stack-overflow-2019-developer-survey-analysis.ipynb

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    "# DevReport Analysis\n",
    "\n",
    "Technology is changing on rapid scale, and stackoverflow is the most important part of the development workflow, and to understand the dev likings stack overflow does annual survey with the aim to know what's trending in the Software Developer Space.\n",
    "\n",
    "This Notebook consist of analysis on Stack Overflow dataset 2019, I have tried to formulate some question while looking at the dataset.\n",
    "\n",
    "This Notebook is made for anyone who is starting up in the field data analysis, and need some familiar dataset to which they can relate with,\n",
    "***All the clearning and visualization is done in the process of solving the questions***\n",
    "\n",
    "If you feel like this notebook helps in anyway do **Upvote (^)** it, and if their is any suggestion do use the comment section\n",
    "\n",
    "Now lets start with the analysis\n"
   ]
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   "source": [
    "For this analysis we will use most commonly used Python library \n",
    "1. **Numpy**: Numpy is used for mathematical computation with Python learn more at: {[Numpy docs](http://https://numpy.org/doc/stable/user/quickstart.html)}\n",
    "and \n",
    "2. **Pandas**: Pandas is mainly used for Data Manipulation and Visualizaiton with Python, learn more at: {[Pandas docs](https://pandas.pydata.org/docs/user_guide/index.html)}"
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   "source": [
    "# Importing Libraries\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
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   "source": [
    "# loading dataset\n",
    "df = pd.read_csv(\"../input/stack-overflow-developer-survey-results-2019/survey_results_public.csv\")"
   ]
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <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",
       "      <th>WelcomeChange</th>\n",
       "      <th>SONewContent</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <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",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>I am a student who is learning to code</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Never</td>\n",
       "      <td>The quality of OSS and closed source software ...</td>\n",
       "      <td>Not employed, and not looking for work</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>No</td>\n",
       "      <td>Primary/elementary school</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>14.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Neither easy nor difficult</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>I am a student who is learning to code</td>\n",
       "      <td>No</td>\n",
       "      <td>Less than once per year</td>\n",
       "      <td>The quality of OSS and closed source software ...</td>\n",
       "      <td>Not employed, but looking for work</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>Yes, full-time</td>\n",
       "      <td>Secondary school (e.g. American high school, G...</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>19.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Neither easy nor difficult</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>I am not primarily a developer, but I write co...</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>Thailand</td>\n",
       "      <td>No</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Web development or web design</td>\n",
       "      <td>...</td>\n",
       "      <td>Just as welcome now as I felt last year</td>\n",
       "      <td>Tech meetups or events in your area;Courses on...</td>\n",
       "      <td>28.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Neither easy nor difficult</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>No</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 States</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>22.0</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>Easy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Once a month or more often</td>\n",
       "      <td>OSS is, on average, of HIGHER quality than pro...</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Ukraine</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 meetups or events in your area;Courses on...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>White or of European descent;Multiracial</td>\n",
       "      <td>No</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Easy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 85 columns</p>\n",
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      "text/plain": [
       "   Respondent                                         MainBranch Hobbyist  \\\n",
       "0           1             I am a student who is learning to code      Yes   \n",
       "1           2             I am a student who is learning to code       No   \n",
       "2           3  I am not primarily a developer, but I write co...      Yes   \n",
       "3           4                     I am a developer by profession       No   \n",
       "4           5                     I am a developer by profession      Yes   \n",
       "\n",
       "                  OpenSourcer  \\\n",
       "0                       Never   \n",
       "1     Less than once per year   \n",
       "2                       Never   \n",
       "3                       Never   \n",
       "4  Once a month or more often   \n",
       "\n",
       "                                          OpenSource  \\\n",
       "0  The quality of OSS and closed source software ...   \n",
       "1  The quality of OSS and closed source software ...   \n",
       "2  The quality of OSS and closed source software ...   \n",
       "3  The quality of OSS and closed source software ...   \n",
       "4  OSS is, on average, of HIGHER quality than pro...   \n",
       "\n",
       "                               Employment                 Country  \\\n",
       "0  Not employed, and not looking for work          United Kingdom   \n",
       "1      Not employed, but looking for work  Bosnia and Herzegovina   \n",
       "2                      Employed full-time                Thailand   \n",
       "3                      Employed full-time           United States   \n",
       "4                      Employed full-time                 Ukraine   \n",
       "\n",
       "          Student                                            EdLevel  \\\n",
       "0              No                          Primary/elementary school   \n",
       "1  Yes, full-time  Secondary school (e.g. American high school, G...   \n",
       "2              No           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "3              No           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "4              No           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "\n",
       "                                      UndergradMajor  ...  \\\n",
       "0                                                NaN  ...   \n",
       "1                                                NaN  ...   \n",
       "2                      Web development or web design  ...   \n",
       "3  Computer science, computer engineering, or sof...  ...   \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  Just as welcome now as I felt 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...  14.0    Man    No   \n",
       "1  Tech articles written by other developers;Indu...  19.0    Man    No   \n",
       "2  Tech meetups or events in your area;Courses on...  28.0    Man    No   \n",
       "3  Tech articles written by other developers;Indu...  22.0    Man    No   \n",
       "4  Tech meetups or events in your area;Courses on...  30.0    Man    No   \n",
       "\n",
       "                 Sexuality                                 Ethnicity  \\\n",
       "0  Straight / Heterosexual                                       NaN   \n",
       "1  Straight / Heterosexual                                       NaN   \n",
       "2  Straight / Heterosexual                                       NaN   \n",
       "3  Straight / Heterosexual              White or of European descent   \n",
       "4  Straight / Heterosexual  White or of European descent;Multiracial   \n",
       "\n",
       "  Dependents           SurveyLength                  SurveyEase  \n",
       "0         No  Appropriate in length  Neither easy nor difficult  \n",
       "1         No  Appropriate in length  Neither easy nor difficult  \n",
       "2        Yes  Appropriate in length  Neither easy nor difficult  \n",
       "3         No  Appropriate in length                        Easy  \n",
       "4         No  Appropriate in length                        Easy  \n",
       "\n",
       "[5 rows x 85 columns]"
      ]
     },
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   ],
   "source": [
    "df.head(5)"
   ]
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      "text/plain": [
       "Index(['Respondent', 'MainBranch', 'Hobbyist', 'OpenSourcer', 'OpenSource',\n",
       "       'Employment', 'Country', 'Student', 'EdLevel', 'UndergradMajor',\n",
       "       'EduOther', 'OrgSize', 'DevType', 'YearsCode', 'Age1stCode',\n",
       "       'YearsCodePro', 'CareerSat', 'JobSat', 'MgrIdiot', 'MgrMoney',\n",
       "       'MgrWant', 'JobSeek', 'LastHireDate', 'LastInt', 'FizzBuzz',\n",
       "       'JobFactors', 'ResumeUpdate', 'CurrencySymbol', 'CurrencyDesc',\n",
       "       'CompTotal', 'CompFreq', 'ConvertedComp', 'WorkWeekHrs', 'WorkPlan',\n",
       "       'WorkChallenge', 'WorkRemote', 'WorkLoc', 'ImpSyn', 'CodeRev',\n",
       "       'CodeRevHrs', 'UnitTests', 'PurchaseHow', 'PurchaseWhat',\n",
       "       'LanguageWorkedWith', 'LanguageDesireNextYear', 'DatabaseWorkedWith',\n",
       "       'DatabaseDesireNextYear', 'PlatformWorkedWith',\n",
       "       'PlatformDesireNextYear', 'WebFrameWorkedWith',\n",
       "       'WebFrameDesireNextYear', 'MiscTechWorkedWith',\n",
       "       'MiscTechDesireNextYear', 'DevEnviron', 'OpSys', 'Containers',\n",
       "       'BlockchainOrg', 'BlockchainIs', 'BetterLife', 'ITperson', 'OffOn',\n",
       "       'SocialMedia', 'Extraversion', 'ScreenName', 'SOVisit1st',\n",
       "       'SOVisitFreq', 'SOVisitTo', 'SOFindAnswer', 'SOTimeSaved',\n",
       "       'SOHowMuchTime', 'SOAccount', 'SOPartFreq', 'SOJobs', 'EntTeams',\n",
       "       'SOComm', 'WelcomeChange', 'SONewContent', 'Age', 'Gender', 'Trans',\n",
       "       'Sexuality', 'Ethnicity', 'Dependents', 'SurveyLength', 'SurveyEase'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
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    }
   ],
   "source": [
    "df.columns"
   ]
  },
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   "source": [
    "The Most Important part of data analysis is:\n",
    "1. Understanding the data {what data is all about}\n",
    "2. Drawing Patterns while going through data columns\n",
    "3. Formulate question {like what are the things that can be extracted from the dataset}\n",
    "\n",
    "Below are the some question that I have formulated:"
   ]
  },
  {
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    "tags": []
   },
   "source": [
    "## What is the average age of developers when they wrote their first line of code?"
