jamesojo
11/22/2018 - 9:36 PM
Nigerian Graduates.ipynb
{
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"<h1><center><font color='blue'> Nigerian Graduates?</font></centre></h1>\n",
"<em>How many</em> jobs did the men and women get after graduating?\n",
"\n",
"<img src=\"joshua-oluwagbemiga-711748-unsplash.jpg\" alt=\"Nigeria Graduates\" style=\"width: 300px;\"/>\n",
"\n",
"<a style=\"background-color:black;color:white;text-decoration:none;padding:4px 6px;font-family:-apple-system, BlinkMacSystemFont, "San Francisco", "Helvetica Neue", Helvetica, Ubuntu, Roboto, Noto, "Segoe UI", Arial, sans-serif;font-size:12px;font-weight:bold;line-height:1.2;display:inline-block;border-radius:3px\" href=\"https://unsplash.com/@joaccord?utm_medium=referral&utm_campaign=photographer-credit&utm_content=creditBadge\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"Download free do whatever you want high-resolution photos from Joshua Oluwagbemiga\"><span style=\"display:inline-block;padding:2px 3px\"><svg xmlns=\"http://www.w3.org/2000/svg\" style=\"height:12px;width:auto;position:relative;vertical-align:middle;top:-1px;fill:white\" viewBox=\"0 0 32 32\"><title>unsplash-logo</title><path d=\"M20.8 18.1c0 2.7-2.2 4.8-4.8 4.8s-4.8-2.1-4.8-4.8c0-2.7 2.2-4.8 4.8-4.8 2.7.1 4.8 2.2 4.8 4.8zm11.2-7.4v14.9c0 2.3-1.9 4.3-4.3 4.3h-23.4c-2.4 0-4.3-1.9-4.3-4.3v-15c0-2.3 1.9-4.3 4.3-4.3h3.7l.8-2.3c.4-1.1 1.7-2 2.9-2h8.6c1.2 0 2.5.9 2.9 2l.8 2.4h3.7c2.4 0 4.3 1.9 4.3 4.3zm-8.6 7.5c0-4.1-3.3-7.5-7.5-7.5-4.1 0-7.5 3.4-7.5 7.5s3.3 7.5 7.5 7.5c4.2-.1 7.5-3.4 7.5-7.5z\"></path></svg></span><span style=\"display:inline-block;padding:2px 3px\">Joshua Oluwagbemiga</span></a>"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import unicodecsv\n",
"import csv\n",
"import seaborn as sns\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"grad = pd.read_csv('nigerian_graduates_survey.csv', sep = ',')"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
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"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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" }\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 gender</th>\n",
" <th>Year of graduation</th>\n",
" <th>Title of course studied</th>\n",
" <th>Polytechnic/University attended</th>\n",
" <th>What is your highest level of education?</th>\n",
" <th>What best describes your current status?</th>\n",
" <th>How many jobs have you had since graduation including your current one?</th>\n",
" <th>Have you completed your NYSC?</th>\n",
" <th>If you answered yes/ongoing to the previous question, what year did you (or will you) complete your NYSC?</th>\n",
" <th>...</th>\n",
" <th>What currency are you currently paid in?</th>\n",
" <th>Approximately how many hours a day do you currently work?</th>\n",
" <th>As far as you are aware, what was most important to your current employer about your qualification?</th>\n",
" <th>How do you find out about your job(s)?</th>\n",
" <th>Thinking about your current employment, did you work for your employer before or during your higher education study?</th>\n",
" <th>Which form of transport do you use the most?</th>\n",
" <th>Were you able to rent an apartment or buy a car from the salary you got from your first job?</th>\n",
" <th>My course of study prepared me well for employment</th>\n",
" <th>My course of study prepared me well for further studies</th>\n",
" <th>Which of these skills/knowledge did your higher education prepare you for?</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2/8/2018 9:05:23</td>\n",
" <td>Male</td>\n",
" <td>2013</td>\n",
" <td>Electrical & Electronic Engineering</td>\n",
" <td>Obafemi Awolowo University,Ile-Ife</td>\n",
" <td>Bachelor's degree</td>\n",
" <td>Working full time (paid employment)</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>Naira</td>\n",
" <td>8.0</td>\n",
" <td>No one thing was important</td>\n",
" <td>Internship</td>\n",
" <td>No</td>\n",
" <td>Bus</td>\n",
" <td>Yes: From my first job</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>Critical thinking skills, Ability to solve com...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2/15/2018 12:11:32</td>\n",
" <td>Male</td>\n",
" <td>2014</td>\n",
" <td>Psychology</td>\n",
" <td>Obafemi Awolowo University,Ile-Ife</td>\n",
" <td>Bachelor's degree</td>\n",
" <td>Working full time (paid employment)</td>\n",
" <td>2</td>\n",
" <td>Yes</td>\n",
" <td>2017.0</td>\n",
" <td>...</td>\n",
" <td>Naira</td>\n",
" <td>8.0</td>\n",
" <td>IT/SIWES/Internship experience (gained as part...</td>\n",
" <td>Internship</td>\n",
" <td>No</td>\n",
" <td>BRT</td>\n",
" <td>No: From my current job</td>\n",
" <td>Strongly Disagree</td>\n",
" <td>Agree</td>\n",
" <td>Critical thinking skills, Ability to solve com...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2/15/2018 13:47:10</td>\n",
" <td>Female</td>\n",
" <td>2013</td>\n",
" <td>Economics</td>\n",
" <td>Bells University of Technology, Otta</td>\n",
" <td>Bachelor's degree</td>\n",
" <td>Working full time (paid employment)</td>\n",
" <td>2</td>\n",
" <td>Yes</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>Naira</td>\n",
" <td>14.0</td>\n",
" <td>The subject(s) I studied</td>\n",
" <td>Employer's website</td>\n",
" <td>No</td>\n",
" <td>Uber/Taxify/Taxi services</td>\n",
" <td>No: From my current job</td>\n",
" <td>Disagree</td>\n",
" <td>Agree</td>\n",
" <td>Ability to work with others, Written communica...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2/16/2018 13:01:34</td>\n",
" <td>Male</td>\n",
" <td>2017</td>\n",
" <td>Mass Communication (Communication and Language...</td>\n",
" <td>Bowen University, Iwo</td>\n",
" <td>Master's degree</td>\n",
" <td>Self-employed/freelance/entrepreneur</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2/16/2018 13:18:03</td>\n",
" <td>Female</td>\n",
" <td>2013</td>\n",
" <td>Statistics</td>\n",
" <td>Ekiti State University</td>\n",
" <td>Bachelor's degree</td>\n",
" <td>Working full time (paid employment)</td>\n",
" <td>3</td>\n",
" <td>Yes</td>\n",
" <td>2016.0</td>\n",
" <td>...</td>\n",
" <td>Naira</td>\n",
" <td>8.0</td>\n",
" <td>IT/SIWES/Internship experience (gained as part...</td>\n",
" <td>Personal contacts, including family and friends</td>\n",
" <td>No</td>\n",
" <td>Commercial Vehicles</td>\n",
" <td>No</td>\n",
" <td>Agree</td>\n",
" <td>Agree</td>\n",
" <td>Critical thinking skills</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 36 columns</p>\n",
"</div>"
],
"text/plain": [
" Timestamp What is your gender Year of graduation \\\n",
"0 2/8/2018 9:05:23 Male 2013 \n",
"1 2/15/2018 12:11:32 Male 2014 \n",
"2 2/15/2018 13:47:10 Female 2013 \n",
"3 2/16/2018 13:01:34 Male 2017 \n",
"4 2/16/2018 13:18:03 Female 2013 \n",
"\n",
" Title of course studied \\\n",
"0 Electrical & Electronic Engineering \n",
"1 Psychology \n",
"2 Economics \n",
"3 Mass Communication (Communication and Language... \n",
"4 Statistics \n",
"\n",
" Polytechnic/University attended \\\n",
"0 Obafemi Awolowo University,Ile-Ife \n",
"1 Obafemi Awolowo University,Ile-Ife \n",
"2 Bells University of Technology, Otta \n",
"3 Bowen University, Iwo \n",
"4 Ekiti State University \n",
"\n",
" What is your highest level of education? \\\n",
"0 Bachelor's degree \n",
"1 Bachelor's degree \n",
"2 Bachelor's degree \n",
"3 Master's degree \n",
"4 Bachelor's degree \n",
"\n",
" What best describes your current status? \\\n",
"0 Working full time (paid employment) \n",
"1 Working full time (paid employment) \n",
"2 Working full time (paid employment) \n",
"3 Self-employed/freelance/entrepreneur \n",
"4 Working full time (paid employment) \n",
"\n",
" How many jobs have you had since graduation including your current one? \\\n",
"0 3 \n",
"1 2 \n",
"2 2 \n",
"3 0 \n",
"4 3 \n",
"\n",
" Have you completed your NYSC? \\\n",
"0 NaN \n",
"1 Yes \n",
"2 Yes \n",
"3 Yes \n",
"4 Yes \n",
"\n",
" If you answered yes/ongoing to the previous question, what year did you (or will you) complete your NYSC? \\\n",
"0 NaN \n",
"1 2017.0 \n",
"2 NaN \n",
"3 NaN \n",
"4 2016.0 \n",
"\n",
" ... \\\n",
"0 ... \n",
"1 ... \n",
"2 ... \n",
"3 ... \n",
"4 ... \n",
"\n",
" What currency are you currently paid in? \\\n",
"0 Naira \n",
"1 Naira \n",
"2 Naira \n",
"3 NaN \n",
"4 Naira \n",
"\n",
" Approximately how many hours a day do you currently work? \\\n",
"0 8.0 \n",
"1 8.0 \n",
"2 14.0 \n",
"3 NaN \n",
"4 8.0 \n",
"\n",
" As far as you are aware, what was most important to your current employer about your qualification? \\\n",
