl0bkzIADJrp86n7ySf3tvZ98pNyZGZaXRIwohxWFwCMFNM09WFzp16uaCLsARiW0M6d6vztb+XfsEEmvQOwEQIfbMEbDOu1qhZtbeoSb9EADovfL99TT8mzerUira1WVwOMCAIfYl51Z7deKG9UUzcTMwCMnHBZ2d7WvnXraO1DzCPwIWaFIhG9s6dN62vb2C0DwOgIBuV79ll5/vIXRTo7ra4GGDYCH2JSqy+gF8ubVMEiygDGQLi8XF333KPgrl1WlwIMC4EPMcU0TW1v7tLLFc3qCoatLgdAHDE9HnkfeEC+F16QGWERd8QWlmVBzOgOhbVhT5saWUQZgIX8r7+uUGWlUi68UI6MDKvLAQaFFj7EhNpOn14obyTsAYgK4cpKdf3udwru2GF1KcCgEPgQ1UIRU+/Vteut2lYFwkzMABA9zO5ueR98UN1r1sgMM8QE0Y0uXUStNl9Qb+9pU2eARZQBRK/Am28qXFW1t4s3K8vqcoCDooUPUam6s1uvVDYT9gDEhHB19d5ZvB9+aHUpwEER+BBVTNPU1qZOra9tU5iFTgHEENPnk/fhh9X9zDPM4kXUIfAhaoQiptbVtunD5i6rSwGAYQusXy/PAw/I7GadUEQPAh+igjcY1iuVTart8lldCgActnBZmbr+9CeFm5utLgWQROBDFGjuDuiliia1+xmvB8A+Is3N8vzxjwqVlVldCkDgg7Uq2r16rapZ/jDjXQDYj+nzyfPAA/Jv2GB1KYhzBD5YwjRNfdDQoXfq2hVhbgYAO4tE5HvqKXU/+yyTOWAZAh/GXDAS0Zs1rdrR6rG6FAAYM4F16+R96CGZfr/VpSAOEfgwpjyBkF6paFadhzc8APEntHOnuv70J0VaW60uBXGGwIcx0+j166XKJnWwmDKAOBZpbFTXH/+oUGWl1aUgjhD4MCbK2rx6vaqF/XABQJLp9crzl78osHGj1aUgThD4MOo+au7Se/XtIuoBwH7CYXU/+aT8paVWV4I4QODDqNrS1KnNTZ1WlwEAUcv3/PPyvfii1WXA5gh8GDXvN3RoO9ukAcCA/K+9tncPXvYQxygh8GHEmaapd+vatJNlVwBg0ALr16v7n/9krT6MCgIfRlTENLVhT5vK29k0HACGKrhxo7yPPSYzHLa6FNgMgQ8jJhwxta62VVWdPqtLAYCYFdq6de8CzcGg1aXARgh8GBGhiKk3a1q0p4sFlQHgcIV27ZLngQfYlQMjhsCHwxYMR1Ra3aIGb8DqUgDANsKVlfLcf78iXq/VpcAGCHw4LIFwRK9Vt6i5m7AHACMtvGePPPfeq0gny1vh8BD4MGy+UFivVjarzcc4EwAYLZGmJnX9+c+KtLVZXQpiGIEPw+IN7g177IsLAKPPbGuT5y9/oaUPw0bgw5D1hL2uIMsGAMBYibS2yrN6NWP6MCwEPgyJPxRRaXWzvCHCHgCMtUhjo7x//SuzdzFkBD4MWigS0Rs1LeoMEPYAwCrh2lp5HnyQdfowJAQ+DErENPVWTatamaABAJYLV1bK+8gj7MiBQSPwYUCmaertPW2sswcAUSS0c6e8jz/O3rsYFAIfBrSpoUM1bJcGAFEntHWruv/1L5mmaXUpfZimqdNOO00rVqw44LK7775bWVlZqq6utqCy+EXgQ7+2NnVqdxszwgAgWgU3bpTv2WetLqMPwzB07733at26dbrnnnt6j5eVlek73/mO7rrrLk2cONHCCuMPgQ+HtKvVow+bu6wuAwAwgMD69fK98ILVZfQxadIk3XnnnbruuutUVlYm0zR11VVX6YwzztDRRx+tlStXKi0tTQUFBfrc5z6npqam3p999NFHNW/ePCUnJys3N1ennXaaPB6Phfcm9hH4cFDVHd3a1NBhdRkAgEHyv/66/KWlVpfRx+WXX67ly5fryiuv1K9//Wtt3rxZ99xzj0499VQdffTR2rBhg5599lnV19frkksukSTt2bNHl112ma688kpt27ZNL7/8sj71qU9FXbd1rDFMHkF8TL3HrzdrWhThmQGbWv6331tdAjBqks8/X+6jjrK6jF4NDQ2aM2eOWlpa9Nhjj2nz5s167bXX9Nxzz/WeU11drUmTJmn79u3q6urSwoULVV5eruLiYgsrtxda+NBHS3dA62paCXsAEKO6//UvhSorrS6jV35+vr70pS9p1qxZOv/887Vp0ya99NJLSktL6/068sgjJUm7du3SUUcdpeXLl2vevHm6+OKL9Yc//EGtra0W34vYR+BDr05/SG/UtChEoy8AxK5wWN6HH1akrc3qSnq5XC65XC5JUldXl8455xxt3Lixz9eOHTt00kknyel0au3atXrmmWc0e/Zs3XXXXZo5c6bKysosvhexjcAHSXv3x329ulmBMGEPAGKd6fXK89BDUbkF2zHHHKMtW7aopKRE06ZN6/OVmpoqae8s36VLl+rGG2/Ue++9J7fbrX/84x8WVx7bCHxQOGLqzZoWdYdYvBMA7CLS0CDvY49F3cLM11xzjVpaWnTZZZfp7bff1q5du/Tcc8/piiuuUDgc1rp163TzzTdrw4YNqqys1OOPP67GxkbNmjXL6tJjGoEPere+Xe3+kNVlAABGWGjHDvnWrLG6jD4KCwtVWlqqcDisM844Q/PmzdO1116rrKwsORwOZWRk6NVXX9VZZ52lGTNm6Pvf/75uu+02rVy50urSYxqzdOPczlaP3mf5FcQZZuki3iR/8pNyL1xodRmwEC18cazR69cHhD0AsL3up59WiEkPcY3AF6e8wbDW17aJ5l0AiAORiLyPPKJwc7PVlcAiBL44FI6Yequ2Vf5wdA3kBQCMHtPnk/fBB2V2d1tdCixA4ItD79W3q80XtLoMAMAYi7S0yPP3v0fdzF2MPgJfnNnV6lFlB3/dAUC8CpeVRd3MXYw+Al8cafIGmJELAFBg3ToFt261ugyMIQJfnOgOhrWutpVJGgAASZL3n/9UuKXF6jIwRgh8cSBiMkkDAPAxfr+8jzwiM8TC+/GAwBcHNta3q5VJGgCAj4nU16v76aetLgNjgMBnc7vbPCpvZ5IGAODggu+9p8CmTVaXgVFG4LOxNl+QSRoAgAF1P/WUwk1NVpeBUUTgs6lwxNSGPW2KMEsDADCQYFDexx5jPJ+NEfhsamtTpzoCvHABAIMTqauTb+1aq8vAKCHw2VCT168drR6rywAAxJjA+vUKbt9udRkYBQQ+mwlGItpQ1251GQCAGNX95JOKdDD+224IfDbzfkOHvMGw1WUAAGKU2d0t7z/+IdNkELidEPhspLbLpwqWYAEAHKZwebkCb79tdRkYQQQ+m/CHwnqPrlwAwAjxPf+8Im1tVpeBEULgs4n36tvZOg0AMHKCQXn/+U+rq8AIIfDZQEW7V7VdfqvLAADYTLisTIF33rG6DIwAAl+M8wbD2sRuGgCAUdK9di2zdm2AwBfDTNPUO3VtCrGdBgBgtPj96v7Xv6yuAoeJwBfDdrV61egNWF0GAMDmQjt3KrBxo9Vl4DAQ+GJUhz+ozU00sQMAxobvuecU6ey0ugwME4EvBpmmqXfr2kVPLgBgrJg+n7qfesrqMjBMBL4YVNHRrRZf0OoyAABxJrR9uwKbN1tdBoaBwBdjguGItjTSpA4AsIbvmWcU8XisLgNDROCLMVubO1lgGQBgGdPrle/ZZ60uA0NE4Ish7f6gdrd6rS4DABDngps3K1RebnUZGAICXwzZVN8h5mkAAKJB93PPyTT5VIoVBL4YUd3RraZu1twDAESHSF2dgu++a3UZGCQCXwwIRSL6oJE19wAA0cX34osyfT6ry8AgEPhiwIfNXeoOMVEDABBdTK9XvldesboMDAKBL8p1BULa2cr0dwBAdAqsX69wU5PVZWAABL4ot6mhgx01AADRKxKR77nnrK4CAyDwRbE9XT7Ve/xWlwEAQL9CO3cquGOH1WWgHwS+KBWOmHq/gYkaAIDY4HvuOZnhsNVl4BAIfFFqR2uXPEFeOACA2BBpblZg/Xqry8AhEPiikDcY1vZmJmoAAGKL75VX2Gc3ShH4otC2pk6FWb0cABBr/H75XnzR6ipwEAS+KNMZCKmyo9vqMgAAGJbge+8p3NxsdRn4GAJflNnW1Ml+uQCA2GWa8rMYc9Qh8EWRdn9Q1Z1sUQMAiG3BzZtZjDnKEPiiyNamTqtLAADg8Jmm/K++anUV2A+BL0q0+gLa08UiywAAewhu3qxwY6PVZWAfAl+U2NLYZXUJAACMHFr5ogqBLwo0dwfU4KV1DwBgL8EtW2jlixIEviiwrYnWPQCADTFjN2oQ+CzWQuseAMDGglu3KtzQYHUZcY/AZ7EPm2ndAwDYGGP5ogKBz0JtvqDqPLTuAQDsLbhlC618FiPwWYjWPQBAvPAxls9SBD6LdPiDqu1iVw0AQHwIbd2qcH291WXELQKfRWjdAwDEG/9bb1ldQtwi8FnAGwyphj1zAQBxJvjBB4p4PFaXEZcIfBbY3eaVaXURAACMtXBYgXfesbqKuETgG2PhiKny9m6rywAAwBKBDRtkhsNWlxF3CHxjrKazW4FwxOoyAACwhNnZqeDWrVaXEXcIfGNsV5vX6hIAALBUYN06q0uIOwS+MdTqC6rVF7S6DAAALBWuqVGopsbqMuIKgW8M7W5lZhIAABKtfGONwDdGAuGIqjuZrAEAgLR3u7VIZ6fVZcQNAt8YKW/3KsxaLAAA7BWJKLBhg9VVxA2X1QXEA9M0VcZkDQDo45evvaZ/bdumHU1NSnK5dNykSbrx9NM1fdy43nPKWlr0/TVr9FZlpQKhkJZPm6ZbzjpL+Wlp/V53bUeHbli7Vmt37lR3MKgpOTn6zXnn6eiiIknSXaWlurO0VJL0jWXL9LUlS3p/dkN1tb711FN64eqr5XI6R+Geo0fgnXeUeOKJMlzEkdFGC98YqPf45Qmy5hAA7K+0vFxXL1qktVdfrX98/vMKRSK6YPVqeQIBSZInENAFq1fLkPTPyy/Xs1ddpUA4rEsffFCRyKGXt2rr7taKP/1JLqdTj37mM3rrmmv0kzPOUFZysiRpc12dbn7pJf3poov0p4su0k9ffFFb9u3xGgqH9c1//1u3f/KThL0xYHo8Cm7ebHUZcYFIPQZYigUADvTY5z7X5/u7zz9f0269VRtra7W0pETrKitV2damV7/0JWUkJUmSfnvBBSr5+c/1almZTpk69aDXe8frr2tiZqbuPv/83mMl2dm9/9/R1KQ5BQU6ecoUSdKcgoLeY7964w0tKS7WMftaAjH6/OvWyb1ggdVl2B4tfKPMEwip3uO3ugwAiHodvr17jGfva4nzh8MyJCXu192X5HLJYRh6s7LykNfzzPbtWlBYqMsfeUTTbrlFJ/7ud7p/v+28ZhcUaGdzs6ra2lTZ1qadzc2alZ+vspYW/fW99/T9U08dnTuIg4rU1Sm8Z4/VZdgegW+U7aZ1DwAGFIlEdP2zz+r4SZM0u6BAkrRo4kSlut360dq18gYC8gQC+v6aNQqbpuq7ug55XeWtrfrz229rak6OHvvc53TVscfqu888owc3bpQkzczL0w+XL9cFq1frU6tX60fLl2tmXp6u/de/dOPpp+vFnTt1wm9+oxN/9zuVlpePwb1HYNMmq0uwPbp0R1E4YqqincAHAAO57umntbWhQc9eeWXvsXGpqbrv4ov13089pXvWrZPDMHThvHk6asIEOQzjkNcVMU0dXVioH552miTpqAkTtLWhQfdu2KBP7+s6vHLRIl25aFHvzzy4caPSEhN13KRJOvauu/TSF7+omo4OXfXoo9p07bV9Whkx8oKbNyvpjDNkOGiHGi08g0dRVWe3AhHWYgGA/nz7qaf03Ecf6akrrlBRZmafy06dNk0bv/ENNXs8cjocykpO1oxbb1XJ3LmHvL6C9HTNzMvrc2xmXp7+tW3bQc9v9nj0i5df1tNXXKEN1dWalpurqfu+gpGIdjY3a86+VkeMDtPjUWjXLiVMn251KbZFlB5Fle0stAwAh2Kapr791FP694cf6p+XX95nYsXH5aamKis5Wa/s3q1Gj0crZ8485LnHT5qknc3NfY7tbG7WpI+FyR7XP/ecvnLCCSrKzFTYNBXcbwZwKBJRuJ8ZwRg5wffft7oEWyPwjZLuUFhN3QGrywCAqHXdU0/p4fff1x8uvFBpbrfqOztV39mp7uB/9hx/4L339HZVlcpaWvTwpk1a9fe/6ysnnNBnrb5z779fv99vm66vnHCC3q6u1m2vvqrdzc36+/vv6/533tHVxx13QA0v7dqlXc3N+sK+7t1jCgu1o6lJa3fs0H0bNshpGH1uC6Mn+OGHMv1MchwtdOmOktpOn9UlAEBU+9O+XRY+ed99fY7/5rzz9Jmjj5Yk7Wxq0k3PP6/W7m5NzsrSt048UdeccEKf88taWtTs/c946WOKivTAf/2XbnrhBd3yyisqzs7Wz848U5fMn9/n57qDQX376af154sukmPf2LGizEzdsnKlrnniCbldLv32gguUnJAw0ncdBxMKKbh1q9z7fvcYWYZpmgwyGwWvVDapuTs48IkAxtzyv/3e6hIAHISzpERpl19udRm2RJfuKPAGw4Q9AACGKFxerkh7u9Vl2BKBbxTUdDJZAwCA4QgweWNUEPhGQTXj9wAAGBZm644OAt8I8wRDavXRnQsAwHBEmpoUqqmxugzbIfCNsJoOWvcAADgctPKNPALfCKM7FwCAwxPcskUsIjKyCHwjqCsQUpuf7lwAAA6H6fEoXF1tdRm2QuAbQbTuAQAwMkIffWR1CbZC4BtBLMcCAMDICBL4RhSBb4R0BkJq94esLgMAAFuINDQo0tZmdRm2QeAbIdUdtO4BADCSaOUbOQS+EVLD+D0AAEYU4/hGDoFvBHgCIXUE6M4FAGAkhcrLZfr9VpdhCwS+EdDgDVhdAgAA9hMOK7Rrl9VV2AKBbwQ0ePnrAwCA0cA4vpFB4DtMpmmqkRY+AABGRWjHDnbdGAEEvsPU7g8pEI5YXQYAALZker3sujECCHyHqZHuXAAARhWzdQ8fge8wMWEDAIDRxTi+w0fgOwwR01QTgQ8AgFEVaWhQpLPT6jJiGoHvMLR0BxRmICkAAKMuXFlpdQkxjcB3GOjOBQBgbIQIfIeFwHcYGjxM2AAAYCwQ+A4PgW+YgpGIWn1Bq8sAACAuROrrZfrYt364CHzD1OQNiNF7AACMEdNUqKrK6ipiFoFvmNhdAwCAscXEjeEj8A0T4/cAABhbjOMbPgLfMPhCYXUEQlaXAQBAXAnX1MgM8fk7HAS+YWCxZQAALBAOK1xba3UVMYnANwxtfmbnAgBghVBFhdUlxCQC3zC0sRwLAACWYOLG8BD4hqHNz/gBAACsEKqqksm2pkNG4BsibzCsQDhidRkAAMQnv1+R+nqrq4g5BL4hamf8HgAAlgrX1FhdQswh8A0R4/cAALBWuK7O6hJiDoFviJihCwCAtQh8Q0fgG6J2HxM2AACwUrihgYkbQ0TgG4JAOCJvKGx1GQAAxLdAQJGWFquriCkEviFg/B4AANGBbt2hIfANATN0AQCIDhEC35AQ+IaABZcBAIgO4YYGq0uIKQS+IWinSxcAgKhA4BsaAt8ghSOmOgO08AEAEA3MtjaZQRpiBovAN0jt/qCYAA4AQPSINDZaXULMIPANEgsuAwAQXcIEvkEj8A1SJxM2AACIKozjGzwC3yCx4DIAANGFLt3BI/ANkjdI4AMAIJpEmputLiFmEPgGicAHAEB0iXR0WF1CzCDwDUIoElEwwhxdAACiSiikiMdjdRUxgcA3CLTuAQAQnSLt7VaXEBMIfINA4AMAIDqZBL5BIfANAoEPAIDoRAvf4BD4BoElWQAAiE4EvsEh8A0CLXwAAEQnAt/gEPgGgcAHAEB0Ygzf4BD4BoEuXQAAohMtfIND4BtAxDTlC0WsLgMAAByE6fHIDLHf/UAIfAPopjsXAICoRivfwAh8A6A7FwCA6MY4voER+AbAhA0AAKIbLXwDI/ANgMAHAEB0i3R2Wl1C1CPwDcAfZsIGAADRzPT5rC4h6hH4BhCKmFaXAAAA+kHgGxiBbwChCC18AABENb/f6gqiHoFvALTwAQAQ3UwC34AIfAMIEvgAAIhqdOkOjMA3AFr4AACIbrTwDYzANwDG8AEAEN1o4RsYgW8AtPABABDdaOEbGIFvAAQ+AACiXDAokx65fhH4+hGOmCLuAQAQ/ejW7R+Brx9B/loAACA20K3bLwJfP+jOBQAgNtDC1z8CXz8IfAAAxAYmbvSPwNcPAh8AALGBFr7+Efj6wRp8AADECD6z+0Xg6wctfAAAwA4IfP1gH10AAGAHBL5+sAofAACwAwJfPxwyrC4BAADgsBH4+mGQ9wAAgA0Q+PrhIPEBAAAbIPD1g7wH2NOm8y5Ty5KTFJk8WXLwNgjA/lxWFxDNDMbwAbbUlJyupslHSpOPVFIooCNa6jSutkLuinKpu9vq8gBgxBH4+uEg7wG253O5tS1/spQ/Wcb8pZrU1awJddVKqyyTmpqsLg8ARgSBrx+M4QPii+lwqDIjT5UZedKMo5Xj82hyY7WyqivkrK6SwmGrSwRwKCZLqfWHwNcP4h4Q31qSUtUyaaY0aaYSw0GVtNQrv7ZC7ooyyeu1ujwAGDQCXz/o0gXQw+9M0Pa8idqeN1Gav0QTO1tUVF+l1MpyGY0NVpcHAP0i8PXDoEsXwMEYhqozclWdkStNX6BMv1cljTXKrqmQs7KCrl8AUYfA1w/iHoDBaE9M0aaJ06WJ05VwbEglbfXKr61SUsVuqavL6vKA+OAi0vSHR6cfTNoAMFRBp0s7cou0I7dImrtYhZ42TayrUlpVuYz6OqvLA2zLSEy0uoSoRuDrB2P4ABwWw1BtWrZqp2VL0+YrI9Ct4sYa5dRUylVZLoVCVlcI2IaRlGR1CVGNwNcPxvABGEkd7mR9UDRNKpqmhIUhTW5r0Pi6KiWV75Y6O60uD4hptPD1j8DXDzZcAjBagk6XduUWalduoTRnscZ72jSxvloZVWUy9uyxujwg9hD4+kXg6wctfADGSl1qluqmZElT5iot4FNJU61ya/d1/QYCVpcHRD26dPtH4OuHi0F8ACzQ5U7S5sIpUuEUOY8Jq7itQePrqpVcsVtqb7e6PCD6JCTIcNAv1x8CXz8SHIYMSWzWAsAqYYdTu3MmaHfOBGn2IhV42jWxsVqZleUy9tSynRQgxu8NBoGvH4ZhKMHpUCAcsboUAJAk1admqj41UyqZo5SgX0c071FuTYUSKsslv9/q8gBLEPgGRuAbgNtpKMCi+QCikDchUVvGl0jjS+Q4+kQVdzRqfF21Usp3S22tVpcHjBnG7w2MwDeARKdDXSLxAYhuEYdDZVkFKssqkI5cqHHdHZrcUKPMqnI5amukCD0VsC9a+AZG4BuA28kgUACxpyk5Q03FGVLxLCWHAipp3qO82kolVJRJPp/V5QEji8A3IALfAAh8AGJdt8utbQXF2lZQLMdRSzWps1kT6qqUWlEmtTRbXR5w2GjhGxiBbwBupnkDsJGIw6GKzDxVZOZJM49RTneXihtrlFVdLkd1FV2/iEmM4RsYgW8AiS4CHwD7aklOU8vkmdLkmUoKBVTSUqe8PZVyV5RLXq/V5QGDYiQnW11C1CPwDSCJLl0AccLncuvD/Mn6MH+yNH+pJnU0q7C+WmlVZVJjo9XlAYfkyMiwuoSoR+AbQJLLaXUJADD2DENVmeNUlTlOmrFA2X6PJjfWKLu6Qs6qSinM6gWIHo7MTKtLiHoEvgEk0aULAGpNTFXrxBnSxBlyHxvSEW11yqutVGJFmeTxWF0e4pxB4BsQgW8AtPABQF8Bl0vbx03U9nETpXknqKirRUX11UqrLJfRUG91eYhDdOkOjMA3ALfTIachhdmuEgAOZBiqSc9VTXquNO0oZfq9Km6qVU5NhZyVFVIoZHWFsDkjNVWGizgzEB6hQUhyOeUJMl4FAAbSnpii94umSUXTlLAwpOK2BhXsqVRSeZnU1Wl1ebAhxu8NDoFvEJJcDgIfAAxR0OnSztxC7cwtlOYs1gRPmybWVyu9qkxGXZ3V5cEmGL83OAS+Qdg7ji9odRkAELsMQ3vSsrUnLVuaOk/pgW6VNNUqp6ZSrspyKch7LIaH8XuDQ+AbhNQEJm4AwEjqdCfrg8KpUuFUuRaGVNzWqII9lUquKJM6OqwuDzGELt3BIfANQpqbhwkARkvI4dKunAnalTNBmrNY4/d1/WZUl8vYs0cymTWHQyPwDQ5JZhDSCXwAMGbqUrNUNyVLmjJXaUG/iptqNa62Qq6KcikQsLo8RBnG8A0OSWYQCHwAYI2uhERtmXCENOEIOY8Oq7i9UQV1VUqpKJPa2qwuD1GAFr7BIckMgtvpUKLTIX84YnUpABC3wg6ndmeP1+7s8dKsRcrzdmhyQ7UyqsrlqK2h6zceOZ0yUlOtriImEPgGKd3tkr+brgQAiBaNKRlqLJktlcxWSsivkqY9GldbqYSKMsnvt7o8jAFHZqYMw7C6jJhA4BukdLdLTQQ+AIhKXleito4vkcaXyLFgmSZ1NKmwp+u3tcXq8jBKHPn5VpcQMwh8g5SeyEMFALEg4nCoIitfFVn50pELNa67U5Maa5RVVS5HTbUUYXiOXTgJfINGihkkJm4AQGxqSk5X0+QjpclHKikU0BEtdRpXWyF3RbnU3W11eTgMBL7BI8UMEoEPAGKfz+XWtvzJUv5kGfOXalJnswrrq5VasVtqbra6PAyRo6DA6hJiBilmkJJdDjkNQ2FmgQGALZgOhyoz81SZmSfNOFo5Po8mN1Qrq6ZCzuoqKcwe6lHN5ZIjJ8fqKmIGgW+QDMNQutupNn/I6lIAAKOgJSlVLZNnSpNnKjEcVElLnfJrK+WuKJO8XqvLw8c4xo2T4XBYXUbMIPANQbrbReADgDjgdyZoe94kbc+bJM1foomdLSqqr1Za5W6psdHq8iDG7w0VgW8I0hNdUqfVVQAAxpRhqDojV9UZudL0o5Tp96qksUbZ1eVyVlXS9WsRAt/QEPiGgIkbAID2xBRtmjhdmjhdCYtCOqK1Tnl7qpRUXiZ5uqwuL24wYWNoSDBDQOADAOwv6HTpo3ET9dG4idLc41XoadXEumqlVZXLqK+zujxbo4VvaEgwQ5DmdsmQxDxdAMABDEO1aTmqnZYjTZuvjIBXxY17lFtTLmdlhRRiDPhIMZKS5MjIsLqMmELgGwKHYSgj0aV2Jm4AAAbQ4U7RB0VTpaKpSlgYUnFbgwr2VCmpYrfUyYDww0F37tAR+IYoN9lN4AMADEnQ6dLO3ELtzC2U5i7W+K5WTWyoUUZVmYw9e6wuL+bQnTt0BL4hyk12a3cb6zEBAIavLi1bdWnZ0pS5Sgv4VNJcq9zqCrkqy6Vg0Oryop6TFr4hI/ANUW5ygtUlAABspMudpM0TpkgTpsi5MKzitkaNr6tUckWZ1N5udXlRyTlxotUlxBwC3xClJLiU5HLIF4pYXQoAwGbCDqd254zX7pzx0uzjVOBp18SGamVWl8uorZXY3nPvhA26dIeMwDcMuclu1XT6rC4DAGBz9amZqj8iUzpijlKCfh3RvEe5NRVKqCyX/H6ry7OEc9IkGYZhdRkxxzBN/lwYqp2tHr3f0GF1GQCAOOWIRFTc0ajxe6qUUlEmtbVaXdKYSVy+XEnLllldRsyhhW8YcpPdVpcAAIhjEYdDZVkFKssqkGYdq7zuDk2qr1FmdbkcNdW27vp1TZ5sdQkxicA3DJmJLjkNQ2Ebv6AAALGjMTlDjSUZUsksJYcCKmneo7zaSiVUlEk+Gw1BcrnkLCqyuoqYRJfuML1W1axGb8DqMgAAOCRHJKJJnc2aUFep1IpyqaXZ6pIOi3PyZKVdcYXVZcQkWviGKTfZTeADAES1iMOhisw8VWTmSTMXKqe7S8WNNcqqLpejukqKxNaKE3TnDh+Bb5gYxwcAiDUtyWlqmTxTmjxTSaGASlrqlLenUu7yMqm72+ryBuQk8A0bgW+YcpJYgBkAELt8Lrc+zJ+sD/MnS/OXalJHswrrq5VWuVtqarK6vAMZhlyTJlldRcwi8A1TgtOhzEQX++oCAGKfYagqc5yqMsdJMxYo2+fZ2/VbUyFnVaUUDltdoRz5+TKSkqwuI2YR+A5DTrKbwAcAsJ3WpFS1TpohTZoh97EhHdG6R3l7qpRYUSZ5PJbUROve4WGW7mGo7OjWhj1tVpcBAMDYME0VdbWoqL5aaZVlMhoaxuymkz/1KbnnzRuz27MbWvgOwzgmbgAA4olhqCY9VzXpudK0o5Tp96q4sUY5PV2/odHr9XIVF4/adccDAt9hSElwKsPtUkeAbl0AQPxpT0zR+xOnSxOnK+HYkEpa65VfV6Wk8t1SV9eI3Y4jP1+OjIwRu754RJfuYdrS2KHtLdaMZwAAICqZpgo9rSqqr1F6VZmMurrDujr3kiVKPv30ESouPtHCd5gmpCUR+AAA2J9hqDYtR7VpOdLUeUoPdKukqVY5NRVyVVZIweCQri5h+vRRKjR+EPgOU3ZSghKdDvnDsbVaOQAAY6XTnawPCqdKhVPlWhhScVujCvZUKrmiTOro6P+HExNZcHkE0KU7At6pa1NFe/SvUA4AQLQZ72nTxPoaZVSVyajbI30slrhmzVLqJZdYVJ190MI3AiakJRH4AAAYhrrULNVNyZKmzFFa0K/iplqNq6mQq7JcCgSUMG2a1SXaAi18IyAcMfXvnXUK80gCADAinJGwitubNHfedLlSU60uJ+Y5rC7ADpwOQ3kpiVaXAQCAbYQdTrVOmEjYGyEEvhEyIY39/QAAGEl8to4cAt8ImZBGCx8AACOpkM/WEUPgGyFJLqeykxKsLgMAAFtIS3AqI5HP1ZFC4BtBtPIBADAy6M4dWQS+EcSTEwCAkVHIZ+qIIvCNoMzEBKUkOK0uAwCAmJbodCgnme7ckUTgG2ETUunWBQDgcExIS5RhGFaXYSsEvhFGty4AAIdnckay1SXYDoFvhOWluJXs4mEFAGA4UhOcyk12W12G7ZBMRphhGPxlAgDAME3OSKY7dxQQ+EZBcWaK1SUAABCT+AwdHQS+UZDmdtEcbYH/d+pxuvDIwgO+/nDT9ZKkgN+nP9x0vS5fPEefOWaabvna1Wprahz09d/zo+/qwiML9e/7/9B7LBjw687vfE2fXThDX12xTJveeLXPzzzxp7v1xx//78jcQQCwubwUN6tdjBKX1QXYVXFmspq7A1aXEVd+8egzioTDvd9X7vhQN115qU5YcY4k6d6f3aB3X3le1915j1LSMvTHH/+vbvnaVbr5oX8OeN3r1j6jjza9o5z88X2Or334Ae3e8r5u/tu/9N6rL+qO667Rn0vfl2EYqq+u1POPPKhbHntmZO8oANhUMUOiRg0tfKNkYnqSXIxBGFOZObnKzsvv/Xrn5ec1fnKJ5hx3gjydHXrxsYe06rs3aN7xyzR17nxd87Nfavt7G/TRxnf6vd7m+j3640++r2/c+hs5XX3/RqrevVPHnnqGJk+fqTM/s0odLc3qaG2RJP3+hv/R5677X6WkpY/afQYAu3A5DBWmE/hGC4FvlLgcDhWls0SLVYKBgF7952M69VOXyjAM7d7yvkLBoOYvObH3nIlTpmtcYZG29xP4IpGIfvWdr+u8q76sydNnHnB5yczZ+vCd9fL7urXx9ZeVnVegjOwcvfqvx5WQmKjFp68clfsHAHZTlJ4kl4OGktFCl+4oKs5MUUVHt9VlxKX1LzwrT2eHPnHBJZKktsYGuRLcSs3I7HNeVm6e2poaDnk9T/zhN3I6nTr7c1cd9PJTL7xUFR9t1bVnn6L07Bx9647fqau9TX/71a266S+P6sE7fqHSp59UwaRiXXPzL5VbMGHk7iQA2EhxBpM1RhOBbxSNS3ErLcGprmB44JMxol549CEdfeInlFMwfuCTD2HX5vf11Oo/6tbHnjvkEgGuhAR94Yc/63Ps19dfq7M+d5XKtm3W+hee1W1PPK8n/vgb/eknP9B37vrjsOsBALtKTXBqXAqTHUcTXbqjjOnlY6+hplofvPmaTrv4073HsvLyFQoG5Olo73NuW3OjssblH/R6tr2zTu3NTfrSqYt08ZxJunjOJDXWVuv+X9yo/3fqcQf9mQ/eKlXVzo+08jNXaPO6N3XMSacqKSVFS1aeqy3r3xy5OwkANlKcydi90UYL3yibnJmsrU2dMq0uJI689PjflJE7TgtPPq332JQ58+VKSND7b76uE1acLUmq2b1TTbU1mrlg4UGv5+RzL9T8E07sc+zHV39aJ513oU694L8OOD/g9+mPP/6evnHrr+V0OhWJhKXQ3t98OBTc+z0A4ACT6c4ddbTwjbJkl1P5qYlWlxE3IpGIXvzHwzrl/Iv7zKhNTc/QqRdepvt+cYM+eKtUuza/r99875uauWChZuwX+L628kStW7t3GZX07BxNnnFkny+ny6XscfkqmjLtgNv++9136JiTTtWU2fMkSUces0hvrX1a5du36pm/3qsjj1k0yvceAGJPPmvvjQla+MZASWay6j1+q8uIC++/8aqaamu0/FOXHnDZFdffIIfD0P994wsKBvxasOyUA8bf1ZbtkqezY8i3W/nRh3rj2X/ptn+s7T12wopPasv6N/WDz1ygwiOm6tr/+83Q7xAA2Nxkhj6NCcM0TXobR1nENPX0rnoFwjzUAAD0SHAYOmtqgZwsxzLq6NIdAw7D0CQWkwQAoI+J6cmEvTFC4BsjJTRZAwDQx7TsVKtLiBsEvjGSmZSgPNYYAgBAkjQ+NVHpiUwlGCsEvjE0IyfN6hIAAIgKfCaOLQLfGCpITVQmf80AAOJcdlICO2uMMQLfGOMvGgBAvJuRw9i9sUbgG2MT05NYYBIAELdSE5wqTEuyuoy4Q+AbY4ZhaDqzkgAAcWpadqoMg6VYxhqBzwLFmSlyO3myAwDii9vpYJkyixD4LOByGJqSRSsfACC+TMlKYaFlixD4LDI1K1VOmrQBAHHCaez97IM1CHwWSXQ5VJzJdmsAgPgwOTNFiS5ih1V45C00PTtVtPEBAOIBExatReCzUKrbpaJ0pqYDAOytMC1JaW42HrASgc9iLMQMALA7Flq2HoHPYllJCcpnexkAgE3lJicoJ5nPOasR+KLAdFr5AAA2NSs33eoSIAJfVChITVRucoLVZQAAMKLyU9zKT020ugyIwBc15uVlWF0CAAAjai6fbVGDwBclcpLdKmIzaQCATUzKSFZWEr1X0YLAF0Xm5KWzLh8AIOY5DGnOOManRxMCXxRJc7s0JYtNpQEAsW1KVqpSElh3L5oQ+KLMkbnpcrGxNAAgRiU4DB2ZS+tetCHwRZlEl0MzWaYFABCjZuSkye0kXkQbfiNRaFp2qpLZYBoAEGOSXQ5NY8/cqESqiEJOh6HZ41ioEgAQW2aNS5eTYUlRicAXpSZnJCszkQGvAIDYkOF2qTgj2eoycAgEvihlGAYLVgIAYsacvHQZBq170YrAF8UKUhOVn8KG0wCA6DYu2a0JbB4Q1Qh8UY5WPgBAtJubx7jzaEfgi3JZSQmazJgIAECUKkpPUk4yvVHRjsAXA2aPSxeTngAA0cZpGJpH615MIPDFgJQEJ6uWAwCizpxx6WyhFiMIfDFiRk6aMty8qAAA0SE7KUFTs9n/PVYQ+GKEwzB0zPhMq8sAAECGpGMKMlmGJYYQ+GJITrKbLWsAAJabnpOqzKQEq8vAEBD4YszscelKSXBaXQYAIE6lJjg1K5eJGrGGwBdjXA5DRxfQtQsAsMbRBZnslxuDCHwxqCA1kbX5AABjbnJGsvJTE60uA8NA4ItR8/MzlOjk1wcAGBuJTofm57P7U6wiMcQoNy88AMAYmp+fITcNDTGL31wMm5SRrPE0rQMARllBaqImMZQophH4YtyCgky5GDwLABglTsPQ0QX0KMU6Al+MS0lwas44pscDAEbH7HFpbJ9mAwQ+G5iSlaLcZBbABACMrKykBBb8twkCnw0Yxt61+ejZBQCMFIchLWT7NNsg8NlERmICK58DAEbMvLwMtk+zEQKfjczISVVeitvqMgAAMa4wLUlT6cq1FQKfjRiGoWMnZLFOEgBg2FJcTh0zni087YZkYDPJLqcW8kIFAAyDIWlRIQ0HdsRv1IYmpCVpanaK1WUAAGLM7HHpyk1maJAdEfhsal5ehjITWTcJADA4+Sluzchh3J5dEfhsymEYOq4wW06m0wMABpDodOjYCVkswWJjBD4bS3e7tIDtcAAAA1g0IUtJLqfVZWAUEfhsrjgzRSWZbHgNADi4mTmpyk9NtLoMjDICXxw4Kj+T8XwAgAPkJidoNvuxxwUCXxxwOgwtLsxWAnuvAQD2cTsMLZqQzbi9OEHgixNpbpeOGZ9ldRkAgChxzPgspSQwbi9eEPjiSFF6kqaxVQ4AxL2pWSkqTE+yugyMIQJfnJmbl64cNsMGgLg1Ltmtefms4BBvCHxxxmEYOr4oW8lMvweAuJOW4NTxRdlyMG4v7hD44lCSy6klE7PlYhIHAMQNt8PQCRNz2Cc3TvFbH0GrVq2SYRj6+c9/3uf4E088EXWzoDITE7S4MFvRVRUAYDQYkhYXZSvdzRJd8YrAN8KSkpL0i1/8Qq2trVaXMqCC1EQdxU4cAGB7x4zPVF4KiyvHMwLfCDvttNM0fvx4/exnPzvkOY899pjmzJmjxMRElZSU6LbbbhvDCvuakpWq6czcBQDbmpGTquLMFKvLgMUIfCPM6XTq5ptv1l133aXq6uoDLn/nnXd0ySWX6NJLL9UHH3ygG264QT/4wQ903333jX2x+8zNS1dhGtPzAcBuCtOSNIedNCAC36i44IILtGDBAv3oRz864LJf/vKXWr58uX7wgx9oxowZWrVqlb761a/q1ltvtaDSvQzD0KIJWcpmuRYAsI3spAQtmpAVdWPIYQ0C3yj5xS9+ofvvv1/btm3rc3zbtm1aunRpn2NLly7Vjh07FA6Hx7LEPpwOQycUZSuF5VoAIOYluxw6oShbTlZjwD4EvlFy0kknacWKFbr++uutLmXQepZrYc9dAIhdLoehJUU5SuIPeOyH+dmj6Oc//7kWLFigmTNn9h6bNWuWSktL+5xXWlqqGTNmyOm0/sWZsW+5ltLqFplWFwMAGBJD0nETspTJEB18DC18o2jevHn6zGc+o1/96le9x771rW/phRde0I9//GN99NFHuv/++/XrX/9a1113nYWV9pWfmqgFBZlWlwEAGKJ5+RkazyQ8HASBb5TddNNNikQivd8fc8wxeuSRR/S3v/1Nc+fO1Q9/+EPddNNNWrVqlXVFHsQRWSmakcNyLQAQK6ZkpWgay2zhEAzTNOm5w0GZpqn1e9pU0+mzuhQAQD8mpicxIxf9ooUPh2QYho4dn6WCVFZnB4BoVZSWpGMJexgAgQ/9cjoMHV+YrfwUt9WlAAA+ZkJaohYVZslB2MMACHwY0N41+nKUR+gDgKhRkJqoxYXZhD0MCoEPg+Lct64ToQ8ArJef4tbxhD0MAYEPg9bT0jcumdAHAFbJS3HrhKIcdtHAkBD4MCQuh6ElE7OVm8yingAw1nKT3WyZhmEh8GHIXA6Hlk7MUQ4ruQPAmMlJStDSidlyOfjoxtDxrMGw9IS+bEIfAIy67KQELZ2YQ9jDsPHMwbAlOB1aRugDgFGVmejS0ok5SnDykY3h49mDw5Lg3NvSl5VI6AOAkZbhdmnZpFy5CXs4TDyDcNjcToeWTcpRZqLL6lIAwDbS3S6dOClHiYQ9jACeRRgRbqdDJ07KJfQBwAjITNwX9lxOq0uBTRimaZpWFwH7CIQjerOmRc3dQatLAYCYNG7f0iuM2cNIIvBhxIUjpt7e06baLp/VpQBATClMS9SiCayzh5FH4MOoME1T7zd2aFer1+pSACAmlGQm6+iCTBlsl4ZRQODDqNrR0qUPGjutLgMAotrMnFTNycuwugzYGIEPo666o1sb6toU4ZkGAAeYn5+hadmpVpcBmyPwYUw0eQN6s6ZFQVIfAEiSHIZ07IQsTUxPtroUxAECH8ZMhz+oN6pb5Q2FrS4FACzldjp0QlG2cpPdVpeCOEHgw5jqDoX1RnWL2v0hq0sBAEukJji1dGKO0tysW4qxQ+DDmAtFInqrpk0NXr/VpQDAmMpJStAJRTlKdLHGHsYWgQ+WiJim3qtrV0VHt9WlAMCYKEpL0rETslhjD5Yg8MFSW5s69WFzl9VlAMCompGTqjnj0lljD5Yh8MFyFe1ebaxvV5hnIgCbcTkMLRyfqSJm4sJiBD5EhXZfUOtqW9UVZAYvAHvIcLu0uChb6UzOQBQg8CFqBMMRvVPXzh68AGLepPQkHT0+Uy4HkzMQHQh8iDo7Wrq0ubFTPDEBxBqHIc3Ly9BUds5AlCHwISo1dwe0rrZVvlDE6lIAYFCSXQ4tLsxWDospIwoR+BC1/KGw3t7TpgZvwOpSAKBf+SluLZqQzfp6iFoEPkQ10zS1rbmLpVsARK2ZOWmaPS6NJVcQ1Qh8iAl1Hp827GlTgLVbAESJBIehYydkaUJaktWlAAMi8CFmeINhrattVasvaHUpAOJcZqJLxxdmK5UlVxAjCHyIKRHT1PsNHdrd5rW6FABxqjgzWQvyM9kiDTGFwIeYVN3Rrffq2xWM8PQFMDbcTocW5GdoYga7ZiD2EPgQs7qDYb1b3656j9/qUgDYXFFakhYUZCjR5bS6FGBYCHyIeRXtXr3f0EFrH4AR53YaWpCfSaseYh6BD7bQHQrrvbp21dHaB2CEFO5r1UuiVQ82QOCDrVR2dOv9+nYFaO0DMExup6Gj8jM1iVY92AiBD7bjC4W1sb5dtV209gEYmglpiTq6IJNWPdgOgQ+2VdXRrU0NHQqE2Y8XQP/cDkNHFdCqB/si8MHWfKGwNtV3qKbLZ3UpAKIUrXqIBwQ+xIXqzm5tqu+Qn9Y+APskOAwdlZ+hyZkpVpcCjDoCH+KGPxTRpoZ2VXfS2gfEu6L0JM3Pz1AyrXqIEwQ+xJ16j18fNHSoIxCyuhQAYywr0aX5+Zkal+K2uhRgTBH4EJdM01RZm1dbm7uY1AHEgUSnQ3Py0lWckSzDYA9cxB8CH+JaMBzRh81d2tXmEUv3AfbjMKRp2amamZumBIfD6nIAyxD4AEldgZA2N3awdh9gI4VpSZqXl65Ut8vqUgDLEfiA/TR6/Xq/oUPtfsb3AbEqM9Gl+fkZyktJtLoUIGoQ+ICPMU1TFR3d2trYKR/j+4CYkeh0aPa4dJVkMk4P+DgCH3AIoUhE25s92tHaxfg+IIo5DGlqVqqOzE1TgpNxesDBEPiAAXiDYW1u7GD9PiAKTUhL1Ly8DKUxTg/oF4EPGKTm7oC2NXWqwRuwuhQg7k1IS9TMnDTlJLOeHjAYBD5giFq6A9re0qU9zOgFxlxRepKOzElTZlKC1aUAMYXABwxTuz+oj5q7VN3pEy8iYPQYkiZlJGtmbprS6boFhoXABxymrkBIH7V0qbKjm8kdwAhyGNLkjGTNzEljLT3gMBH4gBHiDYa1o7VL5W3dCvOyAobNaUglmSmanpOmlASn1eUAtkDgA0aYPxTWzlaPdrd5FaTJDxg0l2HoiKwUTc9JVZKLoAeMJAIfMEqC4Yh2tXm0s9WrAAs4A4eU4DA0NTtV07JT5WYdPWBUEPiAURaKmCpv82pHa5e6QwQ/oEdaglNHZKWoJDOFBZOBUUbgA8aIaZra0+XX7javGrws6YL45DCkwrQkHZGVwl63wBgi8AEW6AqEVNbmVUWHV4EwL0HYX2qCUyWZKSrOTGZ8HmABAh9goXDEVE1nt3a3edXiC1pdDjCiDEkT9rXm5ae4ZRiG1SUBcYvAB0SJdn9QFe3dqurolp9JHohhKfta80pozQOiBoEPiDIR09SeLp/K27vV4PGziwdigiFpfFqijshKUUFKIq15QJQh8AFRrDsUVmV7tyraveoKhq0uBzhAWoJTkzKSVZKVomRa84CoReADYkRLd0C1XT7VdvoIf7BUhtulovQkFaUnKSMxwepyAAwCgQ+IQe3+oGo7fart8qndH7K6HMSBrKQEFaXtDXlp7GsLxBwCHxDjPMFQb/hr7mamL0ZObnKCCveFvJQEQh4Qywh8gI34QmHt6fKrptOnRi8TPjA0hqRxKW4VpiWpMD2JMXmAjRD4AJsKhiPa4/GrttOneo9fYV7qOAiHIeWlJKooLUkT0pKU6GKLM8COCHxAHAhHTDV4/WryBtTUHVCbL0jrX5xyGFJ2klt5KW6NS3YrN9ktp4MlVAC7I/ABcSgUiai5O6gmr19N3QG1+oKK8E5gSw5Dyklya1zK3pCXk0TAA+IRgQ+AwhFTLb5AbwtgS3eQLuAYRcADcDAEPgAHiJimWn3B3gDY3B1QiCbAqETAAzAYBD4AAzJNU23+kFp9AXX4Q3u/AiEF2PN3TLkMQ5lJLmUmJigrMUGZSQnKcLsIeAAGROADMGy+ULg3/HX4g73/pzXw8KUkOJXhdikj0aWspL0BLzXByR61AIaFwAdgxHmDIbXv1xLY4Q+qMxBiYshBpCY4lZHoUrrbpQy3S+mJCUp3u+Si1Q7ACCLwARgTpmmqKxhWdzCs7lBYvlBEvlBY3fv+9YUi8oXDtgmFDkNKcjmV7HIo2eU88P8Je//voMUOwBgg8AGIKv6eIBg+RCgMhRWOmAqbGtOZxA5DchqGnA5DTsOQy2Eo0fmf4LY3yPX83yG300H3K4CoQeADENMiprkvAJp7/2/uXWZm7//N3nC4//emuS/A7Qtvh/zXMOR07A16hDcAsYzABwAAYHNsmggAAGBzBD4AAACbI/ABAADYHIEPAADA5gh8AAAANkfgAwAAsDkCHwAAgM0R+AAAAGyOwAcAAGBzBD4AAACbI/ABAADYHIEPAADA5gh8AAAANkfgAwAAsDkCHwAAgM0R+AAAAGyOwAcAAGBzBD4AAACbI/ABAADYHIEPAADA5gh8AAAANkfgAwAAsDkCHwAAgM0R+AAAAGyOwAcAAGBzBD4AAACbI/ABAADYHIEPAADA5gh8AAAANkfgAwAAsDkCHwAAgM0R+AAAAGyOwAcAAGBzBD4AAACbI/ABAADYHIEPAADA5gh8AAAANkfgAwAAsDkCHwAAgM0R+AAAAGyOwAcAAGBzBD4AAACbI/ABAADYHIEPAADA5gh8AAAANkfgAwAAsDkCHwAAgM0R+AAAAGyOwAcAAGBzBD4AAACbI/ABAADYHIEPAADA5gh8AAAANkfgAwAAsDkCHwAAgM0R+AAAAGyOwAcAAGBzBD4AAACbI/ABAADYHIEPAADA5gh8AAAANkfgAwAAsDkCHwAAgM0R+AAAAGyOwAcAAGBzBD4AAACbI/ABAADYHIEPAADA5gh8AAAANkfgAwAAsLn/D25dXXwu+BF0AAAAAElFTkSuQmCC"