   ]
  },
  {
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    {
     "data": {
      "text/plain": [
       "0         10\n",
       "1         17\n",
       "2         22\n",
       "3         16\n",
       "4         14\n",
       "        ... \n",
       "88878    NaN\n",
       "88879    NaN\n",
       "88880    NaN\n",
       "88881    NaN\n",
       "88882     11\n",
       "Name: Age1stCode, Length: 88883, dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
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    }
   ],
   "source": [
    "#display the columns {Age1stCode}\n",
    "df['Age1stCode']"
   ]
  },
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    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 6,
     "metadata": {},
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   ],
   "source": [
    "#check the datatype of the columns values\n",
    "type(df['Age1stCode'][0])"
   ]
  },
  {
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     "start_time": "2020-11-17T14:46:24.154901",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#as we are supposed to find the average, so convert the values into the numeric format\n",
    "\n",
    "df['Age1stCode'] = pd.to_numeric(df['Age1stCode'], errors = 'coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:24.494364Z",
     "iopub.status.busy": "2020-11-17T14:46:24.493281Z",
     "iopub.status.idle": "2020-11-17T14:46:24.498089Z",
     "shell.execute_reply": "2020-11-17T14:46:24.497204Z"
    },
    "id": "1KTx14PlbuQj",
    "outputId": "38d13e15-d711-486c-e7a4-b8169a1f883f",
    "papermill": {
     "duration": 0.054282,
     "end_time": "2020-11-17T14:46:24.498227",
     "exception": false,
     "start_time": "2020-11-17T14:46:24.443945",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df['Age1stCode'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:24.593759Z",
     "iopub.status.busy": "2020-11-17T14:46:24.592820Z",
     "iopub.status.idle": "2020-11-17T14:46:24.596523Z",
     "shell.execute_reply": "2020-11-17T14:46:24.597139Z"
    },
    "id": "xFv_qAmtb0sV",
    "outputId": "f1909332-74e3-48dd-f7b2-16f6380cb2d8",
    "papermill": {
     "duration": 0.053994,
     "end_time": "2020-11-17T14:46:24.597298",
     "exception": false,
     "start_time": "2020-11-17T14:46:24.543304",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "avg_age = int(df['Age1stCode'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:24.692551Z",
     "iopub.status.busy": "2020-11-17T14:46:24.691488Z",
     "iopub.status.idle": "2020-11-17T14:46:24.696071Z",
     "shell.execute_reply": "2020-11-17T14:46:24.695454Z"
    },
    "papermill": {
     "duration": 0.054253,
     "end_time": "2020-11-17T14:46:24.696205",
     "exception": false,
     "start_time": "2020-11-17T14:46:24.641952",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The average age of developers when they write their first line of code is:  15\n"
     ]
    }
   ],
   "source": [
    "print (\"The average age of developers when they write their first line of code is: \", avg_age)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "h3Rkro8KcLwm",
    "papermill": {
     "duration": 0.044082,
     "end_time": "2020-11-17T14:46:24.785317",
     "exception": false,
     "start_time": "2020-11-17T14:46:24.741235",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## What is the percentage of developers who know python in each country?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:24.884367Z",
     "iopub.status.busy": "2020-11-17T14:46:24.883172Z",
     "iopub.status.idle": "2020-11-17T14:46:24.887686Z",
     "shell.execute_reply": "2020-11-17T14:46:24.888234Z"
    },
    "papermill": {
     "duration": 0.058465,
     "end_time": "2020-11-17T14:46:24.888397",
     "exception": false,
     "start_time": "2020-11-17T14:46:24.829932",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                          HTML/CSS;Java;JavaScript;Python\n",
       "1                                      C++;HTML/CSS;Python\n",
       "2                                                 HTML/CSS\n",
       "3                                      C;C++;C#;Python;SQL\n",
       "4              C++;HTML/CSS;Java;JavaScript;Python;SQL;VBA\n",
       "                               ...                        \n",
       "88878                        HTML/CSS;JavaScript;Other(s):\n",
       "88879                                                  NaN\n",
       "88880                                                  NaN\n",
       "88881                                                  NaN\n",
       "88882    Bash/Shell/PowerShell;HTML/CSS;Java;JavaScript...\n",
       "Name: LanguageWorkedWith, Length: 88883, dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['LanguageWorkedWith']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:24.997035Z",
     "iopub.status.busy": "2020-11-17T14:46:24.996243Z",
     "iopub.status.idle": "2020-11-17T14:46:25.659914Z",
     "shell.execute_reply": "2020-11-17T14:46:25.659256Z"
    },
    "id": "YsyhV1gIcLGJ",
    "papermill": {
     "duration": 0.724628,
     "end_time": "2020-11-17T14:46:25.660052",
     "exception": false,
     "start_time": "2020-11-17T14:46:24.935424",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#we have multiple values in the same cell, so we will split the values\n",
    "\n",
    "new = df['LanguageWorkedWith'].str.split(\";\", expand = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:25.758137Z",
     "iopub.status.busy": "2020-11-17T14:46:25.757353Z",
     "iopub.status.idle": "2020-11-17T14:46:25.840850Z",
     "shell.execute_reply": "2020-11-17T14:46:25.840063Z"
    },
    "id": "qyT2Yufkda-8",
    "papermill": {
     "duration": 0.134402,
     "end_time": "2020-11-17T14:46:25.840978",
     "exception": false,
     "start_time": "2020-11-17T14:46:25.706576",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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       "      <td>HTML/CSS</td>\n",
       "      <td>JavaScript</td>\n",
       "      <td>Other(s):</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <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>88880</th>\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",
       "      <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",
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       "      <th>88881</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
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       "    <tr>\n",
       "      <th>88882</th>\n",
       "      <td>Bash/Shell/PowerShell</td>\n",
       "      <td>HTML/CSS</td>\n",
       "      <td>Java</td>\n",
       "      <td>JavaScript</td>\n",
       "      <td>PHP</td>\n",
       "      <td>SQL</td>\n",
       "      <td>Swift</td>\n",
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       "      <td>None</td>\n",
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       "      <td>None</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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       "                          0           1           2           3       4   \\\n",
       "0                   HTML/CSS        Java  JavaScript      Python    None   \n",
       "1                        C++    HTML/CSS      Python        None    None   \n",
       "2                   HTML/CSS        None        None        None    None   \n",
       "3                          C         C++          C#      Python     SQL   \n",
       "4                        C++    HTML/CSS        Java  JavaScript  Python   \n",
       "...                      ...         ...         ...         ...     ...   \n",
       "88878               HTML/CSS  JavaScript   Other(s):        None    None   \n",
       "88879                    NaN         NaN         NaN         NaN     NaN   \n",
       "88880                    NaN         NaN         NaN         NaN     NaN   \n",
       "88881                    NaN         NaN         NaN         NaN     NaN   \n",
       "88882  Bash/Shell/PowerShell    HTML/CSS        Java  JavaScript     PHP   \n",
       "\n",
       "         5      6     7     8     9   ...    18    19    20    21    22    23  \\\n",
       "0      None   None  None  None  None  ...  None  None  None  None  None  None   \n",
       "1      None   None  None  None  None  ...  None  None  None  None  None  None   \n",
       "2      None   None  None  None  None  ...  None  None  None  None  None  None   \n",
       "3      None   None  None  None  None  ...  None  None  None  None  None  None   \n",
       "4       SQL    VBA  None  None  None  ...  None  None  None  None  None  None   \n",
       "...     ...    ...   ...   ...   ...  ...   ...   ...   ...   ...   ...   ...   \n",
       "88878  None   None  None  None  None  ...  None  None  None  None  None  None   \n",
       "88879   NaN    NaN   NaN   NaN   NaN  ...   NaN   NaN   NaN   NaN   NaN   NaN   \n",
       "88880   NaN    NaN   NaN   NaN   NaN  ...   NaN   NaN   NaN   NaN   NaN   NaN   \n",
       "88881   NaN    NaN   NaN   NaN   NaN  ...   NaN   NaN   NaN   NaN   NaN   NaN   \n",
       "88882   SQL  Swift  None  None  None  ...  None  None  None  None  None  None   \n",
       "\n",
       "         24    25    26    27  \n",
       "0      None  None  None  None  \n",
       "1      None  None  None  None  \n",
       "2      None  None  None  None  \n",
       "3      None  None  None  None  \n",
       "4      None  None  None  None  \n",
       "...     ...   ...   ...   ...  \n",
       "88878  None  None  None  None  \n",
       "88879   NaN   NaN   NaN   NaN  \n",
       "88880   NaN   NaN   NaN   NaN  \n",
       "88881   NaN   NaN   NaN   NaN  \n",
       "88882  None  None  None  None  \n",
       "\n",
       "[88883 rows x 28 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
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    "new"
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   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:25.980455Z",
     "iopub.status.busy": "2020-11-17T14:46:25.975281Z",
     "iopub.status.idle": "2020-11-17T14:46:31.951459Z",
     "shell.execute_reply": "2020-11-17T14:46:31.952062Z"
    },
    "id": "UwUISo49d9r-",
    "papermill": {
     "duration": 6.064935,
     "end_time": "2020-11-17T14:46:31.952243",
     "exception": false,
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     "status": "completed"
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    "tags": []
   },
   "outputs": [],
   "source": [
