{"cells":[{"cell_type":"code","source":"! pip install https://github.com/pandas-profiling/pandas-profiling/archive/master.zip ","metadata":{"id":"ESqgwo4bCTKn","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"60ff962187bd4cc898e1bade5170ea9c","outputId":"36f8da63-f8bb-427c-958b-e80b33d46a0f","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":33486,"user_tz":180,"timestamp":1647389198267},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"Collecting https://github.com/pandas-profiling/pandas-profiling/archive/master.zip\n  Downloading https://github.com/pandas-profiling/pandas-profiling/archive/master.zip\n\u001b[K     \\ 25.9 MB 245 kB/s\n\u001b[?25hRequirement already satisfied: joblib~=1.1.0 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling==3.1.1) 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(2.11.3)\nRequirement already satisfied: markupsafe~=2.0.1 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling==3.1.1) (2.0.1)\nCollecting visions[type_image_path]==0.7.4\n  Downloading visions-0.7.4-py3-none-any.whl (102 kB)\n\u001b[K     |████████████████████████████████| 102 kB 7.8 MB/s \n\u001b[?25hRequirement already satisfied: numpy>=1.16.0 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling==3.1.1) (1.21.5)\nCollecting htmlmin>=0.1.12\n  Downloading htmlmin-0.1.12.tar.gz (19 kB)\nRequirement already satisfied: missingno>=0.4.2 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling==3.1.1) (0.5.1)\nCollecting phik>=0.11.1\n  Downloading phik-0.12.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (687 kB)\n\u001b[K     |████████████████████████████████| 687 kB 56.5 MB/s \n\u001b[?25hCollecting tangled-up-in-unicode==0.2.0\n  Downloading tangled_up_in_unicode-0.2.0-py3-none-any.whl (4.7 MB)\n\u001b[K     |████████████████████████████████| 4.7 MB 58.6 MB/s \n\u001b[?25hCollecting requests>=2.24.0\n  Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB)\n\u001b[K     |████████████████████████████████| 63 kB 567 kB/s \n\u001b[?25hRequirement already satisfied: tqdm>=4.48.2 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling==3.1.1) (4.63.0)\nRequirement already satisfied: seaborn>=0.10.1 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling==3.1.1) (0.11.2)\nCollecting multimethod>=1.4\n  Downloading multimethod-1.7-py3-none-any.whl (9.5 kB)\nRequirement already satisfied: networkx>=2.4 in /usr/local/lib/python3.7/dist-packages (from visions[type_image_path]==0.7.4->pandas-profiling==3.1.1) (2.6.3)\nRequirement already satisfied: attrs>=19.3.0 in /usr/local/lib/python3.7/dist-packages (from visions[type_image_path]==0.7.4->pandas-profiling==3.1.1) (21.4.0)\nRequirement already satisfied: Pillow in /usr/local/lib/python3.7/dist-packages (from visions[type_image_path]==0.7.4->pandas-profiling==3.1.1) (7.1.2)\nCollecting imagehash\n  Downloading ImageHash-4.2.1.tar.gz (812 kB)\n\u001b[K     |████████████████████████████████| 812 kB 42.7 MB/s \n\u001b[?25hRequirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.2.0->pandas-profiling==3.1.1) (0.11.0)\nRequirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.2.0->pandas-profiling==3.1.1) (3.0.7)\nRequirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.2.0->pandas-profiling==3.1.1) (2.8.2)\nRequirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.2.0->pandas-profiling==3.1.1) (1.3.2)\nRequirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas!=1.0.0,!=1.0.1,!=1.0.2,!=1.1.0,>=0.25.3->pandas-profiling==3.1.1) (2018.9)\nCollecting scipy>=1.4.1\n  Downloading scipy-1.7.3-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (38.1 MB)\n\u001b[K     |████████████████████████████████| 38.1 MB 1.3 MB/s \n\u001b[?25hRequirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from pydantic>=1.8.1->pandas-profiling==3.1.1) (3.10.0.2)\nRequirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.1->matplotlib>=3.2.0->pandas-profiling==3.1.1) (1.15.0)\nRequirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.24.0->pandas-profiling==3.1.1) (2021.10.8)\nRequirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.7/dist-packages (from requests>=2.24.0->pandas-profiling==3.1.1) (2.0.12)\nRequirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.24.0->pandas-profiling==3.1.1) (1.24.3)\nRequirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.24.0->pandas-profiling==3.1.1) (2.10)\nRequirement already satisfied: PyWavelets in /usr/local/lib/python3.7/dist-packages (from imagehash->visions[type_image_path]==0.7.4->pandas-profiling==3.1.1) (1.2.0)\nBuilding wheels for collected packages: pandas-profiling, htmlmin, imagehash\n  Building wheel for pandas-profiling (setup.py) ... \u001b[?25l\u001b[?25hdone\n  Created wheel for pandas-profiling: filename=pandas_profiling-3.1.1-py2.py3-none-any.whl size=261287 sha256=34d39bcc7b6c3ae2571a1cd05fa1167d7f75416338c572ca4e37e7847d5ce05a\n  Stored in directory: /tmp/pip-ephem-wheel-cache-bu0fvnco/wheels/cc/d5/09/083fb07c9363a2f45854b0e3a7de7d7c560f07da74b9e9769d\n  Building wheel for htmlmin (setup.py) ... \u001b[?25l\u001b[?25hdone\n  Created wheel for htmlmin: filename=htmlmin-0.1.12-py3-none-any.whl size=27098 sha256=48224fd6f1f84c73b2068ee6d70373c4e67a2646b2e5e0fe43f9ac1a703f5084\n  Stored in directory: /root/.cache/pip/wheels/70/e1/52/5b14d250ba868768823940c3229e9950d201a26d0bd3ee8655\n  Building wheel for imagehash (setup.py) ... \u001b[?25l\u001b[?25hdone\n  Created wheel for imagehash: filename=ImageHash-4.2.1-py2.py3-none-any.whl size=295206 sha256=2434f9cce976c917ce949c4cf82343d43e90058257ae023a1fa523eb8f2af5bf\n  Stored in directory: /root/.cache/pip/wheels/4c/d5/59/5e3e297533ddb09407769762985d134135064c6831e29a914e\nSuccessfully built pandas-profiling htmlmin imagehash\nInstalling collected packages: tangled-up-in-unicode, scipy, multimethod, visions, imagehash, requests, PyYAML, pydantic, phik, htmlmin, pandas-profiling\n  Attempting uninstall: scipy\n    Found existing installation: scipy 1.4.1\n    Uninstalling scipy-1.4.1:\n      Successfully uninstalled scipy-1.4.1\n  Attempting uninstall: requests\n    Found existing installation: requests 2.23.0\n    Uninstalling requests-2.23.0:\n      Successfully uninstalled requests-2.23.0\n  Attempting uninstall: PyYAML\n    Found existing installation: PyYAML 3.13\n    Uninstalling PyYAML-3.13:\n      Successfully uninstalled PyYAML-3.13\n  Attempting uninstall: pandas-profiling\n    Found existing installation: pandas-profiling 1.4.1\n    Uninstalling pandas-profiling-1.4.1:\n      Successfully uninstalled pandas-profiling-1.4.1\n\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\ngoogle-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.27.1 which is incompatible.\ndatascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\nalbumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001b[0m\nSuccessfully installed PyYAML-6.0 htmlmin-0.1.12 imagehash-4.2.1 multimethod-1.7 pandas-profiling-3.1.1 phik-0.12.1 pydantic-1.9.0 requests-2.27.1 scipy-1.7.3 tangled-up-in-unicode-0.2.0 visions-0.7.4\n"}],"execution_count":2},{"cell_type":"markdown","source":"Ahora se debe reiniciar el kernel (**Importante**)\n","metadata":{"id":"LIE04-x5CWPx","cell_id":"3afba6650c834588afc8deb1d07e9437","deepnote_cell_type":"markdown"}},{"cell_type":"markdown","source":"# Ejemplo 1","metadata":{"id":"ecxu71guBtPe","cell_id":"82398165f9eb4c0c9655ded05d91d894","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"from google.colab import drive\nimport os\ndrive.mount('/content/gdrive')\n# Establecer ruta de acceso en drive\nimport os\nprint(os.getcwd())\nos.chdir(\"/content/gdrive/My Drive\")","metadata":{"id":"_YueCvPdBFFy","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"72c1793325ae4e089f8ab143e5c92203","outputId":"a1f94be3-6f37-4f8a-c8ed-d8ed42b88df4","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":2784,"user_tz":180,"timestamp":1647389245396},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n/content\n"}],"execution_count":3},{"cell_type":"code","source":"#Importamos las librerias\n\n# Operaciones Basicas\nimport numpy as np\nimport pandas as pd\nimport pandas_profiling\n\n# Visualizacion de Datos\nimport matplotlib.pyplot as plt\nimport seaborn as sns","metadata":{"id":"7TiJwJbZA8Vb","cell_id":"8ba9b3041674490984fd2a88e30f9bac","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":410,"user_tz":180,"timestamp":1647389248037},"deepnote_cell_type":"code"},"outputs":[],"execution_count":4},{"cell_type":"code","source":"#Lectura del dataframe\ndata = pd.read_csv('heart.csv')\ndata.head()","metadata":{"id":"asKZtNFJA8Ve","colab":{"height":206,"base_uri":"https://localhost:8080/"},"cell_id":"3d4c4da17a5149e1aef4fee0c0c4610f","outputId":"8b31b287-74f9-4464-c27d-4cf6c5a82e75","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":569,"user_tz":180,"timestamp":1647389250281},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n0   