Explore the Data Set.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"text-align:center\">\n",
    "    <a href=\"https://skills.network/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDA0321ENSkillsNetwork21426264-2022-01-01\" target=\"_blank\">\n",
    "    <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/assets/logos/SN_web_lightmode.png\" width=\"200\" alt=\"Skills Network Logo\"  />\n",
    "    </a>\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Survey Dataset Exploration Lab**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Estimated time needed: **30** minutes\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Objectives\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After completing this lab you will be able to:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*   Load the dataset that will used thru the capstone project.\n",
    "*   Explore the dataset.\n",
    "*   Get familier with the data types.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the dataset\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the required libraries.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "#from bs4 import BeautifulSoup\n",
    "#import requests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset is available on the IBM Cloud at the below url.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_url = \"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DA0321EN-SkillsNetwork/LargeData/m1_survey_data.csv\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the data available at dataset_url into a dataframe.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# your code goes here\n",
    "df = pd.read_csv(dataset_url)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore the data set\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is a good idea to print the top 5 rows of the dataset to get a feel of how the dataset will look.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Display the top 5 rows and columns from your dataset.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Respondent</th>\n",
       "      <th>MainBranch</th>\n",
       "      <th>Hobbyist</th>\n",
       "      <th>OpenSourcer</th>\n",
       "      <th>OpenSource</th>\n",
       "      <th>Employment</th>\n",
       "      <th>Country</th>\n",
       "      <th>Student</th>\n",
       "      <th>EdLevel</th>\n",
       "      <th>UndergradMajor</th>\n",
       "      <th>...</th>\n",
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       "      <th>Trans</th>\n",
       "      <th>Sexuality</th>\n",
       "      <th>Ethnicity</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>SurveyLength</th>\n",
       "      <th>SurveyEase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>Easy</td>\n",
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       "      <td>Employed full-time</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>No</td>\n",
       "      <td>Some college/university study without earning ...</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>...</td>\n",
       "      <td>Just as welcome now as I felt last year</td>\n",
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       "      <td>White or of European descent</td>\n",
       "      <td>No</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Neither easy nor difficult</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Less than once a month but more than once per ...</td>\n",
       "      <td>OSS is, on average, of HIGHER quality than pro...</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>United States</td>\n",
       "      <td>No</td>\n",
       "      <td>Master’s degree (MA, MS, M.Eng., MBA, etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>...</td>\n",
       "      <td>Somewhat more welcome now than last year</td>\n",
       "      <td>Tech articles written by other developers;Cour...</td>\n",
       "      <td>28.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>White or of European descent</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Easy</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Never</td>\n",
       "      <td>The quality of OSS and closed source software ...</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>No</td>\n",
       "      <td>Master’s degree (MA, MS, M.Eng., MBA, etc.)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Just as welcome now as I felt last year</td>\n",
       "      <td>Tech articles written by other developers;Indu...</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>White or of European descent</td>\n",
       "      <td>No</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Neither easy nor difficult</td>\n",
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       "      <th>4</th>\n",
       "      <td>17</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Less than once a month but more than once per ...</td>\n",
       "      <td>The quality of OSS and closed source software ...</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Australia</td>\n",
       "      <td>No</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Computer science, computer engineering, or sof...</td>\n",
       "      <td>...</td>\n",
       "      <td>Just as welcome now as I felt last year</td>\n",
       "      <td>Tech articles written by other developers;Indu...</td>\n",
       "      <td>29.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>Hispanic or Latino/Latina;Multiracial</td>\n",
       "      <td>No</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Easy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>5 rows × 85 columns</p>\n",
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      "text/plain": [