    "#We are looking of people with python as a language by country\n",
    "\n",
    "#transpose\n",
    "\n",
    "new_t = new.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:32.138890Z",
     "iopub.status.busy": "2020-11-17T14:46:32.137745Z",
     "iopub.status.idle": "2020-11-17T14:46:32.145042Z",
     "shell.execute_reply": "2020-11-17T14:46:32.144400Z"
    },
    "id": "NlRjsOVpeBCQ",
    "papermill": {
     "duration": 0.113859,
     "end_time": "2020-11-17T14:46:32.145173",
     "exception": false,
     "start_time": "2020-11-17T14:46:32.031314",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>28 rows × 88883 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         0         1         2       3           4     5           6      \\\n",
       "0     HTML/CSS       C++  HTML/CSS       C         C++  Java    HTML/CSS   \n",
       "1         Java  HTML/CSS      None     C++    HTML/CSS     R  JavaScript   \n",
       "2   JavaScript    Python      None      C#        Java   SQL        None   \n",
       "3       Python      None      None  Python  JavaScript  None        None   \n",
       "4         None      None      None     SQL      Python  None        None   \n",
       "5         None      None      None    None         SQL  None        None   \n",
       "6         None      None      None    None         VBA  None        None   \n",
       "7         None      None      None    None        None  None        None   \n",
       "8         None      None      None    None        None  None        None   \n",
       "9         None      None      None    None        None  None        None   \n",
       "10        None      None      None    None        None  None        None   \n",
       "11        None      None      None    None        None  None        None   \n",
       "12        None      None      None    None        None  None        None   \n",
       "13        None      None      None    None        None  None        None   \n",
       "14        None      None      None    None        None  None        None   \n",
       "15        None      None      None    None        None  None        None   \n",
       "16        None      None      None    None        None  None        None   \n",
       "17        None      None      None    None        None  None        None   \n",
       "18        None      None      None    None        None  None        None   \n",
       "19        None      None      None    None        None  None        None   \n",
       "20        None      None      None    None        None  None        None   \n",
       "21        None      None      None    None        None  None        None   \n",
       "22        None      None      None    None        None  None        None   \n",
       "23        None      None      None    None        None  None        None   \n",
       "24        None      None      None    None        None  None        None   \n",
       "25        None      None      None    None        None  None        None   \n",
       "26        None      None      None    None        None  None        None   \n",
       "27        None      None      None    None        None  None        None   \n",
       "\n",
       "                    7                      8           9      ... 88873 88874  \\\n",
       "0   Bash/Shell/PowerShell  Bash/Shell/PowerShell          C#  ...   NaN   NaN   \n",
       "1                       C                     C#          Go  ...   NaN   NaN   \n",
       "2                     C++               HTML/CSS  JavaScript  ...   NaN   NaN   \n",
       "3                HTML/CSS             JavaScript      Python  ...   NaN   NaN   \n",
       "4                    Java                 Python           R  ...   NaN   NaN   \n",
       "5              JavaScript                   Ruby         SQL  ...   NaN   NaN   \n",
       "6                  Python                   Rust        None  ...   NaN   NaN   \n",
       "7                     SQL                    SQL        None  ...   NaN   NaN   \n",
       "8                    None             TypeScript        None  ...   NaN   NaN   \n",
       "9                    None            WebAssembly        None  ...   NaN   NaN   \n",
       "10                   None              Other(s):        None  ...   NaN   NaN   \n",
       "11                   None                   None        None  ...   NaN   NaN   \n",
       "12                   None                   None        None  ...   NaN   NaN   \n",
       "13                   None                   None        None  ...   NaN   NaN   \n",
       "14                   None                   None        None  ...   NaN   NaN   \n",
       "15                   None                   None        None  ...   NaN   NaN   \n",
       "16                   None                   None        None  ...   NaN   NaN   \n",
       "17                   None                   None        None  ...   NaN   NaN   \n",
       "18                   None                   None        None  ...   NaN   NaN   \n",
       "19                   None                   None        None  ...   NaN   NaN   \n",
       "20                   None                   None        None  ...   NaN   NaN   \n",
       "21                   None                   None        None  ...   NaN   NaN   \n",
       "22                   None                   None        None  ...   NaN   NaN   \n",
       "23                   None                   None        None  ...   NaN   NaN   \n",
       "24                   None                   None        None  ...   NaN   NaN   \n",
       "25                   None                   None        None  ...   NaN   NaN   \n",
       "26                   None                   None        None  ...   NaN   NaN   \n",
       "27                   None                   None        None  ...   NaN   NaN   \n",
       "\n",
       "         88875       88876                  88877       88878 88879 88880  \\\n",
       "0     HTML/CSS    HTML/CSS  Bash/Shell/PowerShell    HTML/CSS   NaN   NaN   \n",
       "1         Java  JavaScript                     Go  JavaScript   NaN   NaN   \n",
       "2   JavaScript      Python               HTML/CSS   Other(s):   NaN   NaN   \n",
       "3         None        None             JavaScript        None   NaN   NaN   \n",
       "4         None        None            WebAssembly        None   NaN   NaN   \n",
       "5         None        None                   None        None   NaN   NaN   \n",
       "6         None        None                   None        None   NaN   NaN   \n",
       "7         None        None                   None        None   NaN   NaN   \n",
       "8         None        None                   None        None   NaN   NaN   \n",
       "9         None        None                   None        None   NaN   NaN   \n",
       "10        None        None                   None        None   NaN   NaN   \n",
       "11        None        None                   None        None   NaN   NaN   \n",
       "12        None        None                   None        None   NaN   NaN   \n",
       "13        None        None                   None        None   NaN   NaN   \n",
       "14        None        None                   None        None   NaN   NaN   \n",
       "15        None        None                   None        None   NaN   NaN   \n",
       "16        None        None                   None        None   NaN   NaN   \n",
       "17        None        None                   None        None   NaN   NaN   \n",
       "18        None        None                   None        None   NaN   NaN   \n",
       "19        None        None                   None        None   NaN   NaN   \n",
       "20        None        None                   None        None   NaN   NaN   \n",
       "21        None        None                   None        None   NaN   NaN   \n",
       "22        None        None                   None        None   NaN   NaN   \n",
       "23        None        None                   None        None   NaN   NaN   \n",
       "24        None        None                   None        None   NaN   NaN   \n",
       "25        None        None                   None        None   NaN   NaN   \n",
       "26        None        None                   None        None   NaN   NaN   \n",
       "27        None        None                   None        None   NaN   NaN   \n",
       "\n",
       "   88881                  88882  \n",
       "0    NaN  Bash/Shell/PowerShell  \n",
       "1    NaN               HTML/CSS  \n",
       "2    NaN                   Java  \n",
       "3    NaN             JavaScript  \n",
       "4    NaN                    PHP  \n",
       "5    NaN                    SQL  \n",
       "6    NaN                  Swift  \n",
       "7    NaN                   None  \n",
       "8    NaN                   None  \n",
       "9    NaN                   None  \n",
       "10   NaN                   None  \n",
       "11   NaN                   None  \n",
       "12   NaN                   None  \n",
       "13   NaN                   None  \n",
       "14   NaN                   None  \n",
       "15   NaN                   None  \n",
       "16   NaN                   None  \n",
       "17   NaN                   None  \n",
       "18   NaN                   None  \n",
       "19   NaN                   None  \n",
       "20   NaN                   None  \n",
       "21   NaN                   None  \n",
       "22   NaN                   None  \n",
       "23   NaN                   None  \n",
       "24   NaN                   None  \n",
       "25   NaN                   None  \n",
       "26   NaN                   None  \n",
       "27   NaN                   None  \n",
       "\n",
       "[28 rows x 88883 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:32.252987Z",
     "iopub.status.busy": "2020-11-17T14:46:32.252116Z",
     "iopub.status.idle": "2020-11-17T14:46:32.255468Z",
     "shell.execute_reply": "2020-11-17T14:46:32.256027Z"
    },
    "id": "NWISFKaneL10",
    "papermill": {
     "duration": 0.061034,
     "end_time": "2020-11-17T14:46:32.256192",
     "exception": false,
     "start_time": "2020-11-17T14:46:32.195158",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "count = new.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:32.366577Z",
     "iopub.status.busy": "2020-11-17T14:46:32.363347Z",
     "iopub.status.idle": "2020-11-17T14:46:32.370328Z",
     "shell.execute_reply": "2020-11-17T14:46:32.371035Z"
    },