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"
      },
      "metadata": {},
      "output_type": "display_data"
@@ -208,12 +208,12 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:00:29.477781Z",
-     "start_time": "2024-02-23T02:00:29.336352Z"
+     "end_time": "2024-02-23T02:10:58.965154Z",
+     "start_time": "2024-02-23T02:10:58.764461Z"
     }
    },
    "id": "da1811cc63b41845",
-   "execution_count": 11
+   "execution_count": 5
   },
   {
    "cell_type": "code",
@@ -221,7 +221,7 @@
     {
      "data": {
       "text/plain": "<Figure size 800x800 with 2 Axes>",
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
@@ -240,12 +240,12 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:00:29.790484Z",
-     "start_time": "2024-02-23T02:00:29.479779Z"
+     "end_time": "2024-02-23T02:10:59.277945Z",
+     "start_time": "2024-02-23T02:10:58.967433Z"
     }
    },
    "id": "201db70188d3e778",
-   "execution_count": 12
+   "execution_count": 6
   },
   {
    "cell_type": "markdown",
@@ -261,7 +261,7 @@
     {
      "data": {
       "text/plain": "<Figure size 640x480 with 1 Axes>",
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
@@ -274,12 +274,12 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:00:30.015262Z",
-     "start_time": "2024-02-23T02:00:29.792483Z"
+     "end_time": "2024-02-23T02:10:59.485432Z",
+     "start_time": "2024-02-23T02:10:59.281076Z"
     }
    },
    "id": "5e460707e32c4a2a",
-   "execution_count": 13
+   "execution_count": 7
   }
  ],
  "metadata": {
-- 
cgit v1.2.3


From 795af57d69a1cf709a00ed4c402869936fc7ae80 Mon Sep 17 00:00:00 2001
From: Anshul Gupta <ansg191@anshulg.com>
Date: Thu, 22 Feb 2024 18:37:01 -0800
Subject: Cleans housing data

---
 CS105MiniProject.ipynb | 48 ++++++++++++++++++++++++++++--------------------
 1 file changed, 28 insertions(+), 20 deletions(-)

(limited to 'CS105MiniProject.ipynb')

diff --git a/CS105MiniProject.ipynb b/CS105MiniProject.ipynb
index 818356f..9203683 100644
--- a/CS105MiniProject.ipynb
+++ b/CS105MiniProject.ipynb
@@ -55,8 +55,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:10:58.731970Z",
-     "start_time": "2024-02-23T02:10:58.699969Z"
+     "end_time": "2024-02-23T02:35:17.657074Z",
+     "start_time": "2024-02-23T02:35:17.625812Z"
     }
    },
    "id": "3bea6ea662d6c063",
@@ -100,7 +100,11 @@
     "                                                 .replace('North District 4 bed 2 bath', '4')\n",
     "                                                 .replace('3 (room), 8 (hall), ~70 (building)', '3')\n",
     "                                                 .astype(int))\n",
-    "df['Who do you live with? '] = df['Who do you live with? '].replace('Family, Friends', 'Both').replace('Family, Friends, Both', 'Both')\n",
+    "df['Who do you live with? '] = df['Who do you live with? '].replace('Family, Friends', 'Both').replace(\n",
+    "    'Family, Friends, Both', 'Both')\n",
+    "df['Do you currently live in a house, apartnment, or dorm? '] = (\n",
+    "    df['Do you currently live in a house, apartnment, or dorm? ']\n",
+    "    .replace('house (renting)', 'House'))\n",