       "   Respondent                      MainBranch Hobbyist  \\\n",
       "0           4  I am a developer by profession       No   \n",
       "1           9  I am a developer by profession      Yes   \n",
       "2          13  I am a developer by profession      Yes   \n",
       "3          16  I am a developer by profession      Yes   \n",
       "4          17  I am a developer by profession      Yes   \n",
       "\n",
       "                                         OpenSourcer  \\\n",
       "0                                              Never   \n",
       "1                         Once a month or more often   \n",
       "2  Less than once a month but more than once per ...   \n",
       "3                                              Never   \n",
       "4  Less than once a month but more than once per ...   \n",
       "\n",
       "                                          OpenSource          Employment  \\\n",
       "0  The quality of OSS and closed source software ...  Employed full-time   \n",
       "1  The quality of OSS and closed source software ...  Employed full-time   \n",
       "2  OSS is, on average, of HIGHER quality than pro...  Employed full-time   \n",
       "3  The quality of OSS and closed source software ...  Employed full-time   \n",
       "4  The quality of OSS and closed source software ...  Employed full-time   \n",
       "\n",
       "          Country Student                                            EdLevel  \\\n",
       "0   United States      No           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "1     New Zealand      No  Some college/university study without earning ...   \n",
       "2   United States      No        Master’s degree (MA, MS, M.Eng., MBA, etc.)   \n",
       "3  United Kingdom      No        Master’s degree (MA, MS, M.Eng., MBA, etc.)   \n",
       "4       Australia      No           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "\n",
       "                                      UndergradMajor  ...  \\\n",
       "0  Computer science, computer engineering, or sof...  ...   \n",
       "1  Computer science, computer engineering, or sof...  ...   \n",
       "2  Computer science, computer engineering, or sof...  ...   \n",
       "3                                                NaN  ...   \n",
       "4  Computer science, computer engineering, or sof...  ...   \n",
       "\n",
       "                              WelcomeChange  \\\n",
       "0   Just as welcome now as I felt last year   \n",
       "1   Just as welcome now as I felt last year   \n",
       "2  Somewhat more welcome now than last year   \n",
       "3   Just as welcome now as I felt last year   \n",
       "4   Just as welcome now as I felt last year   \n",
       "\n",
       "                                        SONewContent   Age Gender Trans  \\\n",
       "0  Tech articles written by other developers;Indu...  22.0    Man    No   \n",
       "1                                                NaN  23.0    Man    No   \n",
       "2  Tech articles written by other developers;Cour...  28.0    Man    No   \n",
       "3  Tech articles written by other developers;Indu...  26.0    Man    No   \n",
       "4  Tech articles written by other developers;Indu...  29.0    Man    No   \n",
       "\n",
       "                 Sexuality                              Ethnicity Dependents  \\\n",
       "0  Straight / Heterosexual           White or of European descent         No   \n",
       "1                 Bisexual           White or of European descent         No   \n",
       "2  Straight / Heterosexual           White or of European descent        Yes   \n",
       "3  Straight / Heterosexual           White or of European descent         No   \n",
       "4  Straight / Heterosexual  Hispanic or Latino/Latina;Multiracial         No   \n",
       "\n",
       "            SurveyLength                  SurveyEase  \n",
       "0  Appropriate in length                        Easy  \n",
       "1  Appropriate in length  Neither easy nor difficult  \n",
       "2  Appropriate in length                        Easy  \n",
       "3  Appropriate in length  Neither easy nor difficult  \n",
       "4  Appropriate in length                        Easy  \n",
       "\n",
       "[5 rows x 85 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# your code goes here\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Find out the number of rows and columns\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Start by exploring the numbers of rows and columns of data in the dataset.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print the number of rows in the dataset.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Rows: 11552\n"
     ]
    }
   ],
   "source": [
    "# your code goes here\n",
    "print(\"Number of Rows: {}\".format(df.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print the number of columns in the dataset.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Columns: 85\n"
     ]
    }
   ],
   "source": [
    "# your code goes here\n",
    "print(\"Number of Columns: {}\".format(df.shape[1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Identify the data types of each column\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Explore the dataset and identify the data types of each column.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print the datatype of all columns.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Column Datatype: Respondent                  int64\n",
      "MainBranch                 object\n",
      "Hobbyist                   object\n",
      "OpenSourcer                object\n",