    "id": "eVFqw_ngeL9H",
    "papermill": {
     "duration": 0.064051,
     "end_time": "2020-11-17T14:46:32.371224",
     "exception": false,
     "start_time": "2020-11-17T14:46:32.307173",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#adding a new columns with name 'if_python' and will apply the value 0 with it\n",
    "df['is_python'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:32.484249Z",
     "iopub.status.busy": "2020-11-17T14:46:32.482789Z",
     "iopub.status.idle": "2020-11-17T14:46:32.489650Z",
     "shell.execute_reply": "2020-11-17T14:46:32.488986Z"
    },
    "id": "rq-QgOukeL71",
    "papermill": {
     "duration": 0.067793,
     "end_time": "2020-11-17T14:46:32.489794",
     "exception": false,
     "start_time": "2020-11-17T14:46:32.422001",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        0\n",
       "1        0\n",
       "2        0\n",
       "3        0\n",
       "4        0\n",
       "        ..\n",
       "88878    0\n",
       "88879    0\n",
       "88880    0\n",
       "88881    0\n",
       "88882    0\n",
       "Name: is_python, Length: 88883, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['is_python']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:32.609509Z",
     "iopub.status.busy": "2020-11-17T14:46:32.608231Z",
     "iopub.status.idle": "2020-11-17T14:46:46.601906Z",
     "shell.execute_reply": "2020-11-17T14:46:46.602490Z"
    },
    "id": "pMbeZ2fyeL49",
    "papermill": {
     "duration": 14.057065,
     "end_time": "2020-11-17T14:46:46.602679",
     "exception": false,
     "start_time": "2020-11-17T14:46:32.545614",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "for i in range(0,count):\n",
    "    if 'Python' in new_t[i].unique():\n",
    "        df.at[i, 'is_python'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:46.740111Z",
     "iopub.status.busy": "2020-11-17T14:46:46.739028Z",
     "iopub.status.idle": "2020-11-17T14:46:46.746050Z",
     "shell.execute_reply": "2020-11-17T14:46:46.745406Z"
    },
    "id": "Rh8qlVJrg1EA",
    "papermill": {
     "duration": 0.093714,
     "end_time": "2020-11-17T14:46:46.746182",
     "exception": false,
     "start_time": "2020-11-17T14:46:46.652468",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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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",
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       "      <th>EdLevel</th>\n",
       "      <th>UndergradMajor</th>\n",
       "      <th>...</th>\n",
       "      <th>SONewContent</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Trans</th>\n",
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       "      <th>Ethnicity</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>SurveyLength</th>\n",
       "      <th>SurveyEase</th>\n",
       "      <th>is_python</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>1</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Tech articles written by other developers;Indu...</td>\n",
       "      <td>14.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Neither easy nor difficult</td>\n",
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       "      <th>1</th>\n",
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       "      <td>I am a student who is learning to code</td>\n",
       "      <td>No</td>\n",
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       "      <td>The quality of OSS and closed source software ...</td>\n",
       "      <td>Not employed, but looking for work</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>Yes, full-time</td>\n",
       "      <td>Secondary school (e.g. American high school, G...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Tech articles written by other developers;Indu...</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>NaN</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>3</td>\n",
       "      <td>I am not primarily a developer, but I write co...</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>Thailand</td>\n",
       "      <td>No</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Web development or web design</td>\n",
       "      <td>...</td>\n",
       "      <td>Tech meetups or events in your area;Courses on...</td>\n",
       "      <td>28.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Neither easy nor difficult</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>No</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 States</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>Tech articles written by other developers;Indu...</td>\n",
       "      <td>22.0</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>Easy</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Once a month or more often</td>\n",
       "      <td>OSS is, on average, of HIGHER quality than pro...</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Ukraine</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>Tech meetups or events in your area;Courses on...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>White or of European descent;Multiracial</td>\n",
       "      <td>No</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Easy</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>I am not primarily a developer, but I write co...</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>Canada</td>\n",
       "      <td>No</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Mathematics or statistics</td>\n",
       "      <td>...</td>\n",
       "      <td>Tech articles written by other developers;Indu...</td>\n",
       "      <td>28.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>East Asian</td>\n",
       "      <td>No</td>\n",
       "      <td>Too long</td>\n",
       "      <td>Neither easy nor difficult</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>No</td>\n",
       "      <td>Never</td>\n",
       "      <td>The quality of OSS and closed source software ...</td>\n",
       "      <td>Independent contractor, freelancer, or self-em...</td>\n",
       "      <td>Ukraine</td>\n",
       "      <td>No</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Another engineering discipline (ex. civil, ele...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.0</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>Neither easy nor difficult</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>I code primarily as a hobby</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Less than once per year</td>\n",
       "      <td>OSS is, on average, of HIGHER quality than pro...</td>\n",
       "      <td>Not employed, but looking for work</td>\n",
       "      <td>India</td>\n",
       "      <td>NaN</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>Tech articles written by other developers;Indu...</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Neither easy nor difficult</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Once a month or more often</td>\n",
       "      <td>The quality of OSS and closed source software ...</td>\n",
       "      <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>NaN</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Bisexual</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",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Once a month or more often</td>\n",
       "      <td>OSS is, on average, of HIGHER quality than pro...</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>India</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>Tech articles written by other developers;Tech...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Too long</td>\n",
       "      <td>Difficult</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 86 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Respondent                                         MainBranch Hobbyist  \\\n",
       "0           1             I am a student who is learning to code      Yes   \n",
       "1           2             I am a student who is learning to code       No   \n",
       "2           3  I am not primarily a developer, but I write co...      Yes   \n",
       "3           4                     I am a developer by profession       No   \n",
       "4           5                     I am a developer by profession      Yes   \n",
       "5           6  I am not primarily a developer, but I write co...      Yes   \n",
       "6           7                     I am a developer by profession       No   \n",
       "7           8                        I code primarily as a hobby      Yes   \n",
       "8           9                     I am a developer by profession      Yes   \n",
       "9          10                     I am a developer by profession      Yes   \n",
       "\n",
       "                  OpenSourcer  \\\n",
       "0                       Never   \n",
       "1     Less than once per year   \n",
       "2                       Never   \n",
       "3                       Never   \n",
       "4  Once a month or more often   \n",
       "5                       Never   \n",
       "6                       Never   \n",
       "7     Less than once per year   \n",
       "8  Once a month or more often   \n",
       "9  Once a month or more often   \n",
       "\n",
       "                                          OpenSource  \\\n",
       "0  The quality of OSS and closed source software ...   \n",
       "1  The quality of OSS and closed source software ...   \n",
       "2  The quality of OSS and closed source software ...   \n",
       "3  The quality of OSS and closed source software ...   \n",
       "4  OSS is, on average, of HIGHER quality than pro...   \n",
       "5  The quality of OSS and closed source software ...   \n",
       "6  The quality of OSS and closed source software ...   \n",
       "7  OSS is, on average, of HIGHER quality than pro...   \n",
       "8  The quality of OSS and closed source software ...   \n",
       "9  OSS is, on average, of HIGHER quality than pro...   \n",
       "\n",
       "                                          Employment                 Country  \\\n",
       "0             Not employed, and not looking for work          United Kingdom   \n",
       "1                 Not employed, but looking for work  Bosnia and Herzegovina   \n",
       "2                                 Employed full-time                Thailand   \n",
       "3                                 Employed full-time           United States   \n",
       "4                                 Employed full-time                 Ukraine   \n",
