2. Module_2_PANDAS_assignment_description.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"2. Module_2_PANDAS_assignment_description.ipynb","provenance":[],"collapsed_sections":[],"toc_visible":true},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"markdown","metadata":{"id":"fMcnXE8CajrT"},"source":["Download this data to use in the exercise:\n","\n","https://www.kaggle.com/the-guardian/olympic-games/data\n","\n","This exercise looks at data on all of the past olympics (up to 2014). Follow allong the text and use code cells to answer the questions.\n","\n","First, use UI or use the following code to initialize your backend and upload the datasets to colaboratory."]},{"cell_type":"code","metadata":{"id":"UAaGa0WEZqol","executionInfo":{"status":"ok","timestamp":1613925079979,"user_tz":420,"elapsed":853,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}}},"source":["import pandas as pd\n","pd.options.display.max_rows = 200\n","# The following is code for uploading a file to the colab.research.google \n","# environment.\n","\n","# library for uploading files\n","from google.colab import files \n","\n","def upload_files():\n","    # initiates the upload - follow the dialogues that appear\n","    uploaded = files.upload()\n","\n","    # verify the upload\n","    for fn in uploaded.keys():\n","        print('User uploaded file \"{name}\" with length {length} bytes'.format(\n","            name=fn, length=len(uploaded[fn])))\n","\n","    # uploaded files need to be written to file to interact with them\n","    # as part of a file system\n","    for filename in uploaded.keys():\n","        with open(filename, 'wb') as f:\n","            f.write(uploaded[filename])"],"execution_count":34,"outputs":[]},{"cell_type":"code","metadata":{"id":"d7PUid6eaw30","colab":{"resources":{"http://localhost:8080/nbextensions/google.colab/files.js":{"data":"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Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"124242d6-0173-4a81-e121-b63b24b0ecd8"},"source":["upload_files()"],"execution_count":35,"outputs":[{"output_type":"display_data","data":{"text/html":["\n","     <input type=\"file\" id=\"files-a747c4ac-fe76-46d5-8fc6-db442b414f5c\" name=\"files[]\" multiple disabled\n","        style=\"border:none\" />\n","     <output id=\"result-a747c4ac-fe76-46d5-8fc6-db442b414f5c\">\n","      Upload widget is only available when the cell has been executed in the\n","      current browser session. Please rerun this cell to enable.\n","      </output>\n","      <script src=\"/nbextensions/google.colab/files.js\"></script> "],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{"tags":[]}},{"output_type":"error","ename":"MessageError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mMessageError\u001b[0m                              Traceback (most recent call last)","\u001b[0;32m<ipython-input-35-f037fe590c82>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mupload_files\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m<ipython-input-34-cbf9d35ca7ad>\u001b[0m in \u001b[0;36mupload_files\u001b[0;34m()\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mupload_files\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m     \u001b[0;31m# initiates the upload - follow the dialogues that appear\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m     \u001b[0muploaded\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfiles\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0;31m# verify the upload\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/google/colab/files.py\u001b[0m in \u001b[0;36mupload\u001b[0;34m()\u001b[0m\n\u001b[1;32m     70\u001b[0m     result = _output.eval_js(\n\u001b[1;32m     71\u001b[0m         'google.colab._files._uploadFilesContinue(\"{output_id}\")'.format(\n\u001b[0;32m---> 72\u001b[0;31m             output_id=output_id))\n\u001b[0m\u001b[1;32m     73\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'action'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m'append'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     74\u001b[0m       \u001b[0;31m# JS side uses a generator of promises to process all of the files- some\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/google/colab/output/_js.py\u001b[0m in \u001b[0;36meval_js\u001b[0;34m(script, ignore_result, timeout_sec)\u001b[0m\n\u001b[1;32m     38\u001b[0m   \u001b[0;32mif\u001b[0m \u001b[0mignore_result\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     39\u001b[0m     \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 40\u001b[0;31m   \u001b[0;32mreturn\u001b[0m \u001b[0m_message\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_reply_from_input\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout_sec\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     41\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     42\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/google/colab/_message.py\u001b[0m in \u001b[0;36mread_reply_from_input\u001b[0;34m(message_id, timeout_sec)\u001b[0m\n\u001b[1;32m    104\u001b[0m         reply.get('colab_msg_id') == message_id):\n\u001b[1;32m    105\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0;34m'error'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mreply\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 106\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mMessageError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreply\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'error'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    107\u001b[0m       \u001b[0;32mreturn\u001b[0m \u001b[0mreply\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'data'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    108\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mMessageError\u001b[0m: RangeError: Maximum call stack size exceeded."]}]},{"cell_type":"markdown","metadata":{"id":"uQ9uagHFiS5Y"},"source":["## Basics"]},{"cell_type":"markdown","metadata":{"id":"Q1V_p4JTa34r"},"source":["1) Load the three data files as DataFrames."]},{"cell_type":"code","metadata":{"id":"fZDe_H3tazTf","executionInfo":{"status":"ok","timestamp":1613929558250,"user_tz":420,"elapsed":625,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}}},"source":["country_dict_df = pd.read_csv(\"dictionary.csv\")\n","summer_df = pd.read_csv(\"summer.csv\")\n","winter_df = pd.read_csv(\"winter.csv\")"],"execution_count":157,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"7PtZllvbe714"},"source":["2) Get a basic feel for the schemas of these three dataframes. Run some of the EDA techniques we discussed."]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"2VJgjNF9LF5s","executionInfo":{"status":"ok","timestamp":1613925119458,"user_tz":420,"elapsed":711,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"11bbea8b-c61f-4119-a106-acb90cbea0fb"},"source":["display(country_dict_df.head(10))\n","display(summer_df.head(10))\n","display(winter_df.head(10))\n","\n"],"execution_count":38,"outputs":[{"output_type":"display_data","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>Country</th>\n","      <th>Code</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>Afghanistan</td>\n","      <td>AFG</td>\n","      <td>32526562.0</td>\n","      <td>594.323081</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>Albania</td>\n","      <td>ALB</td>\n","      <td>2889167.0</td>\n","      <td>3945.217582</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>Algeria</td>\n","      <td>ALG</td>\n","      <td>39666519.0</td>\n","      <td>4206.031232</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>American Samoa*</td>\n","      <td>ASA</td>\n","      <td>55538.0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Andorra</td>\n","      <td>AND</td>\n","      <td>70473.0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>Angola</td>\n","      <td>ANG</td>\n","      <td>25021974.0</td>\n","      <td>4101.472152</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>Antigua and Barbuda</td>\n","      <td>ANT</td>\n","      <td>91818.0</td>\n","      <td>13714.731962</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>Argentina</td>\n","      <td>ARG</td>\n","      <td>43416755.0</td>\n","      <td>13431.878340</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>Armenia</td>\n","      <td>ARM</td>\n","      <td>3017712.0</td>\n","      <td>3489.127690</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>Aruba*</td>\n","      <td>ARU</td>\n","      <td>103889.0</td>\n","      <td>NaN</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["               Country Code  Population  GDP per Capita\n","0          Afghanistan  AFG  32526562.0      594.323081\n","1              Albania  ALB   2889167.0     3945.217582\n","2              Algeria  ALG  39666519.0     4206.031232\n","3      American Samoa*  ASA     55538.0             NaN\n","4              Andorra  AND     70473.0             NaN\n","5               Angola  ANG  25021974.0     4101.472152\n","6  Antigua and Barbuda  ANT     91818.0    13714.731962\n","7            Argentina  ARG  43416755.0    13431.878340\n","8              Armenia  ARM   3017712.0     3489.127690\n","9               Aruba*  ARU    103889.0             NaN"]},"metadata":{"tags":[]}},{"output_type":"display_data","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>Year</th>\n","      <th>City</th>\n","      <th>Sport</th>\n","      <th>Discipline</th>\n","      <th>Athlete</th>\n","      <th>Country</th>\n","      <th>Gender</th>\n","      <th>Event</th>\n","      <th>Medal</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1896</td>\n","      <td>Athens</td>\n","      <td>Aquatics</td>\n","      <td>Swimming</td>\n","      <td>HAJOS, Alfred</td>\n","      <td>HUN</td>\n","      <td>Men</td>\n","      <td>100M Freestyle</td>\n","      <td>Gold</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1896</td>\n","      <td>Athens</td>\n","      <td>Aquatics</td>\n","      <td>Swimming</td>\n","      <td>HERSCHMANN, Otto</td>\n","      <td>AUT</td>\n","      <td>Men</td>\n","      <td>100M Freestyle</td>\n","      <td>Silver</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1896</td>\n","      <td>Athens</td>\n","      <td>Aquatics</td>\n","      <td>Swimming</td>\n","      <td>DRIVAS, Dimitrios</td>\n","      <td>GRE</td>\n","      <td>Men</td>\n","      <td>100M Freestyle For Sailors</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1896</td>\n","      <td>Athens</td>\n","      <td>Aquatics</td>\n","      <td>Swimming</td>\n","      <td>MALOKINIS, Ioannis</td>\n","      <td>GRE</td>\n","      <td>Men</td>\n","      <td>100M Freestyle For Sailors</td>\n","      <td>Gold</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1896</td>\n","      <td>Athens</td>\n","      <td>Aquatics</td>\n","      <td>Swimming</td>\n","      <td>CHASAPIS, Spiridon</td>\n","      <td>GRE</td>\n","      <td>Men</td>\n","      <td>100M Freestyle For Sailors</td>\n","      <td>Silver</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>1896</td>\n","      <td>Athens</td>\n","      <td>Aquatics</td>\n","      <td>Swimming</td>\n","      <td>CHOROPHAS, Efstathios</td>\n","      <td>GRE</td>\n","      <td>Men</td>\n","      <td>1200M Freestyle</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>1896</td>\n","      <td>Athens</td>\n","      <td>Aquatics</td>\n","      <td>Swimming</td>\n","      <td>HAJOS, Alfred</td>\n","      <td>HUN</td>\n","      <td>Men</td>\n","      <td>1200M Freestyle</td>\n","      <td>Gold</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>1896</td>\n","      <td>Athens</td>\n","      <td>Aquatics</td>\n","      <td>Swimming</td>\n","      <td>ANDREOU, Joannis</td>\n","      <td>GRE</td>\n","      <td>Men</td>\n","      <td>1200M Freestyle</td>\n","      <td>Silver</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>1896</td>\n","      <td>Athens</td>\n","      <td>Aquatics</td>\n","      <td>Swimming</td>\n","      <td>CHOROPHAS, Efstathios</td>\n","      <td>GRE</td>\n","      <td>Men</td>\n","      <td>400M Freestyle</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>1896</td>\n","      <td>Athens</td>\n","      <td>Aquatics</td>\n","      <td>Swimming</td>\n","      <td>NEUMANN, Paul</td>\n","      <td>AUT</td>\n","      <td>Men</td>\n","      <td>400M Freestyle</td>\n","      <td>Gold</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Year    City     Sport  ... Gender                       Event   Medal\n","0  1896  Athens  Aquatics  ...    Men              100M Freestyle    Gold\n","1  1896  Athens  Aquatics  ...    Men              100M Freestyle  Silver\n","2  1896  Athens  Aquatics  ...    Men  100M Freestyle For Sailors  Bronze\n","3  1896  Athens  Aquatics  ...    Men  100M Freestyle For Sailors    Gold\n","4  1896  Athens  Aquatics  ...    Men  100M Freestyle For Sailors  Silver\n","5  1896  Athens  Aquatics  ...    Men             1200M Freestyle  Bronze\n","6  1896  Athens  Aquatics  ...    Men             1200M Freestyle    Gold\n","7  1896  Athens  Aquatics  ...    Men             1200M Freestyle  Silver\n","8  1896  Athens  Aquatics  ...    Men              400M Freestyle  Bronze\n","9  1896  Athens  Aquatics  ...    Men              400M Freestyle    Gold\n","\n","[10 rows x 9 columns]"]},"metadata":{"tags":[]}},{"output_type":"display_data","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>Year</th>\n","      <th>City</th>\n","      <th>Sport</th>\n","      <th>Discipline</th>\n","      <th>Athlete</th>\n","      <th>Country</th>\n","      <th>Gender</th>\n","      <th>Event</th>\n","      <th>Medal</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>BERTHET, G.</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>MANDRILLON, C.</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>MANDRILLON, Maurice</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>VANDELLE, André</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>AUFDENBLATTEN, Adolf</td>\n","      <td>SUI</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Gold</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>JULEN, Alphonse</td>\n","      <td>SUI</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Gold</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>JULEN, Ant.</td>\n","      <td>SUI</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Gold</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>VAUCHER, D.</td>\n","      <td>SUI</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Gold</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>BREMER, V.E.</td>\n","      <td>FIN</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Silver</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>ESKELINEN, A.