      "OpenSource                 object\n",
      "Employment                 object\n",
      "Country                    object\n",
      "Student                    object\n",
      "EdLevel                    object\n",
      "UndergradMajor             object\n",
      "EduOther                   object\n",
      "OrgSize                    object\n",
      "DevType                    object\n",
      "YearsCode                  object\n",
      "Age1stCode                 object\n",
      "YearsCodePro               object\n",
      "CareerSat                  object\n",
      "JobSat                     object\n",
      "MgrIdiot                   object\n",
      "MgrMoney                   object\n",
      "MgrWant                    object\n",
      "JobSeek                    object\n",
      "LastHireDate               object\n",
      "LastInt                    object\n",
      "FizzBuzz                   object\n",
      "JobFactors                 object\n",
      "ResumeUpdate               object\n",
      "CurrencySymbol             object\n",
      "CurrencyDesc               object\n",
      "CompTotal                 float64\n",
      "CompFreq                   object\n",
      "ConvertedComp             float64\n",
      "WorkWeekHrs               float64\n",
      "WorkPlan                   object\n",
      "WorkChallenge              object\n",
      "WorkRemote                 object\n",
      "WorkLoc                    object\n",
      "ImpSyn                     object\n",
      "CodeRev                    object\n",
      "CodeRevHrs                float64\n",
      "UnitTests                  object\n",
      "PurchaseHow                object\n",
      "PurchaseWhat               object\n",
      "LanguageWorkedWith         object\n",
      "LanguageDesireNextYear     object\n",
      "DatabaseWorkedWith         object\n",
      "DatabaseDesireNextYear     object\n",
      "PlatformWorkedWith         object\n",
      "PlatformDesireNextYear     object\n",
      "WebFrameWorkedWith         object\n",
      "WebFrameDesireNextYear     object\n",
      "MiscTechWorkedWith         object\n",
      "MiscTechDesireNextYear     object\n",
      "DevEnviron                 object\n",
      "OpSys                      object\n",
      "Containers                 object\n",
      "BlockchainOrg              object\n",
      "BlockchainIs               object\n",
      "BetterLife                 object\n",
      "ITperson                   object\n",
      "OffOn                      object\n",
      "SocialMedia                object\n",
      "Extraversion               object\n",
      "ScreenName                 object\n",
      "SOVisit1st                 object\n",
      "SOVisitFreq                object\n",
      "SOVisitTo                  object\n",
      "SOFindAnswer               object\n",
      "SOTimeSaved                object\n",
      "SOHowMuchTime              object\n",
      "SOAccount                  object\n",
      "SOPartFreq                 object\n",
      "SOJobs                     object\n",
      "EntTeams                   object\n",
      "SOComm                     object\n",
      "WelcomeChange              object\n",
      "SONewContent               object\n",
      "Age                       float64\n",
      "Gender                     object\n",
      "Trans                      object\n",
      "Sexuality                  object\n",
      "Ethnicity                  object\n",
      "Dependents                 object\n",
      "SurveyLength               object\n",
      "SurveyEase                 object\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "# your code goes here\n",
    "with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n",
    "    print(\"Column Datatype: {}\".format(df.dtypes))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print the mean age of the survey participants.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean survey age is: 30.8\n"
     ]
    }
   ],
   "source": [
    "# your code goes here\n",
    "print(\"Mean survey age is: {}\".format(round(df[\"Age\"].mean(), 1)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset is the result of a world wide survey. Print how many unique countries are there in the Country column.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 135 unique countries.\n"
     ]
    }
   ],
   "source": [
    "# your code goes here\n",
    "print(\"There are {} unique countries.\".format(df[\"Country\"].nunique()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Authors\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ramesh Sannareddy\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Other Contributors\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rav Ahuja\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Change Log\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Date (YYYY-MM-DD) | Version | Changed By        | Change Description                 |\n",
    "| ----------------- | ------- | ----------------- | ---------------------------------- |\n",
    "| 2020-10-17        | 0.1     | Ramesh Sannareddy | Created initial version of the lab |\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Copyright © 2020 IBM Corporation. This notebook and its source code are released under the terms of the [MIT License](https://cognitiveclass.ai/mit-license?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDA0321ENSkillsNetwork21426264-2022-01-01&cm_mmc=Email_Newsletter-\\_-Developer_Ed%2BTech-\\_-WW_WW-\\_-SkillsNetwork-Courses-IBM-DA0321EN-SkillsNetwork-21426264&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ).\n"
   ]
  }
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