       "5                                 Employed full-time                  Canada   \n",
       "6  Independent contractor, freelancer, or self-em...                 Ukraine   \n",
       "7                 Not employed, but looking for work                   India   \n",
       "8                                 Employed full-time             New Zealand   \n",
       "9                                 Employed full-time                   India   \n",
       "\n",
       "          Student                                            EdLevel  \\\n",
       "0              No                          Primary/elementary school   \n",
       "1  Yes, full-time  Secondary school (e.g. American high school, G...   \n",
       "2              No           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "3              No           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "4              No           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "5              No           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "6              No           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "7             NaN           Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "8              No  Some college/university study without earning ...   \n",
       "9              No        Master’s degree (MA, MS, M.Eng., MBA, etc.)   \n",
       "\n",
       "                                      UndergradMajor  ...  \\\n",
       "0                                                NaN  ...   \n",
       "1                                                NaN  ...   \n",
       "2                      Web development or web design  ...   \n",
       "3  Computer science, computer engineering, or sof...  ...   \n",
       "4  Computer science, computer engineering, or sof...  ...   \n",
       "5                          Mathematics or statistics  ...   \n",
       "6  Another engineering discipline (ex. civil, ele...  ...   \n",
       "7  Computer science, computer engineering, or sof...  ...   \n",
       "8  Computer science, computer engineering, or sof...  ...   \n",
       "9                                                NaN  ...   \n",
       "\n",
       "                                        SONewContent   Age Gender Trans  \\\n",
       "0  Tech articles written by other developers;Indu...  14.0    Man    No   \n",
       "1  Tech articles written by other developers;Indu...  19.0    Man    No   \n",
       "2  Tech meetups or events in your area;Courses on...  28.0    Man    No   \n",
       "3  Tech articles written by other developers;Indu...  22.0    Man    No   \n",
       "4  Tech meetups or events in your area;Courses on...  30.0    Man    No   \n",
       "5  Tech articles written by other developers;Indu...  28.0    Man    No   \n",
       "6                                                NaN  42.0    Man    No   \n",
       "7  Tech articles written by other developers;Indu...  24.0    Man    No   \n",
       "8                                                NaN  23.0    Man    No   \n",
       "9  Tech articles written by other developers;Tech...   NaN    NaN   NaN   \n",
       "\n",
       "                 Sexuality                                 Ethnicity  \\\n",
       "0  Straight / Heterosexual                                       NaN   \n",
       "1  Straight / Heterosexual                                       NaN   \n",
       "2  Straight / Heterosexual                                       NaN   \n",
       "3  Straight / Heterosexual              White or of European descent   \n",
       "4  Straight / Heterosexual  White or of European descent;Multiracial   \n",
       "5  Straight / Heterosexual                                East Asian   \n",
       "6  Straight / Heterosexual              White or of European descent   \n",
       "7  Straight / Heterosexual                                       NaN   \n",
       "8                 Bisexual              White or of European descent   \n",
       "9                      NaN                                       NaN   \n",
       "\n",
       "  Dependents           SurveyLength                  SurveyEase is_python  \n",
       "0         No  Appropriate in length  Neither easy nor difficult         1  \n",
       "1         No  Appropriate in length  Neither easy nor difficult         1  \n",
       "2        Yes  Appropriate in length  Neither easy nor difficult         0  \n",
       "3         No  Appropriate in length                        Easy         1  \n",
       "4         No  Appropriate in length                        Easy         1  \n",
       "5         No               Too long  Neither easy nor difficult         0  \n",
       "6        Yes  Appropriate in length  Neither easy nor difficult         0  \n",
       "7        NaN  Appropriate in length  Neither easy nor difficult         1  \n",
       "8         No  Appropriate in length  Neither easy nor difficult         1  \n",
       "9        Yes               Too long                   Difficult         1  \n",
       "\n",
       "[10 rows x 86 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:46.856748Z",
     "iopub.status.busy": "2020-11-17T14:46:46.855905Z",
     "iopub.status.idle": "2020-11-17T14:46:47.025226Z",
     "shell.execute_reply": "2020-11-17T14:46:47.024467Z"
    },
    "id": "-VECMLLLhwhv",
    "papermill": {
     "duration": 0.226357,
     "end_time": "2020-11-17T14:46:47.025369",
     "exception": false,
     "start_time": "2020-11-17T14:46:46.799012",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "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>Respondent</th>\n",
       "      <th>Age1stCode</th>\n",
       "      <th>CompTotal</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>WorkWeekHrs</th>\n",
       "      <th>CodeRevHrs</th>\n",
       "      <th>Age</th>\n",
       "      <th>is_python</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>47441.431818</td>\n",
       "      <td>18.818182</td>\n",
       "      <td>5.418654e+07</td>\n",
       "      <td>101953.333333</td>\n",
       "      <td>55.352941</td>\n",
       "      <td>14.062500</td>\n",
       "      <td>27.913043</td>\n",
       "      <td>0.181818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>41695.546512</td>\n",
       "      <td>16.783133</td>\n",
       "      <td>1.707424e+05</td>\n",
       "      <td>21833.700000</td>\n",
       "      <td>40.121212</td>\n",
       "      <td>5.781818</td>\n",
       "      <td>25.145833</td>\n",
       "      <td>0.267442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>43010.126866</td>\n",
       "      <td>17.728682</td>\n",
       "      <td>7.544398e+04</td>\n",
       "      <td>34924.047619</td>\n",
       "      <td>38.220930</td>\n",
       "      <td>6.413793</td>\n",
       "      <td>27.284404</td>\n",
       "      <td>0.298507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td>50079.857143</td>\n",
       "      <td>10.666667</td>\n",
       "      <td>7.650000e+04</td>\n",
       "      <td>160931.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\n",
       "      <td>50569.400000</td>\n",
       "      <td>18.250000</td>\n",
       "      <td>2.020000e+05</td>\n",
       "      <td>7764.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>26.666667</td>\n",
       "      <td>0.400000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Venezuela, Bolivarian Republic of...</th>\n",
       "      <td>43461.170455</td>\n",
       "      <td>16.397727</td>\n",
       "      <td>1.174443e+05</td>\n",
       "      <td>14581.627907</td>\n",
       "      <td>40.444444</td>\n",
       "      <td>6.717949</td>\n",
       "      <td>28.301205</td>\n",
       "      <td>0.318182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Viet Nam</th>\n",
       "      <td>43895.337662</td>\n",
       "      <td>15.613636</td>\n",
       "      <td>2.613438e+07</td>\n",
       "      <td>17233.436782</td>\n",
       "      <td>44.602679</td>\n",
       "      <td>8.407767</td>\n",
       "      <td>26.739884</td>\n",
       "      <td>0.337662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yemen</th>\n",
       "      <td>45331.157895</td>\n",
       "      <td>20.176471</td>\n",
       "      <td>1.375000e+05</td>\n",
       "      <td>16909.166667</td>\n",
       "      <td>41.250000</td>\n",
       "      <td>12.800000</td>\n",
       "      <td>28.117647</td>\n",
       "      <td>0.157895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zambia</th>\n",
       "      <td>42096.833333</td>\n",
       "      <td>21.500000</td>\n",
       "      <td>2.774375e+04</td>\n",
       "      <td>10075.375000</td>\n",
       "      <td>48.125000</td>\n",
       "      <td>18.400000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>37455.410256</td>\n",
       "      <td>19.421053</td>\n",
       "      <td>7.841667e+03</td>\n",
       "      <td>34046.666667</td>\n",
       "      <td>43.666667</td>\n",
       "      <td>10.636364</td>\n",
       "      <td>27.371429</td>\n",
       "      <td>0.358974</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>179 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Respondent  Age1stCode     CompTotal  \\\n",
       "Country                                                                        \n",
       "Afghanistan                           47441.431818   18.818182  5.418654e+07   \n",
       "Albania                               41695.546512   16.783133  1.707424e+05   \n",
       "Algeria                               43010.126866   17.728682  7.544398e+04   \n",
       "Andorra                               50079.857143   10.666667  7.650000e+04   \n",
       "Angola                                50569.400000   18.250000  2.020000e+05   \n",
       "...                                            ...         ...           ...   \n",
       "Venezuela, Bolivarian Republic of...  43461.170455   16.397727  1.174443e+05   \n",
       "Viet Nam                              43895.337662   15.613636  2.613438e+07   \n",
       "Yemen                                 45331.157895   20.176471  1.375000e+05   \n",
       "Zambia                                42096.833333   21.500000  2.774375e+04   \n",
       "Zimbabwe                              37455.410256   19.421053  7.841667e+03   \n",
       "\n",
       "                                      ConvertedComp  WorkWeekHrs  CodeRevHrs  \\\n",
       "Country                                                                        \n",
       "Afghanistan                           101953.333333    55.352941   14.062500   \n",
