From 717bd5c3abbc775694a3afa582edacdd8482cdea Mon Sep 17 00:00:00 2001 From: Anshul Gupta 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": [ "
\n", "

CS105 Mini-Project

\n", + "

Does who a student is living with effect if and how they work jobs?

\n", "

By: NAMES HERE

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" ], @@ -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": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
TimestampWhat is your current class standing?Who do you live with?Do you currently live in a house, apartnment, or dorm?How many people live in your household?Do you currently work?How many hours do you work per week on average?Do you work on or off campus?Do you work in a department related to your major?Do you have roommates that are part of your major?
02/9/2024 20:12:14SeniorNeitherHouse6Yes5 - 10Off-campusNoNo
12/9/2024 20:16:34JuniorBothApartment4NoNaNNaNNaNYes
22/9/2024 20:18:55JuniorFriendsHouse4NoNaNNaNNaNNo
32/9/2024 20:24:00SeniorNeitherApartment1NoNaNNaNNoNo
42/9/2024 20:26:16GraduateNeitherApartment1Yes10 - 20Off-campusYesNo
.................................
2552/14/2024 19:46:28JuniorFriendsHouse5Yes10 - 20On-campusNoNo
2562/15/2024 0:28:38NaNFamilyApartmentNorth District 4 bed 2 bathNoNaNNaNNaNNo
2572/15/2024 8:33:45SeniorFamilyHouse9No1 - 5Off-campusNoNo
2582/15/2024 16:10:40SophomoreFamilyApartment4Yes5 - 10On-campusNoNo
2592/15/2024 16:14:11SophomoreFriendsDorm3 (room), 8 (hall), ~70 (building)NoNaNNaNNaNYes
\n

260 rows × 10 columns

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" + }, + "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": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
TimestampWhat is your current class standing?Who do you live with?Do you currently live in a house, apartnment, or dorm?How many people live in your household?Do you currently work?How many hours do you work per week on average?Do you work on or off campus?Do you work in a department related to your major?Do you have roommates that are part of your major?
02/9/2024 20:12:14SeniorNeitherHouse6Yes5 - 10Off-campusNoNo
12/9/2024 20:16:34JuniorBothApartment4No0NaNNaNYes
22/9/2024 20:18:55JuniorFriendsHouse4No0NaNNaNNo
32/9/2024 20:24:00SeniorNeitherApartment1No0NaNNaNNo
42/9/2024 20:26:16GraduateNeitherApartment1Yes10 - 20Off-campusYesNo
.................................
2552/14/2024 19:46:28JuniorFriendsHouse5Yes10 - 20On-campusNoNo
2562/15/2024 0:28:38NaNFamilyApartment4No0NaNNaNNo
2572/15/2024 8:33:45SeniorFamilyHouse9No0Off-campusNaNNo
2582/15/2024 16:10:40SophomoreFamilyApartment4Yes5 - 10On-campusNoNo
2592/15/2024 16:14:11SophomoreFriendsDorm3No0NaNNaNYes
\n

260 rows × 10 columns

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" + }, + "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": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
TimestampWhat is your current class standing?Who do you live with?Do you currently live in a house, apartnment, or dorm?How many people live in your household?Do you currently work?How many hours do you work per week on average?Do you work on or off campus?Do you work in a department related to your major?Do you have roommates that are part of your major?
02/9/2024 20:12:14SeniorNeitherHouse6Yes5 - 10Off-campusNoNo
42/9/2024 20:26:16GraduateNeitherApartment1Yes10 - 20Off-campusYesNo
82/9/2024 22:02:49JuniorFriendsHouse6Yes10 - 20On-campusNoNo
92/9/2024 22:08:43SeniorFamilyHouse5Yes1 - 5On-campusNoNo
132/9/2024 22:15:13JuniorFamilyApartment4Yes10 - 20Off-campusNoNo
.................................
2462/13/2024 19:37:02GraduateFamilyHouse2Yes10 - 20On-campusYesNo
2472/13/2024 21:39:14SeniorFriendsApartment3Yes20 - 40Off-campusNoYes
2522/14/2024 9:48:12JuniorFamilyHouse5Yes20 - 40Off-campusNoNo
2552/14/2024 19:46:28JuniorFriendsHouse5Yes10 - 20On-campusNoNo
2582/15/2024 16:10:40SophomoreFamilyApartment4Yes5 - 10On-campusNoNo
\n

77 rows × 10 columns

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" + }, + "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": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
TimestampWhat is your current class standing?Who do you live with?Do you currently live in a house, apartnment, or dorm?How many people live in your household?Do you currently work?How many hours do you work per week on average?Do you work on or off campus?Do you work in a department related to your major?Do you have roommates that are part of your major?
12/9/2024 20:16:34JuniorBothApartment4No0NaNNaNYes
22/9/2024 20:18:55JuniorFriendsHouse4No0NaNNaNNo
32/9/2024 20:24:00SeniorNeitherApartment1No0NaNNaNNo
52/9/2024 20:45:09JuniorBothApartment4No0NaNNaNNo
62/9/2024 21:55:59SophomoreFriendsApartment4No0NaNNaNNo
.................................
2532/14/2024 13:45:45SeniorFamilyHouse6No0NaNNaNNo
2542/14/2024 16:26:06JuniorFamilyHouse5No0NaNNaNYes
2562/15/2024 0:28:38NaNFamilyApartment4No0NaNNaNNo
2572/15/2024 8:33:45SeniorFamilyHouse9No0Off-campusNaNNo
2592/15/2024 16:14:11SophomoreFriendsDorm3No0NaNNaNYes
\n

183 rows × 10 columns

\n
" + }, + "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": [ - "
\n", - "

CS105 Project

\n", - "

Ali Naqvi, ...

\n", - "

Topic: Does who a student is living with effect if and how they work jobs?

\n", - "
\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": "
", + "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