</td>\n","      <td>FIN</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Silver</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Year      City     Sport Discipline  ... Country Gender            Event   Medal\n","0  1924  Chamonix  Biathlon   Biathlon  ...     FRA    Men  Military Patrol  Bronze\n","1  1924  Chamonix  Biathlon   Biathlon  ...     FRA    Men  Military Patrol  Bronze\n","2  1924  Chamonix  Biathlon   Biathlon  ...     FRA    Men  Military Patrol  Bronze\n","3  1924  Chamonix  Biathlon   Biathlon  ...     FRA    Men  Military Patrol  Bronze\n","4  1924  Chamonix  Biathlon   Biathlon  ...     SUI    Men  Military Patrol    Gold\n","5  1924  Chamonix  Biathlon   Biathlon  ...     SUI    Men  Military Patrol    Gold\n","6  1924  Chamonix  Biathlon   Biathlon  ...     SUI    Men  Military Patrol    Gold\n","7  1924  Chamonix  Biathlon   Biathlon  ...     SUI    Men  Military Patrol    Gold\n","8  1924  Chamonix  Biathlon   Biathlon  ...     FIN    Men  Military Patrol  Silver\n","9  1924  Chamonix  Biathlon   Biathlon  ...     FIN    Men  Military Patrol  Silver\n","\n","[10 rows x 9 columns]"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 201 entries, 0 to 200\n","Data columns (total 4 columns):\n"," #   Column          Non-Null Count  Dtype  \n","---  ------          --------------  -----  \n"," 0   Country         201 non-null    object \n"," 1   Code            201 non-null    object \n"," 2   Population      196 non-null    float64\n"," 3   GDP per Capita  176 non-null    float64\n","dtypes: float64(2), object(2)\n","memory usage: 6.4+ KB\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":799},"id":"Iaw7kNyLbzbT","executionInfo":{"status":"ok","timestamp":1613925153196,"user_tz":420,"elapsed":566,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"8837999b-4bcd-4f47-a794-380183af77c5"},"source":["display(country_dict_df.info())\n","display(summer_df.info())\n","display(winter_df.info())"],"execution_count":39,"outputs":[{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 201 entries, 0 to 200\n","Data columns (total 4 columns):\n"," #   Column          Non-Null Count  Dtype  \n","---  ------          --------------  -----  \n"," 0   Country         201 non-null    object \n"," 1   Code            201 non-null    object \n"," 2   Population      196 non-null    float64\n"," 3   GDP per Capita  176 non-null    float64\n","dtypes: float64(2), object(2)\n","memory usage: 6.4+ KB\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/plain":["None"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 31165 entries, 0 to 31164\n","Data columns (total 9 columns):\n"," #   Column      Non-Null Count  Dtype \n","---  ------      --------------  ----- \n"," 0   Year        31165 non-null  int64 \n"," 1   City        31165 non-null  object\n"," 2   Sport       31165 non-null  object\n"," 3   Discipline  31165 non-null  object\n"," 4   Athlete     31165 non-null  object\n"," 5   Country     31161 non-null  object\n"," 6   Gender      31165 non-null  object\n"," 7   Event       31165 non-null  object\n"," 8   Medal       31165 non-null  object\n","dtypes: int64(1), object(8)\n","memory usage: 2.1+ MB\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/plain":["None"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 5770 entries, 0 to 5769\n","Data columns (total 9 columns):\n"," #   Column      Non-Null Count  Dtype \n","---  ------      --------------  ----- \n"," 0   Year        5770 non-null   int64 \n"," 1   City        5770 non-null   object\n"," 2   Sport       5770 non-null   object\n"," 3   Discipline  5770 non-null   object\n"," 4   Athlete     5770 non-null   object\n"," 5   Country     5770 non-null   object\n"," 6   Gender      5770 non-null   object\n"," 7   Event       5770 non-null   object\n"," 8   Medal       5770 non-null   object\n","dtypes: int64(1), object(8)\n","memory usage: 405.8+ KB\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/plain":["None"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"jx783yoIhp1J"},"source":["3) The semantics of this data all looks pretty straight forward. Can we verify that the Population column is not a power of ten? Try querying for just the 'Canada' row in the country dictionary DataFrame to verify this. \n","\n","Tips: \n","- use `.loc` \n","- Look at the data!"]},{"cell_type":"code","metadata":{"id":"Kuhaep2KIVrK","colab":{"base_uri":"https://localhost:8080/","height":221},"executionInfo":{"status":"ok","timestamp":1613925158816,"user_tz":420,"elapsed":521,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"3553cb57-e726-424a-8672-71688066f13e"},"source":["\n","#Canada Row query. Canada is row index number 34:\n","\n","display(country_dict_df.loc[34,:])\n","\n","print(\"\\nCountry with largest population\")\n","\n","\n","#country with largest population:\n","display(country_dict_df.sort_values('Population', ascending= False).iloc[0])\n"],"execution_count":40,"outputs":[{"output_type":"display_data","data":{"text/plain":["Country                Canada\n","Code                      CAN\n","Population        3.58518e+07\n","GDP per Capita        43248.5\n","Name: 34, dtype: object"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n","Country with largest population\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/plain":["Country                 China\n","Code                      CHN\n","Population        1.37122e+09\n","GDP per Capita        8027.68\n","Name: 40, dtype: object"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"Kvh4laOUjR9c"},"source":["4) Looking at just the Summer olympics let's do some querying. Every query here can be done in one line each:\n","\n",">a) Display the row corresponding to athlete Kate Walsh's medal.\n","\n",">b) Display just the City corresponding to athlete Kate Walsh's medal.\n","\n",">c) List each sport found in the summer olympics DataFrame\n","\n",">d) What medal did Cristian Gatu win in 1976?\n","\n",">e) How many medals have been won by USA and China cummulative? Hint: Use `.count()` after a query to count the rows.\n"]},{"cell_type":"code","metadata":{"id":"Jfb9Xz09Ih08","colab":{"base_uri":"https://localhost:8080/","height":80},"executionInfo":{"status":"ok","timestamp":1613925162122,"user_tz":420,"elapsed":520,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"e5972f6c-6ecb-48ca-f5ee-04e4f6162b35"},"source":["kate_walsh = summer_df[summer_df['Athlete'] == \"WALSH, Kate\"]\n","kate_walsh"],"execution_count":41,"outputs":[{"output_type":"execute_result","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>Year</th>\n","      <th>City</th>\n","      <th>Sport</th>\n","      <th>Discipline</th>\n","      <th>Athlete</th>\n","      <th>Country</th>\n","      <th>Gender</th>\n","      <th>Event</th>\n","      <th>Medal</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>30576</th>\n","      <td>2012</td>\n","      <td>London</td>\n","      <td>Hockey</td>\n","      <td>Hockey</td>\n","      <td>WALSH, Kate</td>\n","      <td>GBR</td>\n","      <td>Women</td>\n","      <td>Hockey</td>\n","      <td>Bronze</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["       Year    City   Sport Discipline  ... Country Gender   Event   Medal\n","30576  2012  London  Hockey     Hockey  ...     GBR  Women  Hockey  Bronze\n","\n","[1 rows x 9 columns]"]},"metadata":{"tags":[]},"execution_count":41}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9egt2FYsOm7q","executionInfo":{"status":"ok","timestamp":1613925165970,"user_tz":420,"elapsed":593,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"347fde10-edb8-4fe7-b24c-cfa27e7f08ae"},"source":[" kate_walsh['City']"],"execution_count":42,"outputs":[{"output_type":"execute_result","data":{"text/plain":["30576    London\n","Name: City, dtype: object"]},"metadata":{"tags":[]},"execution_count":42}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"_aeWiNJ5O4xw","executionInfo":{"status":"ok","timestamp":1613925169017,"user_tz":420,"elapsed":751,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"4b3aa321-8327-488d-823d-4ce7bbf65852"},"source":["print(summer_df['Sport'].sort_values().unique())"],"execution_count":43,"outputs":[{"output_type":"stream","text":["['Aquatics' 'Archery' 'Athletics' 'Badminton' 'Baseball' 'Basketball'\n"," 'Basque Pelota' 'Boxing' 'Canoe' 'Canoe / Kayak' 'Cricket' 'Croquet'\n"," 'Cycling' 'Equestrian' 'Fencing' 'Football' 'Golf' 'Gymnastics'\n"," 'Handball' 'Hockey' 'Ice Hockey' 'Jeu de paume' 'Judo' 'Lacrosse'\n"," 'Modern Pentathlon' 'Polo' 'Rackets' 'Roque' 'Rowing' 'Rugby' 'Sailing'\n"," 'Shooting' 'Skating' 'Softball' 'Table Tennis' 'Taekwondo' 'Tennis'\n"," 'Triathlon' 'Tug of War' 'Volleyball' 'Water Motorsports' 'Weightlifting'\n"," 'Wrestling']\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"2Bc-gqEoPZbb"},"source":["TUG OF WAR was in Olympics????"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"7BBhuC8qPYWH","executionInfo":{"status":"ok","timestamp":1613925171983,"user_tz":420,"elapsed":718,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"8e5d6ee9-4d7d-45f0-8829-cfc307b618f6"},"source":["summer_df[(summer_df['Athlete']==\"GATU, Cristian\") & (summer_df['Year'] == 1976)]['Medal']"],"execution_count":44,"outputs":[{"output_type":"execute_result","data":{"text/plain":["14691    Silver\n","Name: Medal, dtype: object"]},"metadata":{"tags":[]},"execution_count":44}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":80},"id":"Lbq5kN4yQ3ld","executionInfo":{"status":"ok","timestamp":1613925173490,"user_tz":420,"elapsed":666,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"b0dade70-4ec9-4ca7-e311-2664d09b4fc5"},"source":["country_dict_df[country_dict_df['Country'] == \"China\"]"],"execution_count":45,"outputs":[{"output_type":"execute_result","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>Country</th>\n","      <th>Code</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>40</th>\n","      <td>China</td>\n","      <td>CHN</td>\n","      <td>1.371220e+09</td>\n","      <td>8027.68381</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Country Code    Population  GDP per Capita\n","40   China  CHN  1.371220e+09      8027.68381"]},"metadata":{"tags":[]},"execution_count":45}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"QcFF0cCUPY6G","executionInfo":{"status":"ok","timestamp":1613925175473,"user_tz":420,"elapsed":628,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"4b86e2a5-3835-4859-834f-69b618b7db49"},"source":["print(summer_df[(summer_df['Country'] == 'CHN') | (summer_df['Country'] == 'USA') ]['Medal'].count())"],"execution_count":46,"outputs":[{"output_type":"stream","text":["5392\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"hxyXNttaoGlx"},"source":["5) Let's do some sorting! I want you to make two DataFrame variables:\n","\n","\n","*   Sort the country dictionary by Population from lowest to highest\n","*   Sort the country dictionary by population from highest to lowest\n","\n","Make sure you save the results of each sort to a variable.\n","\n","Next, call `.reset_index(drop=True)` on each of the new variables you created. What has this done?\n","\n","Finally, we are interested in know the country name with the largest population and the country name with the\n","smallest population. Fortunately, the data structures we just created lend themselves nicely to this task. Query\n","for the Country name in the first row of each of DataFrames you created in this question. (hint: Use `.at[,]`)\n"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":204},"id":"gM1JwQDZPXo7","executionInfo":{"status":"ok","timestamp":1613925177329,"user_tz":420,"elapsed":569,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"d11d00a3-55ca-41a9-db60-c1639bfa0151"},"source":["population_ascending = country_dict_df.sort_values('Population', ascending = True)\n","population_ascending.head(5)"],"execution_count":47,"outputs":[{"output_type":"execute_result","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>Country</th>\n","      <th>Code</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>127</th>\n","      <td>Nauru</td>\n","      <td>NRU</td>\n","      <td>10222.0</td>\n","      <td>9827.544281</td>\n","    </tr>\n","    <tr>\n","      <th>138</th>\n","      <td>Palau</td>\n","      <td>PLW</td>\n","      <td>21291.0</td>\n","      <td>13498.661406</td>\n","    </tr>\n","    <tr>\n","      <th>27</th>\n","      <td>British Virgin Islands</td>\n","      <td>IVB</td>\n","      <td>30117.0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>156</th>\n","      <td>San Marino</td>\n","      <td>SMR</td>\n","      <td>31781.0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>106</th>\n","      <td>Liechtenstein</td>\n","      <td>LIE</td>\n","      <td>37531.0</td>\n","      <td>NaN</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                    Country Code  Population  GDP per Capita\n","127                   Nauru  NRU     10222.0     9827.544281\n","138                   Palau  PLW     21291.0    13498.661406\n","27   British Virgin Islands  IVB     30117.0             NaN\n","156              San Marino  SMR     31781.0             NaN\n","106           Liechtenstein  LIE     37531.0             NaN"]},"metadata":{"tags":[]},"execution_count":47}]},{"cell_type":"code","metadata":{"id":"TvqJ9isTJC0W","colab":{"base_uri":"https://localhost:8080/","height":204},"executionInfo":{"status":"ok","timestamp":1613925179220,"user_tz":420,"elapsed":553,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"86e483fb-5a95-4af6-f33c-2815d5d7422f"},"source":["population_descending = country_dict_df.sort_values('Population', ascending = False)\n","population_descending.head(5)"],"execution_count":48,"outputs":[{"output_type":"execute_result","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>Country</th>\n","      <th>Code</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>40</th>\n","      <td>China</td>\n","      <td>CHN</td>\n","      <td>1.371220e+09</td>\n","      <td>8027.683810</td>\n","    </tr>\n","    <tr>\n","      <th>84</th>\n","      <td>India</td>\n","      <td>IND</td>\n","      <td>1.311051e+09</td>\n","      <td>1598.259034</td>\n","    </tr>\n","    <tr>\n","      <th>191</th>\n","      <td>United States</td>\n","      <td>USA</td>\n","      <td>3.214188e+08</td>\n","      <td>56115.718426</td>\n","    </tr>\n","    <tr>\n","      <th>85</th>\n","      <td>Indonesia</td>\n","      <td>INA</td>\n","      <td>2.575638e+08</td>\n","      <td>3346.487039</td>\n","    </tr>\n","    <tr>\n","      <th>26</th>\n","      <td>Brazil</td>\n","      <td>BRA</td>\n","      <td>2.078475e+08</td>\n","      <td>8538.589975</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["           Country Code    Population  GDP per Capita\n","40           China  CHN  1.371220e+09     8027.683810\n","84           India  IND  1.311051e+09     1598.259034\n","191  United States  USA  3.214188e+08    56115.718426\n","85       Indonesia  INA  2.575638e+08     