       "Albania                                21833.700000    40.121212    5.781818   \n",
       "Algeria                                34924.047619    38.220930    6.413793   \n",
       "Andorra                               160931.000000    42.000000    2.500000   \n",
       "Angola                                  7764.000000    45.000000   10.000000   \n",
       "...                                             ...          ...         ...   \n",
       "Venezuela, Bolivarian Republic of...   14581.627907    40.444444    6.717949   \n",
       "Viet Nam                               17233.436782    44.602679    8.407767   \n",
       "Yemen                                  16909.166667    41.250000   12.800000   \n",
       "Zambia                                 10075.375000    48.125000   18.400000   \n",
       "Zimbabwe                               34046.666667    43.666667   10.636364   \n",
       "\n",
       "                                            Age  is_python  \n",
       "Country                                                     \n",
       "Afghanistan                           27.913043   0.181818  \n",
       "Albania                               25.145833   0.267442  \n",
       "Algeria                               27.284404   0.298507  \n",
       "Andorra                               28.000000   0.000000  \n",
       "Angola                                26.666667   0.400000  \n",
       "...                                         ...        ...  \n",
       "Venezuela, Bolivarian Republic of...  28.301205   0.318182  \n",
       "Viet Nam                              26.739884   0.337662  \n",
       "Yemen                                 28.117647   0.157895  \n",
       "Zambia                                28.000000   0.333333  \n",
       "Zimbabwe                              27.371429   0.358974  \n",
       "\n",
       "[179 rows x 8 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#finding the mean of the people with country\n",
    "\n",
    "df.groupby('Country').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:47.150587Z",
     "iopub.status.busy": "2020-11-17T14:46:47.149741Z",
     "iopub.status.idle": "2020-11-17T14:46:47.180503Z",
     "shell.execute_reply": "2020-11-17T14:46:47.179678Z"
    },
    "id": "1bMNa800ivW_",
    "outputId": "d25f3688-c73d-49e5-9b76-f0107a7ffc54",
    "papermill": {
     "duration": 0.103733,
     "end_time": "2020-11-17T14:46:47.180633",
     "exception": false,
     "start_time": "2020-11-17T14:46:47.076900",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country\n",
       "Afghanistan                             18.181818\n",
       "Albania                                 26.744186\n",
       "Algeria                                 29.850746\n",
       "Andorra                                  0.000000\n",
       "Angola                                  40.000000\n",
       "                                          ...    \n",
       "Venezuela, Bolivarian Republic of...    31.818182\n",
       "Viet Nam                                33.766234\n",
       "Yemen                                   15.789474\n",
       "Zambia                                  33.333333\n",
       "Zimbabwe                                35.897436\n",
       "Name: is_python, Length: 179, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#basic math to find the percentage 😛\n",
    "(df.groupby('Country')['is_python'].mean())*100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nZf8gMY6rErh",
    "papermill": {
     "duration": 0.051825,
     "end_time": "2020-11-17T14:46:47.287015",
     "exception": false,
     "start_time": "2020-11-17T14:46:47.235190",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Adding Continents to the table\n",
    "\n",
    "we have table with the country in it, but what if we want to add the continents in it\n",
    "we will use python package **\"pycountry_convert as pc\"**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:47.401002Z",
     "iopub.status.busy": "2020-11-17T14:46:47.399891Z",
     "iopub.status.idle": "2020-11-17T14:46:47.404119Z",
     "shell.execute_reply": "2020-11-17T14:46:47.403512Z"
    },
    "papermill": {
     "duration": 0.064164,
     "end_time": "2020-11-17T14:46:47.404247",
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     "start_time": "2020-11-17T14:46:47.340083",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                United Kingdom\n",
       "1        Bosnia and Herzegovina\n",
       "2                      Thailand\n",
       "3                 United States\n",
       "4                       Ukraine\n",
       "                  ...          \n",
       "88878                    Canada\n",
       "88879                       NaN\n",
       "88880                       NaN\n",
       "88881                       NaN\n",
       "88882                     Spain\n",
       "Name: Country, Length: 88883, dtype: object"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Country']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.052129,
     "end_time": "2020-11-17T14:46:47.509042",
     "exception": false,
     "start_time": "2020-11-17T14:46:47.456913",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Cleaning the country columns, because many country in columns have abrevated values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:47.638801Z",
     "iopub.status.busy": "2020-11-17T14:46:47.638017Z",
     "iopub.status.idle": "2020-11-17T14:46:47.741586Z",
     "shell.execute_reply": "2020-11-17T14:46:47.740764Z"
    },
    "id": "Ihc2-JEzLR_Y",
    "papermill": {
     "duration": 0.17958,
     "end_time": "2020-11-17T14:46:47.741715",
     "exception": false,
     "start_time": "2020-11-17T14:46:47.562135",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "index_names = df[df['Country']=='Timor-Leste'].index\n",
    "df.drop(index_names, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:47.870286Z",
     "iopub.status.busy": "2020-11-17T14:46:47.863357Z",
     "iopub.status.idle": "2020-11-17T14:46:47.903263Z",
     "shell.execute_reply": "2020-11-17T14:46:47.902471Z"
    },
    "id": "9f7KTrVYmyRS",
    "papermill": {
     "duration": 0.108637,
     "end_time": "2020-11-17T14:46:47.903405",
     "exception": false,
     "start_time": "2020-11-17T14:46:47.794768",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df['Country'] = df['Country'].replace(['Hong Kong (S.A.R.)'],'Hong Kong')\n",
    "df['Country'] = df['Country'].replace(['Libyan Arab Jamahiriya'],'Libya')\n",
    "df['Country'] = df['Country'].replace(['Venezuela, Bolivarian Republic of...'],'Venezuela')\n",
    "df['Country'] = df['Country'].replace(['The former Yugoslav Republic of Macedonia'],'North Macedonia')\n",
    "df['Country'] = df['Country'].replace(['Republic of Korea'],'South Korea')\n",
    "df['Country'] = df['Country'].replace(['Congo, Republic of the...'],'Congo')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:46:48.018572Z",
     "iopub.status.busy": "2020-11-17T14:46:48.017315Z",
     "iopub.status.idle": "2020-11-17T14:47:03.037322Z",
     "shell.execute_reply": "2020-11-17T14:47:03.036648Z"
    },
    "papermill": {
     "duration": 15.079433,
     "end_time": "2020-11-17T14:47:03.037470",
     "exception": false,
     "start_time": "2020-11-17T14:46:47.958037",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting pycountry_convert\r\n",
      "  Downloading pycountry_convert-0.7.2-py3-none-any.whl (13 kB)\r\n",
      "Collecting as\r\n",
      "  Downloading as-0.1-py3-none-any.whl (2.2 kB)\r\n",
      "Collecting pc\r\n",
      "  Downloading pc-0.0.3.tar.gz (5.7 kB)\r\n",
      "Requirement already satisfied: pycountry>=16.11.27.1 in /opt/conda/lib/python3.7/site-packages (from pycountry_convert) (20.7.3)\r\n",
      "Collecting pprintpp>=0.3.0\r\n",
      "  Downloading pprintpp-0.4.0-py2.py3-none-any.whl (16 kB)\r\n",
      "Requirement already satisfied: wheel>=0.30.0 in /opt/conda/lib/python3.7/site-packages (from pycountry_convert) (0.34.2)\r\n",
      "Requirement already satisfied: pytest-mock>=1.6.3 in /opt/conda/lib/python3.7/site-packages (from pycountry_convert) (3.3.1)\r\n",
      "Requirement already satisfied: pytest>=3.4.0 in /opt/conda/lib/python3.7/site-packages (from pycountry_convert) (5.4.1)\r\n",
      "Collecting repoze.lru>=0.7\r\n",
      "  Downloading repoze.lru-0.7-py3-none-any.whl (10 kB)\r\n",
      "Requirement already satisfied: pytest-cov>=2.5.1 in /opt/conda/lib/python3.7/site-packages (from pycountry_convert) (2.10.1)\r\n",
      "Requirement already satisfied: py>=1.5.0 in /opt/conda/lib/python3.7/site-packages (from pytest>=3.4.0->pycountry_convert) (1.8.1)\r\n",
      "Requirement already satisfied: packaging in /opt/conda/lib/python3.7/site-packages (from pytest>=3.4.0->pycountry_convert) (20.1)\r\n",
      "Requirement already satisfied: attrs>=17.4.0 in /opt/conda/lib/python3.7/site-packages (from pytest>=3.4.0->pycountry_convert) (19.3.0)\r\n",
      "Requirement already satisfied: more-itertools>=4.0.0 in /opt/conda/lib/python3.7/site-packages (from pytest>=3.4.0->pycountry_convert) (8.2.0)\r\n",
      "Requirement already satisfied: pluggy<1.0,>=0.12 in /opt/conda/lib/python3.7/site-packages (from pytest>=3.4.0->pycountry_convert) (0.13.0)\r\n",
      "Requirement already satisfied: wcwidth in /opt/conda/lib/python3.7/site-packages (from pytest>=3.4.0->pycountry_convert) (0.1.9)\r\n",
      "Requirement already satisfied: importlib-metadata>=0.12 in /opt/conda/lib/python3.7/site-packages (from pytest>=3.4.0->pycountry_convert) (2.0.0)\r\n",
      "Requirement already satisfied: coverage>=4.4 in /opt/conda/lib/python3.7/site-packages (from pytest-cov>=2.5.1->pycountry_convert) (5.3)\r\n",
      "Requirement already satisfied: pyparsing>=2.0.2 in /opt/conda/lib/python3.7/site-packages (from packaging->pytest>=3.4.0->pycountry_convert) (2.4.7)\r\n",
      "Requirement already satisfied: six in /opt/conda/lib/python3.7/site-packages (from packaging->pytest>=3.4.0->pycountry_convert) (1.14.0)\r\n",
      "Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.7/site-packages (from importlib-metadata>=0.12->pytest>=3.4.0->pycountry_convert) (3.1.0)\r\n",
      "Building wheels for collected packages: pc\r\n",
      "  Building wheel for pc (setup.py) ... \u001b[?25l-\b \b\\\b \bdone\r\n",
      "\u001b[?25h  Created wheel for pc: filename=pc-0.0.3-py3-none-any.whl size=6175 sha256=ef0873ad23978f6818947e276f667002cf907fade0150ed0bf265cdd49cc0a7a\r\n",