     "# Normalizes non-applicable answers\n",
     "df.loc[df['Do you currently work?'] == 'No', 'How many hours do you work per week on average?'] = 0\n",
     "df.loc[df['Do you currently work?'] == 'No', 'Do you work in a department related to your major?'] = np.nan\n",
@@ -110,8 +114,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:10:58.744774Z",
-     "start_time": "2024-02-23T02:10:58.732815Z"
+     "end_time": "2024-02-23T02:35:17.671536Z",
+     "start_time": "2024-02-23T02:35:17.657952Z"
     }
    },
    "id": "f71f8085d5f66b0",
@@ -140,8 +144,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:10:58.754973Z",
-     "start_time": "2024-02-23T02:10:58.746452Z"
+     "end_time": "2024-02-23T02:35:17.682158Z",
+     "start_time": "2024-02-23T02:35:17.673510Z"
     }
    },
    "id": "6c1d9ee7948e6b9a",
@@ -166,8 +170,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:10:58.763694Z",
-     "start_time": "2024-02-23T02:10:58.755858Z"
+     "end_time": "2024-02-23T02:35:17.690742Z",
+     "start_time": "2024-02-23T02:35:17.683032Z"
     }
    },
    "id": "34f69a756f513fb7",
@@ -208,8 +212,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:10:58.965154Z",
-     "start_time": "2024-02-23T02:10:58.764461Z"
+     "end_time": "2024-02-23T02:35:17.897912Z",
+     "start_time": "2024-02-23T02:35:17.691750Z"
     }
    },
    "id": "da1811cc63b41845",
@@ -221,18 +225,20 @@
     {
      "data": {
       "text/plain": "<Figure size 800x800 with 2 Axes>",
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "plt.subplots(figsize=(8, 8))\n",
     "df_2dhist = pd.DataFrame({\n",
     "    x_label: grp['Do you currently work?'].value_counts()\n",
     "    for x_label, grp in df.groupby('Do you currently live in a house, apartnment, or dorm? ')\n",
     "})\n",
+    "\n",
+    "# Plot heatmap\n",
+    "plt.subplots(figsize=(8, 8))\n",
     "sns.heatmap(df_2dhist, cmap='viridis')\n",
     "plt.xlabel('Do you currently live in a house, apartnment, or dorm? ')\n",
     "_ = plt.ylabel('Do you currently work?')"
@@ -240,8 +246,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:10:59.277945Z",
-     "start_time": "2024-02-23T02:10:58.967433Z"
+     "end_time": "2024-02-23T02:35:18.116782Z",
+     "start_time": "2024-02-23T02:35:17.901109Z"
     }
    },
    "id": "201db70188d3e778",
@@ -261,21 +267,23 @@
     {
      "data": {
       "text/plain": "<Figure size 640x480 with 1 Axes>",
-      "image/png": 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"
+      "image/png": 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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "df.groupby('Do you currently live in a house, apartnment, or dorm? ').size().plot(kind='barh', color=sns.palettes.mpl_palette('Dark2'))\n",
-    "plt.gca().spines[['top', 'right',]].set_visible(False)"
+    "df.groupby('Do you currently live in a house, apartnment, or dorm? ').size().plot(kind='barh',\n",
+    "                                                                                  color=sns.palettes.mpl_palette(\n",
+    "                                                                                      'Dark2'))\n",
+    "plt.gca().spines[['top', 'right', ]].set_visible(False)"
    ],
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-23T02:10:59.485432Z",
-     "start_time": "2024-02-23T02:10:59.281076Z"
+     "end_time": "2024-02-23T02:35:18.248057Z",
+     "start_time": "2024-02-23T02:35:18.118242Z"
     }
    },
    "id": "5e460707e32c4a2a",
-- 
cgit v1.2.3