3346.487039\n","26          Brazil  BRA  2.078475e+08     8538.589975"]},"metadata":{"tags":[]},"execution_count":48}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":224},"id":"2o4GjdiYXKaZ","executionInfo":{"status":"ok","timestamp":1613925181969,"user_tz":420,"elapsed":629,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"62539091-7aba-4832-c50c-db46d140b7e6"},"source":["population_ascending = population_ascending.reset_index(drop = True)\n","display(population_ascending.head(5))\n","population_ascending.at[0,'Country']"],"execution_count":49,"outputs":[{"output_type":"display_data","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>Country</th>\n","      <th>Code</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>Nauru</td>\n","      <td>NRU</td>\n","      <td>10222.0</td>\n","      <td>9827.544281</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>Palau</td>\n","      <td>PLW</td>\n","      <td>21291.0</td>\n","      <td>13498.661406</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>British Virgin Islands</td>\n","      <td>IVB</td>\n","      <td>30117.0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>San Marino</td>\n","      <td>SMR</td>\n","      <td>31781.0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Liechtenstein</td>\n","      <td>LIE</td>\n","      <td>37531.0</td>\n","      <td>NaN</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                  Country Code  Population  GDP per Capita\n","0                   Nauru  NRU     10222.0     9827.544281\n","1                   Palau  PLW     21291.0    13498.661406\n","2  British Virgin Islands  IVB     30117.0             NaN\n","3              San Marino  SMR     31781.0             NaN\n","4           Liechtenstein  LIE     37531.0             NaN"]},"metadata":{"tags":[]}},{"output_type":"execute_result","data":{"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"},"text/plain":["'Nauru'"]},"metadata":{"tags":[]},"execution_count":49}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":224},"id":"PY7wYvbkXKMO","executionInfo":{"status":"ok","timestamp":1613925184434,"user_tz":420,"elapsed":604,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"6bbe4c97-2a69-4474-c58b-f9e34964facb"},"source":["population_descending = population_descending.reset_index(drop = True)\n","display(population_descending.head(5))\n","population_descending.at[0,'Country']"],"execution_count":50,"outputs":[{"output_type":"display_data","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>Country</th>\n","      <th>Code</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>China</td>\n","      <td>CHN</td>\n","      <td>1.371220e+09</td>\n","      <td>8027.683810</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>India</td>\n","      <td>IND</td>\n","      <td>1.311051e+09</td>\n","      <td>1598.259034</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>United States</td>\n","      <td>USA</td>\n","      <td>3.214188e+08</td>\n","      <td>56115.718426</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Indonesia</td>\n","      <td>INA</td>\n","      <td>2.575638e+08</td>\n","      <td>3346.487039</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Brazil</td>\n","      <td>BRA</td>\n","      <td>2.078475e+08</td>\n","      <td>8538.589975</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["         Country Code    Population  GDP per Capita\n","0          China  CHN  1.371220e+09     8027.683810\n","1          India  IND  1.311051e+09     1598.259034\n","2  United States  USA  3.214188e+08    56115.718426\n","3      Indonesia  INA  2.575638e+08     3346.487039\n","4         Brazil  BRA  2.078475e+08     8538.589975"]},"metadata":{"tags":[]}},{"output_type":"execute_result","data":{"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"},"text/plain":["'China'"]},"metadata":{"tags":[]},"execution_count":50}]},{"cell_type":"markdown","metadata":{"id":"wsvaN06hXc4P"},"source":["The index has been re-arranged"]},{"cell_type":"markdown","metadata":{"id":"bok22kSkrKIC"},"source":["6) Grouping time! Remember the group and aggregate paradigm for these tasks.\n","\n","Let's use the winter olympics DataFrame this time. Can you display:\n","\n",">a) The number of medals for each country? (hint: use `.groupby` and then `.count`)\n","\n",">b) The number of medals for each sport. Treat Mens and Womens categories as separate sports? (Hint: groupby can take a list of column names)\n","\n",">c) The Average number of medals in a year they competed for each country? This one requires two groupby statements. First, groupby two columns and aggregate. Then use groupby on that output to compute an average."]},{"cell_type":"code","metadata":{"id":"7VS8clktJGEg","colab":{"base_uri":"https://localhost:8080/","height":816},"executionInfo":{"status":"ok","timestamp":1613925345884,"user_tz":420,"elapsed":527,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"166b6b24-385e-465a-f9a7-dc15e3f44b69"},"source":["winter_medals_country = winter_df.groupby('Country').count()['Medal']\n","display(winter_medals_country)"],"execution_count":62,"outputs":[{"output_type":"display_data","data":{"text/plain":["Country\n","AUS     15\n","AUT    280\n","BEL     13\n","BLR     15\n","BUL      6\n","CAN    625\n","CHN     82\n","CRO     11\n","CZE     75\n","DEN      5\n","ESP      2\n","EST      7\n","EUA     21\n","EUN     60\n","FIN    434\n","FRA    152\n","FRG     94\n","GBR     79\n","GDR    162\n","GER    360\n","HUN     12\n","ITA    192\n","JPN     63\n","KAZ      7\n","KOR     87\n","LAT     15\n","LIE      9\n","LUX      2\n","NED    122\n","NOR    457\n","NZL      1\n","POL     27\n","PRK      2\n","ROU      2\n","RUS    263\n","SLO     18\n","SUI    285\n","SVK      5\n","SWE    433\n","TCH    158\n","UKR     11\n","URS    440\n","USA    653\n","UZB      1\n","YUG      7\n","Name: Medal, dtype: int64"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":289},"id":"GdAfwTTHcQIe","executionInfo":{"status":"ok","timestamp":1613925382070,"user_tz":420,"elapsed":521,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"a020e494-43ee-4aa9-9268-b94de14eaca1"},"source":["winter_medals_gender = winter_df.groupby(['Gender', 'Sport']).count()['Medal']\n","display(winter_medals_gender)"],"execution_count":65,"outputs":[{"output_type":"display_data","data":{"text/plain":["Gender  Sport     \n","Men     Biathlon       270\n","        Bobsleigh      416\n","        Curling         97\n","        Ice Hockey    1231\n","        Luge           135\n","        Skating        665\n","        Skiing        1130\n","Women   Biathlon       150\n","        Bobsleigh       36\n","        Curling         75\n","        Ice Hockey     305\n","        Luge            45\n","        Skating        564\n","        Skiing         651\n","Name: Medal, dtype: int64"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":816},"id":"MDT0zwKJcwBJ","executionInfo":{"status":"ok","timestamp":1613925963278,"user_tz":420,"elapsed":548,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"acbad541-5bcd-442b-ce0c-29fc383477c9"},"source":["winter_country_year =winter_df.groupby(['Country','Year']).count()\n","\n","winter_country_year_medal = winter_country_year.groupby('Country').aggregate('mean')['Medal']\n","\n","display(winter_country_year_medal)"],"execution_count":83,"outputs":[{"output_type":"display_data","data":{"text/plain":["Country\n","AUS     2.500000\n","AUT    12.727273\n","BEL     3.250000\n","BLR     2.500000\n","BUL     1.500000\n","CAN    28.409091\n","CHN    11.714286\n","CRO     2.750000\n","CZE    15.000000\n","DEN     5.000000\n","ESP     1.000000\n","EST     2.333333\n","EUA     7.000000\n","EUN    60.000000\n","FIN    19.727273\n","FRA     7.238095\n","FRG    13.428571\n","GBR     5.266667\n","GDR    27.000000\n","GER    36.000000\n","HUN     2.000000\n","ITA    10.666667\n","JPN     5.250000\n","KAZ     1.750000\n","KOR    12.428571\n","LAT     5.000000\n","LIE     2.250000\n","LUX     2.000000\n","NED     8.133333\n","NOR    20.772727\n","NZL     1.000000\n","POL     3.857143\n","PRK     1.000000\n","ROU     2.000000\n","RUS    43.833333\n","SLO     4.500000\n","SUI    13.571429\n","SVK     1.666667\n","SWE    19.681818\n","TCH    14.363636\n","UKR     2.750000\n","URS    48.888889\n","USA    29.681818\n","UZB     1.000000\n","YUG     3.500000\n","Name: Medal, dtype: float64"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"VmOaHaaYEx-J"},"source":["7) value_counts() is a method that can be used on a Series (individual column) to quickly summarize the contents. It is similar to calling groupby, count and then sort_values. I want to show how this method works and some tricks you can use with it. We are going to use the winter olmpics DataFrame again.\n","\n",">a) Use .value_counts() on the Sport column to see what Sports exist and how many medals have been won in each sport. Save the output to a variable.\n","\n",">b) Notice that the output of value_counts is a Series where the values are the counts and the indices are the labels. Display the largest value in the Series you produced in a). (Hint: use .iat)\n","\n",">c) How many medals have been won in the \"Skating\" sport? (hint: sport names are the indices of the series so you can access them directly with the [] operator)\n","\n",">d) Sometimes it can be easier to work with data as a DataFrame than a Series (e.g. using the loc operator). Use .reset_index() on your Series to turn the value_counts() series into a DataFrame."]},{"cell_type":"code","metadata":{"id":"UJEn4dIJJJjh","colab":{"base_uri":"https://localhost:8080/","height":170},"executionInfo":{"status":"ok","timestamp":1613926263730,"user_tz":420,"elapsed":537,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"6f33e2ac-ed26-48b7-db20-732572d1e57a"},"source":["sport_value_count = winter_df.value_counts('Sport')\n","display(sport_value_count)\n"],"execution_count":86,"outputs":[{"output_type":"display_data","data":{"text/plain":["Sport\n","Skiing        1781\n","Ice Hockey    1536\n","Skating       1229\n","Bobsleigh      452\n","Biathlon       420\n","Luge           180\n","Curling        172\n","dtype: int64"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"hFDVzYzhgS8i","executionInfo":{"status":"ok","timestamp":1613926364212,"user_tz":420,"elapsed":541,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"1da724f1-a747-446e-e9e1-83c11d558afb"},"source":["sport_value_count.iat[0]"],"execution_count":87,"outputs":[{"output_type":"execute_result","data":{"text/plain":["1781"]},"metadata":{"tags":[]},"execution_count":87}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"K8ZGg8N2gUrp","executionInfo":{"status":"ok","timestamp":1613926393898,"user_tz":420,"elapsed":544,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"478140b6-009a-4c19-8269-54d2141bcc25"},"source":["sport_value_count['Skating']"],"execution_count":88,"outputs":[{"output_type":"execute_result","data":{"text/plain":["1229"]},"metadata":{"tags":[]},"execution_count":88}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":266},"id":"MGmx9TgvgHRw","executionInfo":{"status":"ok","timestamp":1613926442746,"user_tz":420,"elapsed":611,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"0f084080-1e7a-4eaf-ad04-e73ba063bf24"},"source":["sport_value_count.reset_index()"],"execution_count":89,"outputs":[{"output_type":"execute_result","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>Sport</th>\n","      <th>0</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>Skiing</td>\n","      <td>1781</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>Ice Hockey</td>\n","      <td>1536</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>Skating</td>\n","      <td>1229</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Bobsleigh</td>\n","      <td>452</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Biathlon</td>\n","      <td>420</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>Luge</td>\n","      <td>180</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>Curling</td>\n","      <td>172</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["        Sport     0\n","0      Skiing  1781\n","1  Ice Hockey  1536\n","2     Skating  1229\n","3   Bobsleigh   452\n","4    Biathlon   420\n","5        Luge   180\n","6     Curling   172"]},"metadata":{"tags":[]},"execution_count":89}]},{"cell_type":"markdown","metadata":{"id":"hgNRWDVxH2yT"},"source":["8) Joins. The country dict is a great example of where you can use a join to connect two DataFrames. Our goal for this question is to join the winter olympics DataFrame with the country dictionary so that every row in the winter olympics dataframe also contains the Country name (not just the country code), Population, and GDP per Capita:\n","\n",">a) Use set_index() on the country dictionary DataFrame and set the index to be the country code.\n","\n",">b) Call .join using the winter olympics DataFrame. The tricky part is deciding what the arguments should be. The first argument should be the DataFrame from a). The join should be done on the \"Country\" column. Give informative suffix values for lsuffix and rsuffix so that there isn't name conflicts. You decide what value should be used for \"how\" so that each row corresponds to a row in the winter olympics DataFrame."]},{"cell_type":"code","metadata":{"id":"5B4aKn7UJMCo","colab":{"base_uri":"https://localhost:8080/","height":450},"executionInfo":{"status":"ok","timestamp":1613926562663,"user_tz":420,"elapsed":538,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"21a3ab15-8998-4ef2-9b1e-8c263972cabb"},"source":["country_dict_df_indexed = country_dict_df.set_index('Code')\n","display(country_dict_df_indexed)"],"execution_count":95,"outputs":[{"output_type":"display_data","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>Country</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</th>\n","    </tr>\n","    <tr>\n","      <th>Code</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>AFG</th>\n","      <td>Afghanistan</td>\n","      <td>32526562.0</td>\n","      <td>594.323081</td>\n","    </tr>\n","    <tr>\n","      <th>ALB</th>\n","      <td>Albania</td>\n","      <td>2889167.0</td>\n","      <td>3945.217582</td>\n","    </tr>\n","    <tr>\n","      <th>ALG</th>\n","      <td>Algeria</td>\n","      <td>39666519.0</td>\n","      <td>4206.031232</td>\n","    </tr>\n","    <tr>\n","      <th>ASA</th>\n","      <td>American Samoa*</td>\n","      <td>55538.0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>AND</th>\n","      <td>Andorra</td>\n","      <td>70473.0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>VIE</th>\n","      <td>Vietnam</td>\n","      <td>91703800.0</td>\n","      <td>2111.138024</td>\n","    </tr>\n","    <tr>\n","      <th>ISV</th>\n","      <td>Virgin Islands*</td>\n","      <td>103574.0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>YEM</th>\n","      <td>Yemen</td>\n","      <td>26832215.0</td>\n","      <td>1406.291651</td>\n","    </tr>\n","    <tr>\n","      <th>ZAM</th>\n","      <td>Zambia</td>\n","      <td>16211767.0</td>\n","      <td>1304.879014</td>\n","    </tr>\n","    <tr>\n","      <th>ZIM</th>\n","      <td>Zimbabwe</td>\n","      <td>15602751.0</td>\n","      <td>924.143819</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>201 rows × 3 columns</p>\n","</div>"],"text/plain":["              Country  Population  GDP per Capita\n","Code                                             \n","AFG       Afghanistan  32526562.0      594.323081\n","ALB           Albania   2889167.0     3945.217582\n","ALG           Algeria  39666519.0     4206.031232\n","ASA   American Samoa*     55538.0             NaN\n","AND           Andorra     70473.0             NaN\n","...               ...         ...             ...\n","VIE           Vietnam  91703800.0     2111.138024\n","ISV   Virgin Islands*    103574.0             NaN\n","YEM             Yemen  26832215.0     1406.291651\n","ZAM            Zambia  16211767.0     1304.879014\n","ZIM          Zimbabwe  15602751.0      924.143819\n","\n","[201 rows x 3 columns]"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":419},"id":"8yN-b2Eahp5z","executionInfo":{"status":"ok","timestamp":1613926678057,"user_tz":420,"elapsed":585,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"5d42a91d-6e2a-4e28-8efd-5cdc2181bfd7"},"source":["winter_df"],"execution_count":96,"outputs":[{"output_type":"execute_result","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>Year</th>\n","      <th>City</th>\n","      <th>Sport</th>\n","      <th>Discipline</th>\n","      <th>Athlete</th>\n","      <th>Country</th>\n","      <th>Gender</th>\n","      <th>Event</th>\n","      <th>Medal</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>BERTHET, G.</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>MANDRILLON, C.</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>MANDRILLON, Maurice</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>VANDELLE, André</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>AUFDENBLATTEN, Adolf</td>\n","      <td>SUI</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Gold</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>5765</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>JONES, Jenny</td>\n","      <td>GBR</td>\n","      <td>Women</td>\n","      <td>Slopestyle</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>5766</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>ANDERSON, Jamie</td>\n","      <td>USA</td>\n","      <td>Women</td>\n","      <td>Slopestyle</td>\n","      <td>Gold</td>\n","    </tr>\n","    <tr>\n","      <th>5767</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>MALTAIS, Dominique</td>\n","      <td>CAN</td>\n","      <td>Women</td>\n","      <td>Snowboard Cross</td>\n","      <td>Silver</td>\n","    </tr>\n","    <tr>\n","      <th>5768</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>SAMKOVA, Eva</td>\n","      <td>CZE</td>\n","      <td>Women</td>\n","      <td>Snowboard Cross</td>\n","      <td>Gold</td>\n","    </tr>\n","    <tr>\n","      <th>5769</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>TRESPEUCH, Chloe</td>\n","      <td>FRA</td>\n","      <td>Women</td>\n","      <td>Snowboard Cross</td>\n","      <td>Bronze</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5770 rows × 9 columns</p>\n","</div>"],"text/plain":["      Year      City     Sport  ... Gender            Event   Medal\n","0     1924  Chamonix  Biathlon  ...    Men  Military Patrol  Bronze\n","1     1924  Chamonix  Biathlon  ...    Men  Military Patrol  Bronze\n","2     1924  Chamonix  Biathlon  ...    Men  Military Patrol  Bronze\n","3     1924  Chamonix  Biathlon  ...    Men  Military Patrol  Bronze\n","4     1924  Chamonix  Biathlon  ...    Men  Military Patrol    Gold\n","...    ...       ...       ...  ...    ...              ...     ...\n","5765  2014     Sochi    Skiing  ...  Women       Slopestyle  Bronze\n","5766  2014     Sochi    Skiing  ...  Women       Slopestyle    Gold\n","5767  2014     Sochi    Skiing  ...  Women  Snowboard Cross  Silver\n","5768  2014     Sochi    Skiing  ...  Women  Snowboard Cross    Gold\n","5769  2014     Sochi    Skiing  ...  Women  Snowboard Cross  Bronze\n","\n","[5770 rows x 9 columns]"]},"metadata":{"tags":[]},"execution_count":96}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":609},"id":"me8JvrvshK0H","executionInfo":{"status":"ok","timestamp":1613926999090,"user_tz":420,"elapsed":618,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"1c5a16c5-6383-431f-d437-f5c65010d8f5"},"source":["winter_df.join(country_dict_df_indexed,on = 'Country', how = \"left\", lsuffix = '_code', rsuffix= '_name')"],"execution_count":103,"outputs":[{"output_type":"execute_result","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>Year</th>\n","      <th>City</th>\n","      <th>Sport</th>\n","      <th>Discipline</th>\n","      <th>Athlete</th>\n","      <th>Country_code</th>\n","      <th>Gender</th>\n","      <th>Event</th>\n","      <th>Medal</th>\n","      <th>Country_name</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>BERTHET, G.</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","      <td>France</td>\n","      <td>66808385.0</td>\n","      <td>36205.568102</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>MANDRILLON, C.</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","      <td>France</td>\n","      <td>66808385.0</td>\n","      <td>36205.568102</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>MANDRILLON, Maurice</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","      <td>France</td>\n","      <td>66808385.0</td>\n","      <td>36205.568102</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>VANDELLE, André</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","      <td>France</td>\n","      <td>66808385.0</td>\n","      <td>36205.568102</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>AUFDENBLATTEN, Adolf</td>\n","      <td>SUI</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Gold</td>\n","      <td>Switzerland</td>\n","      <td>8286976.0</td>\n","      <td>80945.079219</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>5765</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>JONES, Jenny</td>\n","      <td>GBR</td>\n","      <td>Women</td>\n","      <td>Slopestyle</td>\n","      <td>Bronze</td>\n","      <td>United Kingdom</td>\n","      <td>65138232.0</td>\n","      <td>43875.969614</td>\n","    </tr>\n","    <tr>\n","      <th>5766</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>ANDERSON, Jamie</td>\n","      <td>USA</td>\n","      <td>Women</td>\n","      <td>Slopestyle</td>\n","      <td>Gold</td>\n","      <td>United States</td>\n","      <td>321418820.0</td>\n","      <td>56115.718426</td>\n","    </tr>\n","    <tr>\n","      <th>5767</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>MALTAIS, Dominique</td>\n","      <td>CAN</td>\n","      <td>Women</td>\n","      <td>Snowboard Cross</td>\n","      <td>Silver</td>\n","      <td>Canada</td>\n","      <td>35851774.0</td>\n","      <td>43248.529909</td>\n","    </tr>\n","    <tr>\n","      <th>5768</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>SAMKOVA, Eva</td>\n","      <td>CZE</td>\n","      <td>Women</td>\n","      <td>Snowboard Cross</td>\n","      <td>Gold</td>\n","      <td>Czech Republic</td>\n","      <td>10551219.0</td>\n","      <td>17548.338213</td>\n","    </tr>\n","    <tr>\n","      <th>5769</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>TRESPEUCH, Chloe</td>\n","      <td>FRA</td>\n","      <td>Women</td>\n","      <td>Snowboard Cross</td>\n","      <td>Bronze</td>\n","      <td>France</td>\n","      <td>66808385.0</td>\n","      <td>36205.568102</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5770 rows × 12 columns</p>\n","</div>"],"text/plain":["      Year      City     Sport  ...    Country_name   Population GDP per Capita\n","0     1924  Chamonix  Biathlon  ...          France   66808385.0   36205.568102\n","1     1924  Chamonix  Biathlon  ...          France   66808385.0   36205.568102\n","2     1924  Chamonix  Biathlon  ...          France   66808385.0   36205.568102\n","3     1924  Chamonix  Biathlon  ...          France   66808385.0   36205.568102\n","4     1924  Chamonix  Biathlon  ...     Switzerland    8286976.0   80945.079219\n","...    ...       ...       ...  ...             ...          ...            ...\n","5765  2014     Sochi    Skiing  ...  United Kingdom   65138232.0   43875.969614\n","5766  2014     Sochi    Skiing  ...   United States  321418820.0   56115.718426\n","5767  2014     Sochi    Skiing  ...          Canada   35851774.0   43248.529909\n","5768  2014     Sochi    Skiing  ...  Czech Republic   10551219.0   17548.338213\n","5769  2014     Sochi    Skiing  ...          France   66808385.0   36205.568102\n","\n","[5770 rows x 12 columns]"]},"metadata":{"tags":[]},"execution_count":103}]},{"cell_type":"markdown","metadata":{"id":"ZRLGG_xfLUmo"},"source":["9) Apply. The apply method can be very powerful as it allows you to modify or create columns with arbitrary functions. Let's make a new column in the winter olympics DataFrame that contains the Athlete's last name only. Follow these steps:\n",">a) Write a function that takes a string in the format \"x, y\" and returns the \"x\" portion. You can use the .split string method to accomplish this.\n","\n",">b) Call .apply on the Athlete column and give your function you wrote in a) as the argument. Assign the output to a new column named \"athlete_last_name\"."]},{"cell_type":"code","metadata":{"id":"Jt5QTFW1JNzZ","executionInfo":{"status":"ok","timestamp":1613927208840,"user_tz":420,"elapsed":682,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}}},"source":["def extract_Last_Name(full_name):\n","  last_name = full_name.split()[0][:-1]\n","  return last_name"],"execution_count":109,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":419},"id":"p4uPIy_ijQMA","executionInfo":{"status":"ok","timestamp":1613927462418,"user_tz":420,"elapsed":570,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"ade77063-8a39-44ee-ef0c-71f2f7b4d6e2"},"source":["winter_df_last_name = winter_df\n","winter_df_last_name['athlete_last_name'] = winter_df['Athlete'].apply(extract_Last_Name)\n","display(winter_df_last_name)"],"execution_count":117,"outputs":[{"output_type":"display_data","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>Year</th>\n","      <th>City</th>\n","      <th>Sport</th>\n","      <th>Discipline</th>\n","      <th>Athlete</th>\n","      <th>Country</th>\n","      <th>Gender</th>\n","      <th>Event</th>\n","      <th>Medal</th>\n","      <th>athlete_last_name</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>BERTHET, G.</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","      <td>BERTHET</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>MANDRILLON, C.</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","      <td>MANDRILLON</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>MANDRILLON, Maurice</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","      <td>MANDRILLON</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>VANDELLE, André</td>\n","      <td>FRA</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Bronze</td>\n","      <td>VANDELLE</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1924</td>\n","      <td>Chamonix</td>\n","      <td>Biathlon</td>\n","      <td>Biathlon</td>\n","      <td>AUFDENBLATTEN, Adolf</td>\n","      <td>SUI</td>\n","      <td>Men</td>\n","      <td>Military Patrol</td>\n","      <td>Gold</td>\n","      <td>AUFDENBLATTEN</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>5765</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>JONES, Jenny</td>\n","      <td>GBR</td>\n","      <td>Women</td>\n","      <td>Slopestyle</td>\n","      <td>Bronze</td>\n","      <td>JONES</td>\n","    </tr>\n","    <tr>\n","      <th>5766</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>ANDERSON, Jamie</td>\n","      <td>USA</td>\n","      <td>Women</td>\n","      <td>Slopestyle</td>\n","      <td>Gold</td>\n","      <td>ANDERSON</td>\n","    </tr>\n","    <tr>\n","      <th>5767</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>MALTAIS, Dominique</td>\n","      <td>CAN</td>\n","      <td>Women</td>\n","      <td>Snowboard Cross</td>\n","      <td>Silver</td>\n","      <td>MALTAIS</td>\n","    </tr>\n","    <tr>\n","      <th>5768</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>SAMKOVA, Eva</td>\n","      <td>CZE</td>\n","      <td>Women</td>\n","      <td>Snowboard Cross</td>\n","      <td>Gold</td>\n","      <td>SAMKOVA</td>\n","    </tr>\n","    <tr>\n","      <th>5769</th>\n","      <td>2014</td>\n","      <td>Sochi</td>\n","      <td>Skiing</td>\n","      <td>Snowboard</td>\n","      <td>TRESPEUCH, Chloe</td>\n","      <td>FRA</td>\n","      <td>Women</td>\n","      <td>Snowboard Cross</td>\n","      <td>Bronze</td>\n","      <td>TRESPEUCH</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5770 rows × 10 columns</p>\n","</div>"],"text/plain":["      Year      City     Sport  ...            Event   Medal athlete_last_name\n","0     1924  Chamonix  Biathlon  ...  Military Patrol  Bronze           BERTHET\n","1     1924  Chamonix  Biathlon  ...  Military Patrol  Bronze        MANDRILLON\n","2     1924  Chamonix  Biathlon  ...  Military Patrol  Bronze        MANDRILLON\n","3     1924  Chamonix  Biathlon  ...  Military Patrol  Bronze          VANDELLE\n","4     1924  Chamonix  Biathlon  ...  Military Patrol    Gold     AUFDENBLATTEN\n","...    ...       ...       ...  ...              ...     ...               ...\n","5765  2014     Sochi    Skiing  ...       Slopestyle  Bronze             JONES\n","5766  2014     Sochi    Skiing  ...       Slopestyle    Gold          ANDERSON\n","5767  2014     Sochi    Skiing  ...  Snowboard Cross  Silver           MALTAIS\n","5768  2014     Sochi    Skiing  ...  Snowboard Cross    Gold           SAMKOVA\n","5769  2014     Sochi    Skiing  ...  Snowboard Cross  Bronze         TRESPEUCH\n","\n","[5770 rows x 10 columns]"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"uPPLAI-dd0wV"},"source":["## Advanced Questions\n","\n"]},{"cell_type":"markdown","metadata":{"id":"ejlVd9Tvkm_g"},"source":["1) What country has the most medals in the summer olympics overall? Please return the name of the country. Your code should do look up the name of the country from the country codes dictionary."]