      "  Stored in directory: /root/.cache/pip/wheels/d9/44/dd/d6ea155fcf51b584d1ed91bedc60ecaf5745e3b699e65b5b45\r\n",
      "Successfully built pc\r\n",
      "Installing collected packages: pprintpp, repoze.lru, pycountry-convert, as, pc\r\n",
      "Successfully installed as-0.1 pc-0.0.3 pprintpp-0.4.0 pycountry-convert-0.7.2 repoze.lru-0.7\r\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install pycountry_convert as pc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:03.175031Z",
     "iopub.status.busy": "2020-11-17T14:47:03.173893Z",
     "iopub.status.idle": "2020-11-17T14:47:05.388468Z",
     "shell.execute_reply": "2020-11-17T14:47:05.387757Z"
    },
    "id": "TcQDoUkwmyPn",
    "papermill": {
     "duration": 2.288032,
     "end_time": "2020-11-17T14:47:05.388611",
     "exception": false,
     "start_time": "2020-11-17T14:47:03.100579",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#for adding continents field as according with country\n",
    "\n",
    "import pycountry_convert as pc\n",
    "\n",
    "def country_to_continent(country_name):\n",
    "\n",
    "    country_alpha2 = pc.country_name_to_country_alpha2(country_name)\n",
    "    country_continent_code = pc.country_alpha2_to_continent_code(country_alpha2)\n",
    "    country_continent_name = pc.convert_continent_code_to_continent_name(country_continent_code)\n",
    "    return country_continent_name\n",
    "\n",
    "# Example\n",
    "row_count = 0\n",
    "for i in df['Country']:\n",
    "  i = str(i)\n",
    "  if i == 'Other Country (Not Listed Above)' or i == 'nan':\n",
    "    df.at[row_count,'Continent'] = 'NA'\n",
    "    continue\n",
    "\n",
    "  cont = country_to_continent(i)\n",
    "  df.at[row_count,'Continent'] = cont \n",
    "  row_count += 1\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-PvuitrCknkp",
    "papermill": {
     "duration": 0.063045,
     "end_time": "2020-11-17T14:47:05.515626",
     "exception": false,
     "start_time": "2020-11-17T14:47:05.452581",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## What is the average salary of developer based on Continents?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:05.660307Z",
     "iopub.status.busy": "2020-11-17T14:47:05.659383Z",
     "iopub.status.idle": "2020-11-17T14:47:05.663503Z",
     "shell.execute_reply": "2020-11-17T14:47:05.664051Z"
    },
    "papermill": {
     "duration": 0.080401,
     "end_time": "2020-11-17T14:47:05.664223",
     "exception": false,
     "start_time": "2020-11-17T14:47:05.583822",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0            NaN\n",
       "1            NaN\n",
       "2         8820.0\n",
       "3        61000.0\n",
       "4            NaN\n",
       "          ...   \n",
       "88879        NaN\n",
       "88880        NaN\n",
       "88881        NaN\n",
       "88882        NaN\n",
       "12853        NaN\n",
       "Name: ConvertedComp, Length: 88883, dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#ConvertedComp: Compansasion of the salary as provided in the dataset\n",
    "df['ConvertedComp'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:05.798407Z",
     "iopub.status.busy": "2020-11-17T14:47:05.797650Z",
     "iopub.status.idle": "2020-11-17T14:47:05.802992Z",
     "shell.execute_reply": "2020-11-17T14:47:05.802354Z"
    },
    "id": "XC72l3nnkskH",
    "outputId": "2c154ad7-8203-4a57-e593-17fbd50f44c5",
    "papermill": {
     "duration": 0.07449,
     "end_time": "2020-11-17T14:47:05.803114",
     "exception": false,
     "start_time": "2020-11-17T14:47:05.728624",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "127108.90421339257"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#😛\n",
    "df['ConvertedComp'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:05.949902Z",
     "iopub.status.busy": "2020-11-17T14:47:05.942399Z",
     "iopub.status.idle": "2020-11-17T14:47:05.959389Z",
     "shell.execute_reply": "2020-11-17T14:47:05.958609Z"
    },
    "id": "daAO6A1amjd4",
    "outputId": "8f5a5f29-de74-44b8-d609-1c9ed49ccf32",
    "papermill": {
     "duration": 0.092071,
     "end_time": "2020-11-17T14:47:05.959536",
     "exception": false,
     "start_time": "2020-11-17T14:47:05.867465",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Continent\n",
       "Africa           125978.401639\n",
       "Asia             125371.035023\n",
       "Europe           125454.243098\n",
       "North America    130332.328250\n",
       "Oceania          133850.459442\n",
       "South America    125968.272809\n",
       "Name: ConvertedComp, dtype: float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#grouping the compensation according to the continent \n",
    "(df.groupby('Continent')['ConvertedComp'].mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rhoHgivMmyUX",
    "papermill": {
     "duration": 0.067501,
     "end_time": "2020-11-17T14:47:06.094741",
     "exception": false,
     "start_time": "2020-11-17T14:47:06.027240",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Which will be the most desired programming language for the year 2020?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:06.234366Z",
     "iopub.status.busy": "2020-11-17T14:47:06.233387Z",
     "iopub.status.idle": "2020-11-17T14:47:06.238718Z",
     "shell.execute_reply": "2020-11-17T14:47:06.238086Z"
    },
    "papermill": {
     "duration": 0.079037,
     "end_time": "2020-11-17T14:47:06.238850",
     "exception": false,
     "start_time": "2020-11-17T14:47:06.159813",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        C;C++;C#;Go;HTML/CSS;Java;JavaScript;Python;SQL\n",
       "1                            C++;HTML/CSS;JavaScript;SQL\n",
       "2                                        Elixir;HTML/CSS\n",
       "3                                    C;C#;JavaScript;SQL\n",
       "4               HTML/CSS;Java;JavaScript;SQL;WebAssembly\n",
       "                              ...                       \n",
       "88879                                                NaN\n",
       "88880                                                NaN\n",
       "88881                                                NaN\n",
       "88882       C;C++;C#;HTML/CSS;Java;Objective-C;SQL;Swift\n",
       "12853                                                NaN\n",
       "Name: LanguageDesireNextYear, Length: 88883, dtype: object"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['LanguageDesireNextYear']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:06.410146Z",
     "iopub.status.busy": "2020-11-17T14:47:06.383927Z",
     "iopub.status.idle": "2020-11-17T14:47:06.643070Z",
     "shell.execute_reply": "2020-11-17T14:47:06.643767Z"
    },
    "id": "-LG1YRSfrOPA",
    "papermill": {
     "duration": 0.339456,
     "end_time": "2020-11-17T14:47:06.643942",
     "exception": false,
     "start_time": "2020-11-17T14:47:06.304486",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#spling the values with their values:\n",
    "\n",
    "lang_count = {}\n",
    "for i in df['LanguageDesireNextYear']:\n",
    "  i  = str(i)\n",
    "  j = i.split(';')\n",
    "  for a in j:\n",
    "    if a in lang_count:\n",
    "      lang_count[a]+=1\n",
    "    else:\n",
    "       lang_count[a] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:06.782485Z",
     "iopub.status.busy": "2020-11-17T14:47:06.781691Z",
     "iopub.status.idle": "2020-11-17T14:47:06.784806Z",
     "shell.execute_reply": "2020-11-17T14:47:06.785694Z"
    },
    "id": "acsEz5eRik3R",
    "outputId": "979367a9-141a-4fb6-ec18-9da87ee0c903",
    "papermill": {
     "duration": 0.075026,
     "end_time": "2020-11-17T14:47:06.785908",
     "exception": false,
     "start_time": "2020-11-17T14:47:06.710882",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'C': 11142, 'C++': 16856, 'C#': 22449, 'Go': 17059, 'HTML/CSS': 36644, 'Java': 23508, 'JavaScript': 44738, 'Python': 40005, 'SQL': 33565, 'Elixir': 3787, 'WebAssembly': 8439, 'Scala': 5561, 'Bash/Shell/PowerShell': 21302, 'Erlang': 2124, 'Ruby': 7251, 'Rust': 10497, 'TypeScript': 23719, 'Other(s):': 7912, 'Kotlin': 13260, 'R': 6733, 'Assembly': 4659, 'Objective-C': 2851, 'PHP': 12837, 'Swift': 8799, 'VBA': 1641, 'Clojure': 2752, 'Dart': 4428, 'nan': 4796, 'F#': 3521}\n"
     ]
    }
   ],
   "source": [
    "print(lang_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:06.925585Z",
     "iopub.status.busy": "2020-11-17T14:47:06.924600Z",
     "iopub.status.idle": "2020-11-17T14:47:06.928638Z",
     "shell.execute_reply": "2020-11-17T14:47:06.929151Z"
    },
    "id": "DgaHymnauUUH",
    "outputId": "a72bbe7f-79fe-4de2-f55b-f303ed0a2e4c",
    "papermill": {
     "duration": 0.076508,
     "end_time": "2020-11-17T14:47:06.929316",
     "exception": false,
     "start_time": "2020-11-17T14:47:06.852808",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type (lang_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:07.071292Z",
     "iopub.status.busy": "2020-11-17T14:47:07.070267Z",
     "iopub.status.idle": "2020-11-17T14:47:07.073919Z",
     "shell.execute_reply": "2020-11-17T14:47:07.074634Z"
    },
    "id": "Cjgxm7BzuPHR",
    "outputId": "b9583671-f0d8-474a-a508-70e8aa7e4414",
    "papermill": {
     "duration": 0.077922,
     "end_time": "2020-11-17T14:47:07.074800",
     "exception": false,
     "start_time": "2020-11-17T14:47:06.996878",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The most desired languaage for 2020 is:  JavaScript\n"
     ]
    }
   ],
   "source": [
    "# max of a dictionary\n",
    "lang_count1 = max(lang_count, key = lang_count.get)\n",
    "print(\"The most desired languaage for 2020 is: \", lang_count1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "R8nRBqy0tR-L",
    "papermill": {
     "duration": 0.068121,
     "end_time": "2020-11-17T14:47:07.211158",
     "exception": false,
     "start_time": "2020-11-17T14:47:07.143037",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## What is the distribution of people who code as a hobby based on gender and continent? **"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:07.400891Z",
     "iopub.status.busy": "2020-11-17T14:47:07.367735Z",
     "iopub.status.idle": "2020-11-17T14:47:07.504084Z",
     "shell.execute_reply": "2020-11-17T14:47:07.503247Z"
    },
    "id": "SEpH_DfDsppE",
    "papermill": {
     "duration": 0.22401,
     "end_time": "2020-11-17T14:47:07.504213",
     "exception": false,
     "start_time": "2020-11-17T14:47:07.280203",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#categorizing {Men, Women, Other}\n",
    "\n",
    "Gender = []\n",