"0 No one thing was important \n",
"1 IT/SIWES/Internship experience (gained as part... \n",
"2 The subject(s) I studied \n",
"3 NaN \n",
"4 IT/SIWES/Internship experience (gained as part... \n",
"\n",
" How do you find out about your job(s)? \\\n",
"0 Internship \n",
"1 Internship \n",
"2 Employer's website \n",
"3 NaN \n",
"4 Personal contacts, including family and friends \n",
"\n",
" Thinking about your current employment, did you work for your employer before or during your higher education study? \\\n",
"0 No \n",
"1 No \n",
"2 No \n",
"3 NaN \n",
"4 No \n",
"\n",
" Which form of transport do you use the most? \\\n",
"0 Bus \n",
"1 BRT \n",
"2 Uber/Taxify/Taxi services \n",
"3 NaN \n",
"4 Commercial Vehicles \n",
"\n",
" Were you able to rent an apartment or buy a car from the salary you got from your first job? \\\n",
"0 Yes: From my first job \n",
"1 No: From my current job \n",
"2 No: From my current job \n",
"3 NaN \n",
"4 No \n",
"\n",
" My course of study prepared me well for employment \\\n",
"0 No \n",
"1 Strongly Disagree \n",
"2 Disagree \n",
"3 NaN \n",
"4 Agree \n",
"\n",
" My course of study prepared me well for further studies \\\n",
"0 No \n",
"1 Agree \n",
"2 Agree \n",
"3 NaN \n",
"4 Agree \n",
"\n",
" Which of these skills/knowledge did your higher education prepare you for? \n",
"0 Critical thinking skills, Ability to solve com... \n",
"1 Critical thinking skills, Ability to solve com... \n",
"2 Ability to work with others, Written communica... \n",
"3 NaN \n",
"4 Critical thinking skills \n",
"\n",
"[5 rows x 36 columns]"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"grad.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Clean NaN values "
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"grad['x'] = pd.to_numeric(grad['Approximately how many hours a day do you currently work?'], errors='coerce')\n",
"grad = grad.dropna(subset=['Approximately how many hours a day do you currently work?'])\n",
"grad['Approximately how many hours a day do you currently work?'] = grad['Approximately how many hours a day do you currently work?'].astype(int)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"9.0"
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"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"grad['Approximately how many hours a day do you currently work?'].median()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x10eb6a860>"
]
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"execution_count": 31,
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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x120110e48>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.distplot(grad['How many jobs have you had since graduation including your current one?'])"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x116731f98>"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1167e89b0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.distplot(grad['Approximately how many hours a day do you currently work?'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It is quite normally distributed at 8 hours a day. Most people work that or a little bit more"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116f7bcc0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = sns.boxplot(x = 'How many jobs have you had since graduation including your current?', y = 'What is your highest level of education?', data = grad, palette = 'husl' , hue = 'What is your gender')"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['Working full time (paid employment)', 'Youth Corper (NYSC)',\n",
" 'Due to start a job in the next month/developing a professional portfolio/creative practice',\n",
" 'Voluntary or other unpaid work or on an internship',\n",
" 'Engaged in full-time further study, training or research',\n",
" 'Self-employed/freelance/entrepreneur', 'Unemployed',\n",
" 'Taking time out to prepare for further studies, GMAT, professional exams',\n",
" 'Engaged in part-time further study, training or research',\n",
" 'Doing something else (e.g. looking after home or family)'],\n",
" dtype=object)"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"grad['What best describes your current status?'].unique()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}