},{"cell_type":"code","metadata":{"id":"IGsntvTLJRyf","colab":{"base_uri":"https://localhost:8080/","height":37},"executionInfo":{"status":"ok","timestamp":1613927947334,"user_tz":420,"elapsed":770,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"82fbd31c-a559-4697-f092-4d25d58d6bdb"},"source":["country_medal_count = summer_df.value_counts('Country').reset_index()\n","country_medal_count = country_medal_count.join(country_dict_df_indexed, on = 'Country', how = 'left', lsuffix = '_code', rsuffix = '_name')\n","country_medal_count.iat[0,2]"],"execution_count":134,"outputs":[{"output_type":"execute_result","data":{"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"},"text/plain":["'United States'"]},"metadata":{"tags":[]},"execution_count":134}]},{"cell_type":"markdown","metadata":{"id":"sra2rCAcoYZO"},"source":["For each country, what sport have they won the most Gold medals in? Consider\n"," * 2) Just the summer olympics.\n"," * 3) Just the winter olympics.\n"," * 4) Both the summer and winter olympics.\n"," \n","Some bonus goals:\n","\n","*   Think about how to organize your code to avoid repetition\n","*   Display the results with informative column names\n","*   Use full names of the countries\n","*   Ignore countries that are not in the country codes dictionary\n","\n"]},{"cell_type":"code","metadata":{"id":"OxEch-nIJUY9","executionInfo":{"status":"ok","timestamp":1613930387660,"user_tz":420,"elapsed":1050,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}}},"source":["def finding_most_gold(df, type_of_medal = 'Gold', country_df = country_dict_df_indexed):\n","  df = df[df['Medal']== type_of_medal]\n","  df = df.value_counts(['Country','Sport','Medal']).reset_index()\n","  df = df.groupby('Country').max()\n","  df = df.rename(columns = {0:'Count of Medals'})\n","  if isinstance(country_df, pd.DataFrame):\n","    df = df.join(country_dict_df_indexed,on = 'Country', how = \"inner\", lsuffix = '_code', rsuffix= '_name')\n","  \n","  return df\n"],"execution_count":198,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"KcIToh2itOsv","executionInfo":{"status":"ok","timestamp":1613929771720,"user_tz":420,"elapsed":617,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"946e3f1d-1495-4ffa-a414-1a01c5d9fdf7"},"source":["if isinstance(summer_df,pd.DataFrame):\n","  print('Yes')\n","else:\n","  print('No')"],"execution_count":161,"outputs":[{"output_type":"stream","text":["Yes\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"jCehajYSsAjo","executionInfo":{"status":"ok","timestamp":1613930390206,"user_tz":420,"elapsed":642,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"638a7329-d2a3-48f1-aa59-fde087920a92"},"source":["finding_most_gold(summer_df,'Gold')"],"execution_count":199,"outputs":[{"output_type":"execute_result","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>Sport</th>\n","      <th>Medal</th>\n","      <th>Count of Medals</th>\n","      <th>Country</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</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","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>ALG</th>\n","      <td>Boxing</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Algeria</td>\n","      <td>3.966652e+07</td>\n","      <td>4206.031232</td>\n","    </tr>\n","    <tr>\n","      <th>ARG</th>\n","      <td>Taekwondo</td>\n","      <td>Gold</td>\n","      <td>32</td>\n","      <td>Argentina</td>\n","      <td>4.341676e+07</td>\n","      <td>13431.878340</td>\n","    </tr>\n","    <tr>\n","      <th>ARM</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Armenia</td>\n","      <td>3.017712e+06</td>\n","      <td>3489.127690</td>\n","    </tr>\n","    <tr>\n","      <th>AUS</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>121</td>\n","      <td>Australia</td>\n","      <td>2.378117e+07</td>\n","      <td>56310.962993</td>\n","    </tr>\n","    <tr>\n","      <th>AUT</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>5</td>\n","      <td>Austria</td>\n","      <td>8.611088e+06</td>\n","      <td>43774.985174</td>\n","    </tr>\n","    <tr>\n","      <th>AZE</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Azerbaijan</td>\n","      <td>9.651349e+06</td>\n","      <td>5496.344640</td>\n","    </tr>\n","    <tr>\n","      <th>BAH</th>\n","      <td>Sailing</td>\n","      <td>Gold</td>\n","      <td>11</td>\n","      <td>Bahamas</td>\n","      <td>3.880190e+05</td>\n","      <td>22817.230857</td>\n","    </tr>\n","    <tr>\n","      <th>BDI</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Burundi</td>\n","      <td>1.117892e+07</td>\n","      <td>277.068309</td>\n","    </tr>\n","    <tr>\n","      <th>BEL</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>35</td>\n","      <td>Belgium</td>\n","      <td>1.128572e+07</td>\n","      <td>40324.027766</td>\n","    </tr>\n","    <tr>\n","      <th>BLR</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>6</td>\n","      <td>Belarus</td>\n","      <td>9.513000e+06</td>\n","      <td>5740.456495</td>\n","    </tr>\n","    <tr>\n","      <th>BRA</th>\n","      <td>Volleyball</td>\n","      <td>Gold</td>\n","      <td>52</td>\n","      <td>Brazil</td>\n","      <td>2.078475e+08</td>\n","      <td>8538.589975</td>\n","    </tr>\n","    <tr>\n","      <th>BUL</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>16</td>\n","      <td>Bulgaria</td>\n","      <td>7.177991e+06</td>\n","      <td>6993.477360</td>\n","    </tr>\n","    <tr>\n","      <th>CAN</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>50</td>\n","      <td>Canada</td>\n","      <td>3.585177e+07</td>\n","      <td>43248.529909</td>\n","    </tr>\n","    <tr>\n","      <th>CHI</th>\n","      <td>Tennis</td>\n","      <td>Gold</td>\n","      <td>3</td>\n","      <td>Chile</td>\n","      <td>1.794814e+07</td>\n","      <td>13416.230039</td>\n","    </tr>\n","    <tr>\n","      <th>CHN</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>58</td>\n","      <td>China</td>\n","      <td>1.371220e+09</td>\n","      <td>8027.683810</td>\n","    </tr>\n","    <tr>\n","      <th>CMR</th>\n","      <td>Football</td>\n","      <td>Gold</td>\n","      <td>18</td>\n","      <td>Cameroon</td>\n","      <td>2.334418e+07</td>\n","      <td>1217.260670</td>\n","    </tr>\n","    <tr>\n","      <th>COL</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Colombia</td>\n","      <td>4.822870e+07</td>\n","      <td>6056.147717</td>\n","    </tr>\n","    <tr>\n","      <th>CRC</th>\n","      <td>Aquatics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Costa Rica</td>\n","      <td>4.807850e+06</td>\n","      <td>11260.092160</td>\n","    </tr>\n","    <tr>\n","      <th>CRO</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>30</td>\n","      <td>Croatia</td>\n","      <td>4.224404e+06</td>\n","      <td>11535.829356</td>\n","    </tr>\n","    <tr>\n","      <th>CUB</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>63</td>\n","      <td>Cuba</td>\n","      <td>1.138956e+07</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>CZE</th>\n","      <td>Shooting</td>\n","      <td>Gold</td>\n","      <td>5</td>\n","      <td>Czech Republic</td>\n","      <td>1.055122e+07</td>\n","      <td>17548.338213</td>\n","    </tr>\n","    <tr>\n","      <th>DEN</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>46</td>\n","      <td>Denmark</td>\n","      <td>5.676002e+06</td>\n","      <td>51989.293471</td>\n","    </tr>\n","    <tr>\n","      <th>DOM</th>\n","      <td>Boxing</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Dominican Republic</td>\n","      <td>1.052839e+07</td>\n","      <td>6468.473492</td>\n","    </tr>\n","    <tr>\n","      <th>ECU</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Ecuador</td>\n","      <td>1.614436e+07</td>\n","      <td>6205.064145</td>\n","    </tr>\n","    <tr>\n","      <th>EGY</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>5</td>\n","      <td>Egypt</td>\n","      <td>9.150808e+07</td>\n","      <td>3614.746766</td>\n","    </tr>\n","    <tr>\n","      <th>ESP</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>24</td>\n","      <td>Spain</td>\n","      <td>4.641827e+07</td>\n","      <td>25831.582305</td>\n","    </tr>\n","    <tr>\n","      <th>EST</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>5</td>\n","      <td>Estonia</td>\n","      <td>1.311998e+06</td>\n","      <td>17118.504200</td>\n","    </tr>\n","    <tr>\n","      <th>ETH</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>21</td>\n","      <td>Ethiopia</td>\n","      <td>9.939075e+07</td>\n","      <td>619.169406</td>\n","    </tr>\n","    <tr>\n","      <th>FIN</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>60</td>\n","      <td>Finland</td>\n","      <td>5.482013e+06</td>\n","      <td>42311.036231</td>\n","    </tr>\n","    <tr>\n","      <th>FRA</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>116</td>\n","      <td>France</td>\n","      <td>6.680838e+07</td>\n","      <td>36205.568102</td>\n","    </tr>\n","    <tr>\n","      <th>GBR</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>94</td>\n","      <td>United Kingdom</td>\n","      <td>6.513823e+07</td>\n","      <td>43875.969614</td>\n","    </tr>\n","    <tr>\n","      <th>GEO</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>3</td>\n","      <td>Georgia</td>\n","      <td>3.679000e+06</td>\n","      <td>3795.973308</td>\n","    </tr>\n","    <tr>\n","      <th>GER</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>75</td>\n","      <td>Germany</td>\n","      <td>8.141314e+07</td>\n","      <td>41313.313995</td>\n","    </tr>\n","    <tr>\n","      <th>GRE</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>6</td>\n","      <td>Greece</td>\n","      <td>1.082373e+07</td>\n","      <td>18002.230578</td>\n","    </tr>\n","    <tr>\n","      <th>GRN</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Grenada</td>\n","      <td>1.068250e+05</td>\n","      <td>9212.020352</td>\n","    </tr>\n","    <tr>\n","      <th>HKG</th>\n","      <td>Sailing</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Hong Kong*</td>\n","      <td>7.305700e+06</td>\n","      <td>42327.839957</td>\n","    </tr>\n","    <tr>\n","      <th>HUN</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>135</td>\n","      <td>Hungary</td>\n","      <td>9.844686e+06</td>\n","      <td>12363.543460</td>\n","    </tr>\n","    <tr>\n","      <th>INA</th>\n","      <td>Badminton</td>\n","      <td>Gold</td>\n","      <td>9</td>\n","      <td>Indonesia</td>\n","      <td>2.575638e+08</td>\n","      <td>3346.487039</td>\n","    </tr>\n","    <tr>\n","      <th>IND</th>\n","      <td>Shooting</td>\n","      <td>Gold</td>\n","      <td>127</td>\n","      <td>India</td>\n","      <td>1.311051e+09</td>\n","      <td>1598.259034</td>\n","    </tr>\n","    <tr>\n","      <th>IRI</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>8</td>\n","      <td>Iran</td>\n","      <td>7.910927e+07</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>IRL</th>\n","      <td>Boxing</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Ireland</td>\n","      <td>4.640703e+06</td>\n","      <td>61133.672427</td>\n","    </tr>\n","    <tr>\n","      <th>ISR</th>\n","      <td>Sailing</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Israel</td>\n","      <td>8.380400e+06</td>\n","      <td>35728.093495</td>\n","    </tr>\n","    <tr>\n","      <th>ITA</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>145</td>\n","      <td>Italy</td>\n","      <td>6.080208e+07</td>\n","      <td>29957.804315</td>\n","    </tr>\n","    <tr>\n","      <th>JAM</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>31</td>\n","      <td>Jamaica</td>\n","      <td>2.725941e+06</td>\n","      <td>5232.024583</td>\n","    </tr>\n","    <tr>\n","      <th>JPN</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>59</td>\n","      <td>Japan</td>\n","      <td>1.269585e+08</td>\n","      <td>32477.215145</td>\n","    </tr>\n","    <tr>\n","      <th>KAZ</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>6</td>\n","      <td>Kazakhstan</td>\n","      <td>1.754413e+07</td>\n","      <td>10509.981070</td>\n","    </tr>\n","    <tr>\n","      <th>KEN</th>\n","      <td>Boxing</td>\n","      <td>Gold</td>\n","      <td>27</td>\n","      <td>Kenya</td>\n","      <td>4.605030e+07</td>\n","      <td>1376.712829</td>\n","    </tr>\n","    <tr>\n","      <th>KOR</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>41</td>\n","      <td>Korea, South</td>\n","      <td>5.061704e+07</td>\n","      <td>27221.524051</td>\n","    </tr>\n","    <tr>\n","      <th>LAT</th>\n","      <td>Gymnastics</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Latvia</td>\n","      <td>1.978440e+06</td>\n","      <td>13648.547556</td>\n","    </tr>\n","    <tr>\n","      <th>LTU</th>\n","      <td>Shooting</td>\n","      <td>Gold</td>\n","      <td>3</td>\n","      <td>Lithuania</td>\n","      <td>2.910199e+06</td>\n","      <td>14147.049379</td>\n","    </tr>\n","    <tr>\n","      <th>LUX</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Luxembourg</td>\n","      <td>5.696760e+05</td>\n","      <td>101449.968168</td>\n","    </tr>\n","    <tr>\n","      <th>MAR</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>6</td>\n","      <td>Morocco</td>\n","      <td>3.437751e+07</td>\n","      <td>2878.201342</td>\n","    </tr>\n","    <tr>\n","      <th>MEX</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>18</td>\n","      <td>Mexico</td>\n","      <td>1.270172e+08</td>\n","      <td>9005.024265</td>\n","    </tr>\n","    <tr>\n","      <th>MGL</th>\n","      <td>Judo</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Mongolia</td>\n","      <td>2.959134e+06</td>\n","      <td>3967.829386</td>\n","    </tr>\n","    <tr>\n","      <th>MOZ</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Mozambique</td>\n","      <td>2.797786e+07</td>\n","      <td>529.242556</td>\n","    </tr>\n","    <tr>\n","      <th>NED</th>\n","      <td>Volleyball</td>\n","      <td>Gold</td>\n","      <td>80</td>\n","      <td>Netherlands</td>\n","      <td>1.693652e+07</td>\n","      <td>44299.768085</td>\n","    </tr>\n","    <tr>\n","      <th>NGR</th>\n","      <td>Football</td>\n","      <td>Gold</td>\n","      <td>18</td>\n","      <td>Nigeria</td>\n","      <td>1.822020e+08</td>\n","      <td>2640.290739</td>\n","    </tr>\n","    <tr>\n","      <th>NOR</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>81</td>\n","      <td>Norway</td>\n","      <td>5.195921e+06</td>\n","      <td>74400.369777</td>\n","    </tr>\n","    <tr>\n","      <th>NZL</th>\n","      <td>Triathlon</td>\n","      <td>Gold</td>\n","      <td>28</td>\n","      <td>New Zealand</td>\n","      <td>4.595700e+06</td>\n","      <td>37807.967276</td>\n","    </tr>\n","    <tr>\n","      <th>PAK</th>\n","      <td>Hockey</td>\n","      <td>Gold</td>\n","      <td>42</td>\n","      <td>Pakistan</td>\n","      <td>1.889249e+08</td>\n","      <td>1434.696665</td>\n","    </tr>\n","    <tr>\n","      <th>PAN</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Panama</td>\n","      <td>3.929141e+06</td>\n","      <td>13268.113755</td>\n","    </tr>\n","    <tr>\n","      <th>PER</th>\n","      <td>Shooting</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Peru</td>\n","      <td>3.137667e+07</td>\n","      <td>6027.125855</td>\n","    </tr>\n","    <tr>\n","      <th>POL</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>27</td>\n","      <td>Poland</td>\n","      <td>3.799949e+07</td>\n","      <td>12554.547554</td>\n","    </tr>\n","    <tr>\n","      <th>POR</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Portugal</td>\n","      <td>1.034865e+07</td>\n","      <td>19222.150076</td>\n","    </tr>\n","    <tr>\n","      <th>PRK</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Korea, North</td>\n","      <td>2.515532e+07</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>RSA</th>\n","      <td>Tennis</td>\n","      <td>Gold</td>\n","      <td>9</td>\n","      <td>South Africa</td>\n","      <td>5.495692e+07</td>\n","      <td>5723.973357</td>\n","    </tr>\n","    <tr>\n","      <th>RUS</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>54</td>\n","      <td>Russia</td>\n","      <td>1.440968e+08</td>\n","      <td>9092.580536</td>\n","    </tr>\n","    <tr>\n","      <th>SLO</th>\n","      <td>Shooting</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Slovenia</td>\n","      <td>2.063768e+06</td>\n","      <td>20726.539886</td>\n","    </tr>\n","    <tr>\n","      <th>SUI</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>23</td>\n","      <td>Switzerland</td>\n","      <td>8.286976e+06</td>\n","      <td>80945.079219</td>\n","    </tr>\n","    <tr>\n","      <th>SUR</th>\n","      <td>Aquatics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Suriname</td>\n","      <td>5.429750e+05</td>\n","      <td>9485.319244</td>\n","    </tr>\n","    <tr>\n","      <th>SVK</th>\n","      <td>Canoe / Kayak</td>\n","      <td>Gold</td>\n","      <td>10</td>\n","      <td>Slovakia</td>\n","      <td>5.424050e+06</td>\n","      <td>16088.277587</td>\n","    </tr>\n","    <tr>\n","      <th>SWE</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>116</td>\n","      <td>Sweden</td>\n","      <td>9.798871e+06</td>\n","      <td>50579.673649</td>\n","    </tr>\n","    <tr>\n","      <th>SYR</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Syria</td>\n","      <td>1.850241e+07</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>THA</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Thailand</td>\n","      <td>6.795936e+07</td>\n","      <td>5814.769764</td>\n","    </tr>\n","    <tr>\n","      <th>TPE</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Taiwan</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>TRI</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Trinidad and Tobago</td>\n","      <td>1.360088e+06</td>\n","      <td>17321.884675</td>\n","    </tr>\n","    <tr>\n","      <th>TUN</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Tunisia</td>\n","      <td>1.110780e+07</td>\n","      <td>3872.512084</td>\n","    </tr>\n","    <tr>\n","      <th>TUR</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>28</td>\n","      <td>Turkey</td>\n","      <td>7.866583e+07</td>\n","      <td>9125.687590</td>\n","    </tr>\n","    <tr>\n","      <th>UAE</th>\n","      <td>Shooting</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>United Arab Emirates</td>\n","      <td>9.156963e+06</td>\n","      <td>40438.762934</td>\n","    </tr>\n","    <tr>\n","      <th>UGA</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Uganda</td>\n","      <td>3.903238e+07</td>\n","      <td>705.292570</td>\n","    </tr>\n","    <tr>\n","      <th>UKR</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>6</td>\n","      <td>Ukraine</td>\n","      <td>4.519820e+07</td>\n","      <td>2114.954716</td>\n","    </tr>\n","    <tr>\n","      <th>URU</th>\n","      <td>Football</td>\n","      <td>Gold</td>\n","      <td>44</td>\n","      <td>Uruguay</td>\n","      <td>3.431555e+06</td>\n","      <td>15573.900919</td>\n","    </tr>\n","    <tr>\n","      <th>USA</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>578</td>\n","      <td>United States</td>\n","      <td>3.214188e+08</td>\n","      <td>56115.718426</td>\n","    </tr>\n","    <tr>\n","      <th>UZB</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Uzbekistan</td>\n","      <td>3.129950e+07</td>\n","      <td>2132.070368</td>\n","    </tr>\n","    <tr>\n","      <th>VEN</th>\n","      <td>Fencing</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Venezuela</td>\n","      <td>3.110808e+07</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>ZIM</th>\n","      <td>Hockey</td>\n","      <td>Gold</td>\n","      <td>16</td>\n","      <td>Zimbabwe</td>\n","      <td>1.560275e+07</td>\n","      <td>924.143819</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                 Sport Medal  ...    Population GDP per Capita\n","Country                       ...                             \n","ALG             Boxing  Gold  ...  3.966652e+07    4206.031232\n","ARG          Taekwondo  Gold  ...  4.341676e+07   13431.878340\n","ARM          Wrestling  Gold  ...  3.017712e+06    3489.127690\n","AUS      Weightlifting  Gold  ...  2.378117e+07   56310.962993\n","AUT      Weightlifting  Gold  ...  8.611088e+06   43774.985174\n","AZE          Wrestling  Gold  ...  9.651349e+06    5496.344640\n","BAH            Sailing  Gold  ...  3.880190e+05   22817.230857\n","BDI          Athletics  Gold  ...  1.117892e+07     277.068309\n","BEL      Weightlifting  Gold  ...  1.128572e+07   40324.027766\n","BLR      Weightlifting  Gold  ...  9.513000e+06    5740.456495\n","BRA         Volleyball  Gold  ...  2.078475e+08    8538.589975\n","BUL          Wrestling  Gold  ...  7.177991e+06    6993.477360\n","CAN          Wrestling  Gold  ...  3.585177e+07   43248.529909\n","CHI             Tennis  Gold  ...  1.794814e+07   13416.230039\n","CHN          Wrestling  Gold  ...  1.371220e+09    8027.683810\n","CMR           Football  Gold  ...  2.334418e+07    1217.260670\n","COL      Weightlifting  Gold  ...  4.822870e+07    6056.147717\n","CRC           Aquatics  Gold  ...  4.807850e+06   11260.092160\n","CRO      Weightlifting  Gold  ...  4.224404e+06   11535.829356\n","CUB          Wrestling  Gold  ...  1.138956e+07            NaN\n","CZE           Shooting  Gold  ...  1.055122e+07   17548.338213\n","DEN      Weightlifting  Gold  ...  5.676002e+06   51989.293471\n","DOM             Boxing  Gold  ...  1.052839e+07    6468.473492\n","ECU          Athletics  Gold  ...  1.614436e+07    6205.064145\n","EGY          Wrestling  Gold  ...  9.150808e+07    3614.746766\n","ESP      Weightlifting  Gold  ...  4.641827e+07   25831.582305\n","EST          Wrestling  Gold  ...  1.311998e+06   17118.504200\n","ETH          Athletics  Gold  ...  9.939075e+07     619.169406\n","FIN          Wrestling  Gold  ...  5.482013e+06   42311.036231\n","FRA          Wrestling  Gold  ...  6.680838e+07   36205.568102\n","GBR          Wrestling  Gold  ...  6.513823e+07   43875.969614\n","GEO          Wrestling  Gold  ...  3.679000e+06    3795.973308\n","GER          Wrestling  Gold  ...  8.141314e+07   41313.313995\n","GRE          Wrestling  Gold  ...  1.082373e+07   18002.230578\n","GRN          Athletics  Gold  ...  1.068250e+05    9212.020352\n","HKG            Sailing  Gold  ...  7.305700e+06   42327.839957\n","HUN          Wrestling  Gold  ...  9.844686e+06   12363.543460\n","INA          Badminton  Gold  ...  2.575638e+08    3346.487039\n","IND           Shooting  Gold  ...  1.311051e+09    1598.259034\n","IRI          Wrestling  Gold  ...  7.910927e+07            NaN\n","IRL             Boxing  Gold  ...  4.640703e+06   61133.672427\n","ISR            Sailing  Gold  ...  8.380400e+06   35728.093495\n","ITA          Wrestling  Gold  ...  6.080208e+07   29957.804315\n","JAM          Athletics  Gold  ...  2.725941e+06    5232.024583\n","JPN          Wrestling  Gold  ...  1.269585e+08   32477.215145\n","KAZ          Wrestling  Gold  ...  1.754413e+07   10509.981070\n","KEN             Boxing  Gold  ...  4.605030e+07    1376.712829\n","KOR          Wrestling  Gold  ...  5.061704e+07   27221.524051\n","LAT         Gymnastics  Gold  ...  1.978440e+06   13648.547556\n","LTU           Shooting  Gold  ...  2.910199e+06   14147.049379\n","LUX          Athletics  Gold  ...  5.696760e+05  101449.968168\n","MAR          Athletics  Gold  ...  3.437751e+07    2878.201342\n","MEX      Weightlifting  Gold  ...  1.270172e+08    9005.024265\n","MGL               Judo  Gold  ...  2.959134e+06    3967.829386\n","MOZ          Athletics  Gold  ...  2.797786e+07     529.242556\n","NED         Volleyball  Gold  ...  1.693652e+07   44299.768085\n","NGR           Football  Gold  ...  1.822020e+08    2640.290739\n","NOR          Wrestling  Gold  ...  5.195921e+06   74400.369777\n","NZL          Triathlon  Gold  ...  4.595700e+06   37807.967276\n","PAK             Hockey  Gold  ...  1.889249e+08    1434.696665\n","PAN          Athletics  Gold  ...  3.929141e+06   13268.113755\n","PER           Shooting  Gold  ...  3.137667e+07    6027.125855\n","POL          Wrestling  Gold  ...  3.799949e+07   12554.547554\n","POR          Athletics  Gold  ...  1.034865e+07   19222.150076\n","PRK          Wrestling  Gold  ...  2.515532e+07            NaN\n","RSA             Tennis  Gold  ...  5.495692e+07    5723.973357\n","RUS          Wrestling  Gold  ...  1.440968e+08    9092.580536\n","SLO           Shooting  Gold  ...  2.063768e+06   20726.539886\n","SUI          Wrestling  Gold  ...  8.286976e+06   80945.079219\n","SUR           Aquatics  Gold  ...  5.429750e+05    9485.319244\n","SVK      Canoe / Kayak  Gold  ...  5.424050e+06   16088.277587\n","SWE          Wrestling  Gold  ...  9.798871e+06   50579.673649\n","SYR          Athletics  Gold  ...  1.850241e+07            NaN\n","THA      Weightlifting  Gold  ...  6.795936e+07    5814.769764\n","TPE      Weightlifting  Gold  ...           NaN            NaN\n","TRI          Athletics  Gold  ...  1.360088e+06   17321.884675\n","TUN          Athletics  Gold  ...  1.110780e+07    3872.512084\n","TUR          Wrestling  Gold  ...  7.866583e+07    9125.687590\n","UAE           Shooting  Gold  ...  9.156963e+06   40438.762934\n","UGA          Athletics  Gold  ...  3.903238e+07     705.292570\n","UKR          Wrestling  Gold  ...  4.519820e+07    2114.954716\n","URU           Football  Gold  ...  3.431555e+06   15573.900919\n","USA          Wrestling  Gold  ...  3.214188e+08   56115.718426\n","UZB          Wrestling  Gold  ...  3.129950e+07    2132.070368\n","VEN            Fencing  Gold  ...  3.110808e+07            NaN\n","ZIM             Hockey  Gold  ...  1.560275e+07     924.143819\n","\n","[86 rows x 6 columns]"]},"metadata":{"tags":[]},"execution_count":199}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"StcN5IsbsHFm","executionInfo":{"status":"ok","timestamp":1613930407209,"user_tz":420,"elapsed":631,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"91274ba4-15c4-47f3-a395-a3658df77f16"},"source":["finding_most_gold(winter_df)"],"execution_count":200,"outputs":[{"output_type":"execute_result","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>Sport</th>\n","      <th>Medal</th>\n","      <th>Count of Medals</th>\n","      <th>Country</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</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","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>AUS</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Australia</td>\n","      <td>2.378117e+07</td>\n","      <td>56310.962993</td>\n","    </tr>\n","    <tr>\n","      <th>AUT</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>57</td>\n","      <td>Austria</td>\n","      <td>8.611088e+06</td>\n","      <td>43774.985174</td>\n","    </tr>\n","    <tr>\n","      <th>BEL</th>\n","      <td>Skating</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Belgium</td>\n","      <td>1.128572e+07</td>\n","      <td>40324.027766</td>\n","    </tr>\n","    <tr>\n","      <th>BLR</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>3</td>\n","      <td>Belarus</td>\n","      <td>9.513000e+06</td>\n","      <td>5740.456495</td>\n","    </tr>\n","    <tr>\n","      <th>BUL</th>\n","      <td>Biathlon</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Bulgaria</td>\n","      <td>7.177991e+06</td>\n","      <td>6993.477360</td>\n","    </tr>\n","    <tr>\n","      <th>CAN</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>220</td>\n","      <td>Canada</td>\n","      <td>3.585177e+07</td>\n","      <td>43248.529909</td>\n","    </tr>\n","    <tr>\n","      <th>CHN</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>15</td>\n","      <td>China</td>\n","      <td>1.371220e+09</td>\n","      <td>8027.683810</td>\n","    </tr>\n","    <tr>\n","      <th>CRO</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Croatia</td>\n","      <td>4.224404e+06</td>\n","      <td>11535.829356</td>\n","    </tr>\n","    <tr>\n","      <th>CZE</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>22</td>\n","      <td>Czech Republic</td>\n","      <td>1.055122e+07</td>\n","      <td>17548.338213</td>\n","    </tr>\n","    <tr>\n","      <th>ESP</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Spain</td>\n","      <td>4.641827e+07</td>\n","      <td>25831.582305</td>\n","    </tr>\n","    <tr>\n","      <th>EST</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Estonia</td>\n","      <td>1.311998e+06</td>\n","      <td>17118.504200</td>\n","    </tr>\n","    <tr>\n","      <th>FIN</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>59</td>\n","      <td>Finland</td>\n","      <td>5.482013e+06</td>\n","      <td>42311.036231</td>\n","    </tr>\n","    <tr>\n","      <th>FRA</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>22</td>\n","      <td>France</td>\n","      <td>6.680838e+07</td>\n","      <td>36205.568102</td>\n","    </tr>\n","    <tr>\n","      <th>GBR</th>\n","      <td>Skating</td>\n","      <td>Gold</td>\n","      <td>13</td>\n","      <td>United Kingdom</td>\n","      <td>6.513823e+07</td>\n","      <td>43875.969614</td>\n","    </tr>\n","    <tr>\n","      <th>GER</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>35</td>\n","      <td>Germany</td>\n","      <td>8.141314e+07</td>\n","      <td>41313.313995</td>\n","    </tr>\n","    <tr>\n","      <th>ITA</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>28</td>\n","      <td>Italy</td>\n","      <td>6.080208e+07</td>\n","      <td>29957.804315</td>\n","    </tr>\n","    <tr>\n","      <th>JPN</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>13</td>\n","      <td>Japan</td>\n","      <td>1.269585e+08</td>\n","      <td>32477.215145</td>\n","    </tr>\n","    <tr>\n","      <th>KAZ</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Kazakhstan</td>\n","      <td>1.754413e+07</td>\n","      <td>10509.981070</td>\n","    </tr>\n","    <tr>\n","      <th>KOR</th>\n","      <td>Skating</td>\n","      <td>Gold</td>\n","      <td>51</td>\n","      <td>Korea, South</td>\n","      <td>5.061704e+07</td>\n","      <td>27221.524051</td>\n","    </tr>\n","    <tr>\n","      <th>LIE</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Liechtenstein</td>\n","      <td>3.753100e+04</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>NED</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>41</td>\n","      <td>Netherlands</td>\n","      <td>1.693652e+07</td>\n","      <td>44299.768085</td>\n","    </tr>\n","    <tr>\n","      <th>NOR</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>102</td>\n","      <td>Norway</td>\n","      <td>5.195921e+06</td>\n","      <td>74400.369777</td>\n","    </tr>\n","    <tr>\n","      <th>POL</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>5</td>\n","      <td>Poland</td>\n","      <td>3.799949e+07</td>\n","      <td>12554.547554</td>\n","    </tr>\n","    <tr>\n","      <th>RUS</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>40</td>\n","      <td>Russia</td>\n","      <td>1.440968e+08</td>\n","      <td>9092.580536</td>\n","    </tr>\n","    <tr>\n","      <th>SLO</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Slovenia</td>\n","      <td>2.063768e+06</td>\n","      <td>20726.539886</td>\n","    </tr>\n","    <tr>\n","      <th>SUI</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>38</td>\n","      <td>Switzerland</td>\n","      <td>8.286976e+06</td>\n","      <td>80945.079219</td>\n","    </tr>\n","    <tr>\n","      <th>SVK</th>\n","      <td>Biathlon</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Slovakia</td>\n","      <td>5.424050e+06</td>\n","      <td>16088.277587</td>\n","    </tr>\n","    <tr>\n","      <th>SWE</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>59</td>\n","      <td>Sweden</td>\n","      <td>9.798871e+06</td>\n","      <td>50579.673649</td>\n","    </tr>\n","    <tr>\n","      <th>UKR</th>\n","      <td>Skating</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Ukraine</td>\n","      <td>4.519820e+07</td>\n","      <td>2114.954716</td>\n","    </tr>\n","    <tr>\n","      <th>USA</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>56</td>\n","      <td>United States</td>\n","      <td>3.214188e+08</td>\n","      <td>56115.718426</td>\n","    </tr>\n","    <tr>\n","      <th>UZB</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Uzbekistan</td>\n","      <td>3.129950e+07</td>\n","      <td>2132.070368</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["            Sport Medal  ...    Population GDP per Capita\n","Country                  ...                             \n","AUS        Skiing  Gold  ...  2.378117e+07   56310.962993\n","AUT        Skiing  Gold  ...  8.611088e+06   43774.985174\n","BEL       Skating  Gold  ...  1.128572e+07   40324.027766\n","BLR        Skiing  Gold  ...  9.513000e+06    5740.456495\n","BUL      Biathlon  Gold  ...  7.177991e+06    6993.477360\n","CAN        Skiing  Gold  ...  3.585177e+07   43248.529909\n","CHN        Skiing  Gold  ...  1.371220e+09    8027.683810\n","CRO        Skiing  Gold  ...  4.224404e+06   11535.829356\n","CZE        Skiing  Gold  ...  1.055122e+07   17548.338213\n","ESP        Skiing  Gold  ...  4.641827e+07   25831.582305\n","EST        Skiing  Gold  ...  1.311998e+06   17118.504200\n","FIN        Skiing  Gold  ...  5.482013e+06   42311.036231\n","FRA        Skiing  Gold  ...  6.680838e+07   36205.568102\n","GBR       Skating  Gold  ...  6.513823e+07   43875.969614\n","GER        Skiing  Gold  ...  8.141314e+07   41313.313995\n","ITA        Skiing  Gold  ...  6.080208e+07   29957.804315\n","JPN        Skiing  Gold  ...  1.269585e+08   32477.215145\n","KAZ        Skiing  Gold  ...  1.754413e+07   10509.981070\n","KOR       Skating  Gold  ...  5.061704e+07   27221.524051\n","LIE        Skiing  Gold  ...  3.753100e+04            NaN\n","NED        Skiing  Gold  ...  1.693652e+07   44299.768085\n","NOR        Skiing  Gold  ...  5.195921e+06   74400.369777\n","POL        Skiing  Gold  ...  3.799949e+07   12554.547554\n","RUS        Skiing  Gold  ...  1.440968e+08    9092.580536\n","SLO        Skiing  Gold  ...  2.063768e+06   20726.539886\n","SUI        Skiing  Gold  ...  8.286976e+06   80945.079219\n","SVK      Biathlon  Gold  ...  5.424050e+06   16088.277587\n","SWE        Skiing  Gold  ...  9.798871e+06   50579.673649\n","UKR       Skating  Gold  ...  4.519820e+07    2114.954716\n","USA        Skiing  Gold  ...  3.214188e+08   56115.718426\n","UZB        Skiing  Gold  ...  3.129950e+07    2132.070368\n","\n","[31 rows x 6 columns]"]},"metadata":{"tags":[]},"execution_count":200}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"bFxM4Myisc7V","executionInfo":{"status":"ok","timestamp":1613930408884,"user_tz":420,"elapsed":613,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"a6a31ded-bd77-4ed0-ed10-f8b18ef465e1"},"source":["finding_most_gold(summer_df.append(winter_df).reset_index())"],"execution_count":201,"outputs":[{"output_type":"execute_result","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>Sport</th>\n","      <th>Medal</th>\n","      <th>Count of Medals</th>\n","      <th>Country</th>\n","      <th>Population</th>\n","      <th>GDP per Capita</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","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>ALG</th>\n","      <td>Boxing</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Algeria</td>\n","      <td>3.966652e+07</td>\n","      <td>4206.031232</td>\n","    </tr>\n","    <tr>\n","      <th>ARG</th>\n","      <td>Taekwondo</td>\n","      <td>Gold</td>\n","      <td>32</td>\n","      <td>Argentina</td>\n","      <td>4.341676e+07</td>\n","      <td>13431.878340</td>\n","    </tr>\n","    <tr>\n","      <th>ARM</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Armenia</td>\n","      <td>3.017712e+06</td>\n","      <td>3489.127690</td>\n","    </tr>\n","    <tr>\n","      <th>AUS</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>121</td>\n","      <td>Australia</td>\n","      <td>2.378117e+07</td>\n","      <td>56310.962993</td>\n","    </tr>\n","    <tr>\n","      <th>AUT</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>57</td>\n","      <td>Austria</td>\n","      <td>8.611088e+06</td>\n","      <td>43774.985174</td>\n","    </tr>\n","    <tr>\n","      <th>AZE</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Azerbaijan</td>\n","      <td>9.651349e+06</td>\n","      <td>5496.344640</td>\n","    </tr>\n","    <tr>\n","      <th>BAH</th>\n","      <td>Sailing</td>\n","      <td>Gold</td>\n","      <td>11</td>\n","      <td>Bahamas</td>\n","      <td>3.880190e+05</td>\n","      <td>22817.230857</td>\n","    </tr>\n","    <tr>\n","      <th>BDI</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Burundi</td>\n","      <td>1.117892e+07</td>\n","      <td>277.068309</td>\n","    </tr>\n","    <tr>\n","      <th>BEL</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>35</td>\n","      <td>Belgium</td>\n","      <td>1.128572e+07</td>\n","      <td>40324.027766</td>\n","    </tr>\n","    <tr>\n","      <th>BLR</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>6</td>\n","      <td>Belarus</td>\n","      <td>9.513000e+06</td>\n","      <td>5740.456495</td>\n","    </tr>\n","    <tr>\n","      <th>BRA</th>\n","      <td>Volleyball</td>\n","      <td>Gold</td>\n","      <td>52</td>\n","      <td>Brazil</td>\n","      <td>2.078475e+08</td>\n","      <td>8538.589975</td>\n","    </tr>\n","    <tr>\n","      <th>BUL</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>16</td>\n","      <td>Bulgaria</td>\n","      <td>7.177991e+06</td>\n","      <td>6993.477360</td>\n","    </tr>\n","    <tr>\n","      <th>CAN</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>228</td>\n","      <td>Canada</td>\n","      <td>3.585177e+07</td>\n","      <td>43248.529909</td>\n","    </tr>\n","    <tr>\n","      <th>CHI</th>\n","      <td>Tennis</td>\n","      <td>Gold</td>\n","      <td>3</td>\n","      <td>Chile</td>\n","      <td>1.794814e+07</td>\n","      <td>13416.230039</td>\n","    </tr>\n","    <tr>\n","      <th>CHN</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>58</td>\n","      <td>China</td>\n","      <td>1.371220e+09</td>\n","      <td>8027.683810</td>\n","    </tr>\n","    <tr>\n","      <th>CMR</th>\n","      <td>Football</td>\n","      <td>Gold</td>\n","      <td>18</td>\n","      <td>Cameroon</td>\n","      <td>2.334418e+07</td>\n","      <td>1217.260670</td>\n","    </tr>\n","    <tr>\n","      <th>COL</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Colombia</td>\n","      <td>4.822870e+07</td>\n","      <td>6056.147717</td>\n","    </tr>\n","    <tr>\n","      <th>CRC</th>\n","      <td>Aquatics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Costa Rica</td>\n","      <td>4.807850e+06</td>\n","      <td>11260.092160</td>\n","    </tr>\n","    <tr>\n","      <th>CRO</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>30</td>\n","      <td>Croatia</td>\n","      <td>4.224404e+06</td>\n","      <td>11535.829356</td>\n","    </tr>\n","    <tr>\n","      <th>CUB</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>63</td>\n","      <td>Cuba</td>\n","      <td>1.138956e+07</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>CZE</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>22</td>\n","      <td>Czech Republic</td>\n","      <td>1.055122e+07</td>\n","      <td>17548.338213</td>\n","    </tr>\n","    <tr>\n","      <th>DEN</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>46</td>\n","      <td>Denmark</td>\n","      <td>5.676002e+06</td>\n","      <td>51989.293471</td>\n","    </tr>\n","    <tr>\n","      <th>DOM</th>\n","      <td>Boxing</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Dominican Republic</td>\n","      <td>1.052839e+07</td>\n","      <td>6468.473492</td>\n","    </tr>\n","    <tr>\n","      <th>ECU</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Ecuador</td>\n","      <td>1.614436e+07</td>\n","      <td>6205.064145</td>\n","    </tr>\n","    <tr>\n","      <th>EGY</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>5</td>\n","      <td>Egypt</td>\n","      <td>9.150808e+07</td>\n","      <td>3614.746766</td>\n","    </tr>\n","    <tr>\n","      <th>ESP</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>24</td>\n","      <td>Spain</td>\n","      <td>4.641827e+07</td>\n","      <td>25831.582305</td>\n","    </tr>\n","    <tr>\n","      <th>EST</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>5</td>\n","      <td>Estonia</td>\n","      <td>1.311998e+06</td>\n","      <td>17118.504200</td>\n","    </tr>\n","    <tr>\n","      <th>ETH</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>21</td>\n","      <td>Ethiopia</td>\n","      <td>9.939075e+07</td>\n","      <td>619.169406</td>\n","    </tr>\n","    <tr>\n","      <th>FIN</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>60</td>\n","      <td>Finland</td>\n","      <td>5.482013e+06</td>\n","      <td>42311.036231</td>\n","    </tr>\n","    <tr>\n","      <th>FRA</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>116</td>\n","      <td>France</td>\n","      <td>6.680838e+07</td>\n","      <td>36205.568102</td>\n","    </tr>\n","    <tr>\n","      <th>GBR</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>94</td>\n","      <td>United Kingdom</td>\n","      <td>6.513823e+07</td>\n","      <td>43875.969614</td>\n","    </tr>\n","    <tr>\n","      <th>GEO</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>3</td>\n","      <td>Georgia</td>\n","      <td>3.679000e+06</td>\n","      <td>3795.973308</td>\n","    </tr>\n","    <tr>\n","      <th>GER</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>75</td>\n","      <td>Germany</td>\n","      <td>8.141314e+07</td>\n","      <td>41313.313995</td>\n","    </tr>\n","    <tr>\n","      <th>GRE</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>6</td>\n","      <td>Greece</td>\n","      <td>1.082373e+07</td>\n","      <td>18002.230578</td>\n","    </tr>\n","    <tr>\n","      <th>GRN</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Grenada</td>\n","      <td>1.068250e+05</td>\n","      <td>9212.020352</td>\n","    </tr>\n","    <tr>\n","      <th>HKG</th>\n","      <td>Sailing</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Hong Kong*</td>\n","      <td>7.305700e+06</td>\n","      <td>42327.839957</td>\n","    </tr>\n","    <tr>\n","      <th>HUN</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>135</td>\n","      <td>Hungary</td>\n","      <td>9.844686e+06</td>\n","      <td>12363.543460</td>\n","    </tr>\n","    <tr>\n","      <th>INA</th>\n","      <td>Badminton</td>\n","      <td>Gold</td>\n","      <td>9</td>\n","      <td>Indonesia</td>\n","      <td>2.575638e+08</td>\n","      <td>3346.487039</td>\n","    </tr>\n","    <tr>\n","      <th>IND</th>\n","      <td>Shooting</td>\n","      <td>Gold</td>\n","      <td>127</td>\n","      <td>India</td>\n","      <td>1.311051e+09</td>\n","      <td>1598.259034</td>\n","    </tr>\n","    <tr>\n","      <th>IRI</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>8</td>\n","      <td>Iran</td>\n","      <td>7.910927e+07</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>IRL</th>\n","      <td>Boxing</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Ireland</td>\n","      <td>4.640703e+06</td>\n","      <td>61133.672427</td>\n","    </tr>\n","    <tr>\n","      <th>ISR</th>\n","      <td>Sailing</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Israel</td>\n","      <td>8.380400e+06</td>\n","      <td>35728.093495</td>\n","    </tr>\n","    <tr>\n","      <th>ITA</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>145</td>\n","      <td>Italy</td>\n","      <td>6.080208e+07</td>\n","      <td>29957.804315</td>\n","    </tr>\n","    <tr>\n","      <th>JAM</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>31</td>\n","      <td>Jamaica</td>\n","      <td>2.725941e+06</td>\n","      <td>5232.024583</td>\n","    </tr>\n","    <tr>\n","      <th>JPN</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>59</td>\n","      <td>Japan</td>\n","      <td>1.269585e+08</td>\n","      <td>32477.215145</td>\n","    </tr>\n","    <tr>\n","      <th>KAZ</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>6</td>\n","      <td>Kazakhstan</td>\n","      <td>1.754413e+07</td>\n","      <td>10509.981070</td>\n","    </tr>\n","    <tr>\n","      <th>KEN</th>\n","      <td>Boxing</td>\n","      <td>Gold</td>\n","      <td>27</td>\n","      <td>Kenya</td>\n","      <td>4.605030e+07</td>\n","      <td>1376.712829</td>\n","    </tr>\n","    <tr>\n","      <th>KOR</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>51</td>\n","      <td>Korea, South</td>\n","      <td>5.061704e+07</td>\n","      <td>27221.524051</td>\n","    </tr>\n","    <tr>\n","      <th>LAT</th>\n","      <td>Gymnastics</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Latvia</td>\n","      <td>1.978440e+06</td>\n","      <td>13648.547556</td>\n","    </tr>\n","    <tr>\n","      <th>LIE</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Liechtenstein</td>\n","      <td>3.753100e+04</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>LTU</th>\n","      <td>Shooting</td>\n","      <td>Gold</td>\n","      <td>3</td>\n","      <td>Lithuania</td>\n","      <td>2.910199e+06</td>\n","      <td>14147.049379</td>\n","    </tr>\n","    <tr>\n","      <th>LUX</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Luxembourg</td>\n","      <td>5.696760e+05</td>\n","      <td>101449.968168</td>\n","    </tr>\n","    <tr>\n","      <th>MAR</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>6</td>\n","      <td>Morocco</td>\n","      <td>3.437751e+07</td>\n","      <td>2878.201342</td>\n","    </tr>\n","    <tr>\n","      <th>MEX</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>18</td>\n","      <td>Mexico</td>\n","      <td>1.270172e+08</td>\n","      <td>9005.024265</td>\n","    </tr>\n","    <tr>\n","      <th>MGL</th>\n","      <td>Judo</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Mongolia</td>\n","      <td>2.959134e+06</td>\n","      <td>3967.829386</td>\n","    </tr>\n","    <tr>\n","      <th>MOZ</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Mozambique</td>\n","      <td>2.797786e+07</td>\n","      <td>529.242556</td>\n","    </tr>\n","    <tr>\n","      <th>NED</th>\n","      <td>Volleyball</td>\n","      <td>Gold</td>\n","      <td>80</td>\n","      <td>Netherlands</td>\n","      <td>1.693652e+07</td>\n","      <td>44299.768085</td>\n","    </tr>\n","    <tr>\n","      <th>NGR</th>\n","      <td>Football</td>\n","      <td>Gold</td>\n","      <td>18</td>\n","      <td>Nigeria</td>\n","      <td>1.822020e+08</td>\n","      <td>2640.290739</td>\n","    </tr>\n","    <tr>\n","      <th>NOR</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>102</td>\n","      <td>Norway</td>\n","      <td>5.195921e+06</td>\n","      <td>74400.369777</td>\n","    </tr>\n","    <tr>\n","      <th>NZL</th>\n","      <td>Triathlon</td>\n","      <td>Gold</td>\n","      <td>28</td>\n","      <td>New Zealand</td>\n","      <td>4.595700e+06</td>\n","      <td>37807.967276</td>\n","    </tr>\n","    <tr>\n","      <th>PAK</th>\n","      <td>Hockey</td>\n","      <td>Gold</td>\n","      <td>42</td>\n","      <td>Pakistan</td>\n","      <td>1.889249e+08</td>\n","      <td>1434.696665</td>\n","    </tr>\n","    <tr>\n","      <th>PAN</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Panama</td>\n","      <td>3.929141e+06</td>\n","      <td>13268.113755</td>\n","    </tr>\n","    <tr>\n","      <th>PER</th>\n","      <td>Shooting</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Peru</td>\n","      <td>3.137667e+07</td>\n","      <td>6027.125855</td>\n","    </tr>\n","    <tr>\n","      <th>POL</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>27</td>\n","      <td>Poland</td>\n","      <td>3.799949e+07</td>\n","      <td>12554.547554</td>\n","    </tr>\n","    <tr>\n","      <th>POR</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Portugal</td>\n","      <td>1.034865e+07</td>\n","      <td>19222.150076</td>\n","    </tr>\n","    <tr>\n","      <th>PRK</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Korea, North</td>\n","      <td>2.515532e+07</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>RSA</th>\n","      <td>Tennis</td>\n","      <td>Gold</td>\n","      <td>9</td>\n","      <td>South Africa</td>\n","      <td>5.495692e+07</td>\n","      <td>5723.973357</td>\n","    </tr>\n","    <tr>\n","      <th>RUS</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>54</td>\n","      <td>Russia</td>\n","      <td>1.440968e+08</td>\n","      <td>9092.580536</td>\n","    </tr>\n","    <tr>\n","      <th>SLO</th>\n","      <td>Skiing</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Slovenia</td>\n","      <td>2.063768e+06</td>\n","      <td>20726.539886</td>\n","    </tr>\n","    <tr>\n","      <th>SUI</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>38</td>\n","      <td>Switzerland</td>\n","      <td>8.286976e+06</td>\n","      <td>80945.079219</td>\n","    </tr>\n","    <tr>\n","      <th>SUR</th>\n","      <td>Aquatics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Suriname</td>\n","      <td>5.429750e+05</td>\n","      <td>9485.319244</td>\n","    </tr>\n","    <tr>\n","      <th>SVK</th>\n","      <td>Canoe / Kayak</td>\n","      <td>Gold</td>\n","      <td>10</td>\n","      <td>Slovakia</td>\n","      <td>5.424050e+06</td>\n","      <td>16088.277587</td>\n","    </tr>\n","    <tr>\n","      <th>SWE</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>116</td>\n","      <td>Sweden</td>\n","      <td>9.798871e+06</td>\n","      <td>50579.673649</td>\n","    </tr>\n","    <tr>\n","      <th>SYR</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Syria</td>\n","      <td>1.850241e+07</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>THA</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Thailand</td>\n","      <td>6.795936e+07</td>\n","      <td>5814.769764</td>\n","    </tr>\n","    <tr>\n","      <th>TPE</th>\n","      <td>Weightlifting</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Taiwan</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>TRI</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Trinidad and Tobago</td>\n","      <td>1.360088e+06</td>\n","      <td>17321.884675</td>\n","    </tr>\n","    <tr>\n","      <th>TUN</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Tunisia</td>\n","      <td>1.110780e+07</td>\n","      <td>3872.512084</td>\n","    </tr>\n","    <tr>\n","      <th>TUR</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>28</td>\n","      <td>Turkey</td>\n","      <td>7.866583e+07</td>\n","      <td>9125.687590</td>\n","    </tr>\n","    <tr>\n","      <th>UAE</th>\n","      <td>Shooting</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>United Arab Emirates</td>\n","      <td>9.156963e+06</td>\n","      <td>40438.762934</td>\n","    </tr>\n","    <tr>\n","      <th>UGA</th>\n","      <td>Athletics</td>\n","      <td>Gold</td>\n","      <td>2</td>\n","      <td>Uganda</td>\n","      <td>3.903238e+07</td>\n","      <td>705.292570</td>\n","    </tr>\n","    <tr>\n","      <th>UKR</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>6</td>\n","      <td>Ukraine</td>\n","      <td>4.519820e+07</td>\n","      <td>2114.954716</td>\n","    </tr>\n","    <tr>\n","      <th>URU</th>\n","      <td>Football</td>\n","      <td>Gold</td>\n","      <td>44</td>\n","      <td>Uruguay</td>\n","      <td>3.431555e+06</td>\n","      <td>15573.900919</td>\n","    </tr>\n","    <tr>\n","      <th>USA</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>578</td>\n","      <td>United States</td>\n","      <td>3.214188e+08</td>\n","      <td>56115.718426</td>\n","    </tr>\n","    <tr>\n","      <th>UZB</th>\n","      <td>Wrestling</td>\n","      <td>Gold</td>\n","      <td>4</td>\n","      <td>Uzbekistan</td>\n","      <td>3.129950e+07</td>\n","      <td>2132.070368</td>\n","    </tr>\n","    <tr>\n","      <th>VEN</th>\n","      <td>Fencing</td>\n","      <td>Gold</td>\n","      <td>1</td>\n","      <td>Venezuela</td>\n","      <td>3.110808e+07</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>ZIM</th>\n","      <td>Hockey</td>\n","      <td>Gold</td>\n","      <td>16</td>\n","      <td>Zimbabwe</td>\n","      <td>1.560275e+07</td>\n","      <td>924.143819</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                 Sport Medal  ...    Population GDP per Capita\n","Country                       ...                             \n","ALG             Boxing  Gold  ...  3.966652e+07    4206.031232\n","ARG          Taekwondo  Gold  ...  4.341676e+07   13431.878340\n","ARM          Wrestling  Gold  ...  3.017712e+06    3489.127690\n","AUS      Weightlifting  Gold  ...  2.378117e+07   56310.962993\n","AUT      Weightlifting  Gold  ...  8.611088e+06   43774.985174\n","AZE          Wrestling  Gold  ...  9.651349e+06    5496.344640\n","BAH            Sailing  Gold  ...  3.880190e+05   22817.230857\n","BDI          Athletics  Gold  ...  1.117892e+07     277.068309\n","BEL      Weightlifting  Gold  ...  1.128572e+07   40324.027766\n","BLR      Weightlifting  Gold  ...  9.513000e+06    5740.456495\n","BRA         Volleyball  Gold  ...  2.078475e+08    8538.589975\n","BUL          Wrestling  Gold  ...  7.177991e+06    6993.477360\n","CAN          Wrestling  Gold  ...  3.585177e+07   43248.529909\n","CHI             Tennis  Gold  ...  1.794814e+07   13416.230039\n","CHN          Wrestling  Gold  ...  1.371220e+09    8027.683810\n","CMR           Football  Gold  ...  2.334418e+07    1217.260670\n","COL      Weightlifting  Gold  ...  4.822870e+07    6056.147717\n","CRC           Aquatics  Gold  ...  4.807850e+06   11260.092160\n","CRO      Weightlifting  Gold  ...  4.224404e+06   11535.829356\n","CUB          Wrestling  Gold  ...  1.138956e+07            NaN\n","CZE             Skiing  Gold  ...  1.055122e+07   17548.338213\n","DEN      Weightlifting  Gold  ...  5.676002e+06   51989.293471\n","DOM             Boxing  Gold  ...  1.052839e+07    6468.473492\n","ECU          Athletics  Gold  ...  1.614436e+07    6205.064145\n","EGY          Wrestling  Gold  ...  9.150808e+07    3614.746766\n","ESP      Weightlifting  Gold  ...  4.641827e+07   25831.582305\n","EST          Wrestling  Gold  ...  1.311998e+06   17118.504200\n","ETH          Athletics  Gold  ...  9.939075e+07     619.169406\n","FIN          Wrestling  Gold  ...  5.482013e+06   42311.036231\n","FRA          Wrestling  Gold  ...  6.680838e+07   36205.568102\n","GBR          Wrestling  Gold  ...  6.513823e+07   43875.969614\n","GEO          Wrestling  Gold  ...  3.679000e+06    3795.973308\n","GER          Wrestling  Gold  ...  8.141314e+07   41313.313995\n","GRE          Wrestling  Gold  ...  1.082373e+07   18002.230578\n","GRN          Athletics  Gold  ...  1.068250e+05    9212.020352\n","HKG            Sailing  Gold  ...  7.305700e+06   42327.839957\n","HUN          Wrestling  Gold  ...  9.844686e+06   12363.543460\n","INA          Badminton  Gold  ...  2.575638e+08    3346.487039\n","IND           Shooting  Gold  ...  1.311051e+09    1598.259034\n","IRI          Wrestling  Gold  ...  7.910927e+07            NaN\n","IRL             Boxing  Gold  ...  4.640703e+06   61133.672427\n","ISR            Sailing  Gold  ...  8.380400e+06   35728.093495\n","ITA          Wrestling  Gold  ...  6.080208e+07   29957.804315\n","JAM          Athletics  Gold  ...  2.725941e+06    5232.024583\n","JPN          Wrestling  Gold  ...  1.269585e+08   32477.215145\n","KAZ          Wrestling  Gold  ...  1.754413e+07   10509.981070\n","KEN             Boxing  Gold  ...  4.605030e+07    1376.712829\n","KOR          Wrestling  Gold  ...  5.061704e+07   27221.524051\n","LAT         Gymnastics  Gold  ...  1.978440e+06   13648.547556\n","LIE             Skiing  Gold  ...  3.753100e+04            NaN\n","LTU           Shooting  Gold  ...  2.910199e+06   14147.049379\n","LUX          Athletics  Gold  ...  5.696760e+05  101449.968168\n","MAR          Athletics  Gold  ...  3.437751e+07    2878.201342\n","MEX      Weightlifting  Gold  ...  1.270172e+08    9005.024265\n","MGL               Judo  Gold  ...  2.959134e+06    3967.829386\n","MOZ          Athletics  Gold  ...  2.797786e+07     529.242556\n","NED         Volleyball  Gold  ...  1.693652e+07   44299.768085\n","NGR           Football  Gold  ...  1.822020e+08    2640.290739\n","NOR          Wrestling  Gold  ...  5.195921e+06   74400.369777\n","NZL          Triathlon  Gold  ...  4.595700e+06   37807.967276\n","PAK             Hockey  Gold  ...  1.889249e+08    1434.696665\n","PAN          Athletics  Gold  ...  3.929141e+06   13268.113755\n","PER           Shooting  Gold  ...  3.137667e+07    6027.125855\n","POL          Wrestling  Gold  ...  3.799949e+07   12554.547554\n","POR          Athletics  Gold  ...  1.034865e+07   19222.150076\n","PRK          Wrestling  Gold  ...  2.515532e+07            NaN\n","RSA             Tennis  Gold  ...  5.495692e+07    5723.973357\n","RUS          Wrestling  Gold  ...  1.440968e+08    9092.580536\n","SLO             Skiing  Gold  ...  2.063768e+06   20726.539886\n","SUI          Wrestling  Gold  ...  8.286976e+06   80945.079219\n","SUR           Aquatics  Gold  ...  5.429750e+05    9485.319244\n","SVK      Canoe / Kayak  Gold  ...  5.424050e+06   16088.277587\n","SWE          Wrestling  Gold  ...  9.798871e+06   50579.673649\n","SYR          Athletics  Gold  ...  1.850241e+07            NaN\n","THA      Weightlifting  Gold  ...  6.795936e+07    5814.769764\n","TPE      Weightlifting  Gold  ...           NaN            NaN\n","TRI          Athletics  Gold  ...  1.360088e+06   17321.884675\n","TUN          Athletics  Gold  ...  1.110780e+07    3872.512084\n","TUR          Wrestling  Gold  ...  7.866583e+07    9125.687590\n","UAE           Shooting  Gold  ...  9.156963e+06   40438.762934\n","UGA          Athletics  Gold  ...  3.903238e+07     705.292570\n","UKR          Wrestling  Gold  ...  4.519820e+07    2114.954716\n","URU           Football  Gold  ...  3.431555e+06   15573.900919\n","USA          Wrestling  Gold  ...  3.214188e+08   56115.718426\n","UZB          Wrestling  Gold  ...  3.129950e+07    2132.070368\n","VEN            Fencing  Gold  ...  3.110808e+07            NaN\n","ZIM             Hockey  Gold  ...  1.560275e+07     924.143819\n","\n","[87 rows x 6 columns]"]},"metadata":{"tags":[]},"execution_count":201}]},{"cell_type":"markdown","metadata":{"id":"597P9sad04XC"},"source":["5) For each country, what is the average medal count for each gender? The average should be across years. This time report the average taking both summer and winter olympics into account."]},{"cell_type":"code","metadata":{"id":"yXvrDbfnJWe6"},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"KK_WtwGHHdBK"},"source":["6) Get the top 5 athletes in terms of how many separate olympics they have appeared at? (NOT the most medals). Use both the winter and summer olympics. Treat the winter and summer olympics as separate olympics."]},{"cell_type":"code","metadata":{"id":"luNcu2JmJYT3"},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"mlDBbHBiFGHU"},"source":["Optional: 7) Come up with your own analytical question. What interesting things can you ask the data? Use pandas to answer the question. If possible, elaborate how the answer could be used."]},{"cell_type":"code","metadata":{"id":"BASVuAs4JZiE"},"source":[""],"execution_count":null,"outputs":[]}]}