    "for i in df['Gender']:\n",
    "    if (i=='Man') or (i== 'Man;Non-binary, genderqueer, or gender non-conforming'):\n",
    "        Gender.append('Man')\n",
    "    elif (i=='Woman') or (i=='Woman;Non-binary, genderqueer, or gender non-conforming') or (i=='Woman;Man;Non-binary, genderqueer, or gender non-conforming'):\n",
    "        Gender.append('Woman')\n",
    "    else:\n",
    "        Gender.append('Others')\n",
    "df['Gender'] = Gender\n",
    "df['Gender'] = df['Gender'].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:07.645966Z",
     "iopub.status.busy": "2020-11-17T14:47:07.645147Z",
     "iopub.status.idle": "2020-11-17T14:47:07.656263Z",
     "shell.execute_reply": "2020-11-17T14:47:07.655506Z"
    },
    "id": "x5TK8pmQszAn",
    "outputId": "e9631fcb-beb9-455e-80a6-90e28972069e",
    "papermill": {
     "duration": 0.084261,
     "end_time": "2020-11-17T14:47:07.656396",
     "exception": false,
     "start_time": "2020-11-17T14:47:07.572135",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Man       78100\n",
       "Woman      6576\n",
       "Others     4207\n",
       "Name: Gender, dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Gender'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:07.824212Z",
     "iopub.status.busy": "2020-11-17T14:47:07.813462Z",
     "iopub.status.idle": "2020-11-17T14:47:08.000051Z",
     "shell.execute_reply": "2020-11-17T14:47:07.999191Z"
    },
    "id": "yTTCVcYQs7oB",
    "papermill": {
     "duration": 0.274589,
     "end_time": "2020-11-17T14:47:08.000188",
     "exception": false,
     "start_time": "2020-11-17T14:47:07.725599",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "Hobbyist = []\n",
    "for i in df['Hobbyist']:\n",
    "  if i == 'Yes':\n",
    "    Hobbyist.append(1)\n",
    "  else:\n",
    "    Hobbyist.append(0)\n",
    "df['Hobbyist'] = Hobbyist\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:08.149510Z",
     "iopub.status.busy": "2020-11-17T14:47:08.148395Z",
     "iopub.status.idle": "2020-11-17T14:47:08.153323Z",
     "shell.execute_reply": "2020-11-17T14:47:08.152558Z"
    },
    "id": "ZV0btqSItCBv",
    "outputId": "0bb07ec3-3783-44e5-c633-0bbc42741781",
    "papermill": {
     "duration": 0.082118,
     "end_time": "2020-11-17T14:47:08.153484",
     "exception": false,
     "start_time": "2020-11-17T14:47:08.071366",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        1\n",
       "1        0\n",
       "2        1\n",
       "3        0\n",
       "4        1\n",
       "        ..\n",
       "88879    0\n",
       "88880    0\n",
       "88881    0\n",
       "88882    1\n",
       "12853    0\n",
       "Name: Hobbyist, Length: 88883, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Hobbyist']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:08.306834Z",
     "iopub.status.busy": "2020-11-17T14:47:08.306017Z",
     "iopub.status.idle": "2020-11-17T14:47:08.329611Z",
     "shell.execute_reply": "2020-11-17T14:47:08.328904Z"
    },
    "id": "NKt7WauLtGa2",
    "outputId": "9ca905c4-af6d-4af4-e1d3-8ffbe5c28462",
    "papermill": {
     "duration": 0.105738,
     "end_time": "2020-11-17T14:47:08.329741",
     "exception": false,
     "start_time": "2020-11-17T14:47:08.224003",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Continent      Gender\n",
       "Africa         Man        2420\n",
       "               Others      148\n",
       "               Woman       181\n",
       "Asia           Man       16309\n",
       "               Others      905\n",
       "               Woman      1358\n",
       "Europe         Man       31568\n",
       "               Others     1679\n",
       "               Woman      2596\n",
       "North America  Man       22445\n",
       "               Others     1098\n",
       "               Woman      1951\n",
       "Oceania        Man        2135\n",
       "               Others      123\n",
       "               Woman       176\n",
       "South America  Man        3094\n",
       "               Others      150\n",
       "               Woman       278\n",
       "Name: Hobbyist, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['Continent', 'Gender'])['Hobbyist'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "azByClI2xt9N",
    "papermill": {
     "duration": 0.071237,
     "end_time": "2020-11-17T14:47:08.471114",
     "exception": false,
     "start_time": "2020-11-17T14:47:08.399877",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## What is job and career satisfaction of developer based on their gender and continent?\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:08.619018Z",
     "iopub.status.busy": "2020-11-17T14:47:08.617874Z",
     "iopub.status.idle": "2020-11-17T14:47:08.622381Z",
     "shell.execute_reply": "2020-11-17T14:47:08.621723Z"
    },
    "id": "gULA1fxQx2QN",
    "papermill": {
     "duration": 0.081451,
     "end_time": "2020-11-17T14:47:08.622526",
     "exception": false,
     "start_time": "2020-11-17T14:47:08.541075",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Respondent', 'MainBranch', 'Hobbyist', 'OpenSourcer', 'OpenSource',\n",
       "       'Employment', 'Country', 'Student', 'EdLevel', 'UndergradMajor',\n",
       "       'EduOther', 'OrgSize', 'DevType', 'YearsCode', 'Age1stCode',\n",
       "       'YearsCodePro', 'CareerSat', 'JobSat', 'MgrIdiot', 'MgrMoney',\n",
       "       'MgrWant', 'JobSeek', 'LastHireDate', 'LastInt', 'FizzBuzz',\n",
       "       'JobFactors', 'ResumeUpdate', 'CurrencySymbol', 'CurrencyDesc',\n",
       "       'CompTotal', 'CompFreq', 'ConvertedComp', 'WorkWeekHrs', 'WorkPlan',\n",
       "       'WorkChallenge', 'WorkRemote', 'WorkLoc', 'ImpSyn', 'CodeRev',\n",
       "       'CodeRevHrs', 'UnitTests', 'PurchaseHow', 'PurchaseWhat',\n",
       "       'LanguageWorkedWith', 'LanguageDesireNextYear', 'DatabaseWorkedWith',\n",
       "       'DatabaseDesireNextYear', 'PlatformWorkedWith',\n",
       "       'PlatformDesireNextYear', 'WebFrameWorkedWith',\n",
       "       'WebFrameDesireNextYear', 'MiscTechWorkedWith',\n",
       "       'MiscTechDesireNextYear', 'DevEnviron', 'OpSys', 'Containers',\n",
       "       'BlockchainOrg', 'BlockchainIs', 'BetterLife', 'ITperson', 'OffOn',\n",
       "       'SocialMedia', 'Extraversion', 'ScreenName', 'SOVisit1st',\n",
       "       'SOVisitFreq', 'SOVisitTo', 'SOFindAnswer', 'SOTimeSaved',\n",
       "       'SOHowMuchTime', 'SOAccount', 'SOPartFreq', 'SOJobs', 'EntTeams',\n",
       "       'SOComm', 'WelcomeChange', 'SONewContent', 'Age', 'Gender', 'Trans',\n",
       "       'Sexuality', 'Ethnicity', 'Dependents', 'SurveyLength', 'SurveyEase',\n",
       "       'is_python', 'Continent'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:08.782908Z",
     "iopub.status.busy": "2020-11-17T14:47:08.775409Z",
     "iopub.status.idle": "2020-11-17T14:47:08.812553Z",
     "shell.execute_reply": "2020-11-17T14:47:08.813111Z"
    },
    "papermill": {
     "duration": 0.119527,
     "end_time": "2020-11-17T14:47:08.813284",
     "exception": false,
     "start_time": "2020-11-17T14:47:08.693757",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "job = df. groupby(['Continent', 'Gender', 'JobSat'])['Respondent'].count().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:08.966022Z",
     "iopub.status.busy": "2020-11-17T14:47:08.965208Z",
     "iopub.status.idle": "2020-11-17T14:47:08.968539Z",
     "shell.execute_reply": "2020-11-17T14:47:08.969095Z"
    },
    "papermill": {
     "duration": 0.08318,
     "end_time": "2020-11-17T14:47:08.969259",
     "exception": false,
     "start_time": "2020-11-17T14:47:08.886079",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "job = job.rename(columns= {'Respondent':'Count'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-11-17T14:47:09.135921Z",
     "iopub.status.busy": "2020-11-17T14:47:09.134687Z",
     "iopub.status.idle": "2020-11-17T14:47:09.140205Z",
     "shell.execute_reply": "2020-11-17T14:47:09.139499Z"
    },
    "papermill": {
     "duration": 0.09853,
     "end_time": "2020-11-17T14:47:09.140332",
     "exception": false,
     "start_time": "2020-11-17T14:47:09.041802",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "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>Continent</th>\n",
       "      <th>Gender</th>\n",
       "      <th>JobSat</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Man</td>\n",
       "      <td>Neither satisfied nor dissatisfied</td>\n",
       "      <td>223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Man</td>\n",
       "      <td>Slightly dissatisfied</td>\n",
       "      <td>323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Man</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Man</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Man</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>South America</td>\n",
       "      <td>Woman</td>\n",
       "      <td>Neither satisfied nor dissatisfied</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>South America</td>\n",
       "      <td>Woman</td>\n",
       "      <td>Slightly dissatisfied</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>South America</td>\n",
       "      <td>Woman</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>South America</td>\n",
       "      <td>Woman</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>South America</td>\n",
       "      <td>Woman</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>90 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Continent Gender                              JobSat  Count\n",
       "0          Africa    Man  Neither satisfied nor dissatisfied    223\n",
       "1          Africa    Man               Slightly dissatisfied    323\n",
       "2          Africa    Man                  Slightly satisfied    667\n",
       "3          Africa    Man                   Very dissatisfied    141\n",
       "4          Africa    Man                      Very satisfied    599\n",
       "..            ...    ...                                 ...    ...\n",
       "85  South America  Woman  Neither satisfied nor dissatisfied     26\n",
       "86  South America  Woman               Slightly dissatisfied     37\n",
       "87  South America  Woman                  Slightly satisfied     60\n",
       "88  South America  Woman                   Very dissatisfied     11\n",
       "89  South America  Woman                      Very satisfied     81\n",
       "\n",
       "[90 rows x 4 columns]"
      ]
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