63    1   3       145   233    1        0      150      0      2.3      0   \n1   37    1   2       130   250    0        1      187      0      3.5      0   \n2   41    0   1       130   204    0        0      172      0      1.4      2   \n3   56    1   1       120   236    0        1      178      0      0.8      2   \n4   57    0   0       120   354    0        1      163      1      0.6      2   \n\n   ca  thal  target  \n0   0     1       1  \n1   0     2       1  \n2   0     2       1  \n3   0     2       1  \n4   0     2       1  ","text/html":"\n  <div id=\"df-a9d15881-4cb7-4bac-bbe2-69910418b505\">\n    <div class=\"colab-df-container\">\n      <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>age</th>\n      <th>sex</th>\n      <th>cp</th>\n      <th>trestbps</th>\n      <th>chol</th>\n      <th>fbs</th>\n      <th>restecg</th>\n      <th>thalach</th>\n      <th>exang</th>\n      <th>oldpeak</th>\n      <th>slope</th>\n      <th>ca</th>\n      <th>thal</th>\n      <th>target</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>63</td>\n      <td>1</td>\n      <td>3</td>\n      <td>145</td>\n      <td>233</td>\n      <td>1</td>\n      <td>0</td>\n      <td>150</td>\n      <td>0</td>\n      <td>2.3</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>37</td>\n      <td>1</td>\n      <td>2</td>\n      <td>130</td>\n      <td>250</td>\n      <td>0</td>\n      <td>1</td>\n      <td>187</td>\n      <td>0</td>\n      <td>3.5</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>41</td>\n      <td>0</td>\n      <td>1</td>\n      <td>130</td>\n      <td>204</td>\n      <td>0</td>\n      <td>0</td>\n      <td>172</td>\n      <td>0</td>\n      <td>1.4</td>\n      <td>2</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>56</td>\n      <td>1</td>\n      <td>1</td>\n      <td>120</td>\n      <td>236</td>\n      <td>0</td>\n      <td>1</td>\n      <td>178</td>\n      <td>0</td>\n      <td>0.8</td>\n      <td>2</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>57</td>\n      <td>0</td>\n      <td>0</td>\n      <td>120</td>\n      <td>354</td>\n      <td>0</td>\n      <td>1</td>\n      <td>163</td>\n      <td>1</td>\n      <td>0.6</td>\n      <td>2</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a9d15881-4cb7-4bac-bbe2-69910418b505')\"\n              title=\"Convert this dataframe to an interactive table.\"\n              style=\"display:none;\">\n        \n  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n       width=\"24px\">\n    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n  </svg>\n      </button>\n      \n  <style>\n    .colab-df-container {\n      display:flex;\n      flex-wrap:wrap;\n      gap: 12px;\n    }\n\n    .colab-df-convert {\n      background-color: #E8F0FE;\n      border: none;\n      border-radius: 50%;\n      cursor: pointer;\n      display: none;\n      fill: #1967D2;\n      height: 32px;\n      padding: 0 0 0 0;\n      width: 32px;\n    }\n\n    .colab-df-convert:hover {\n      background-color: #E2EBFA;\n      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n      fill: #174EA6;\n    }\n\n    [theme=dark] .colab-df-convert {\n      background-color: #3B4455;\n      fill: #D2E3FC;\n    }\n\n    [theme=dark] .colab-df-convert:hover {\n      background-color: #434B5C;\n      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n      fill: #FFFFFF;\n    }\n  </style>\n\n      <script>\n        const buttonEl =\n          document.querySelector('#df-a9d15881-4cb7-4bac-bbe2-69910418b505 button.colab-df-convert');\n        buttonEl.style.display =\n          google.colab.kernel.accessAllowed ? 'block' : 'none';\n\n        async function convertToInteractive(key) {\n          const element = document.querySelector('#df-a9d15881-4cb7-4bac-bbe2-69910418b505');\n          const dataTable =\n            await google.colab.kernel.invokeFunction('convertToInteractive',\n                                                     [key], {});\n          if (!dataTable) return;\n\n          const docLinkHtml = 'Like what you see? Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  "},"metadata":{},"execution_count":5}],"execution_count":5},{"cell_type":"code","source":"#Veamos el shape\ndata.shape","metadata":{"id":"7lNbf35sA8Vg","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"7c73fc8b29ef485c926bc0e4c2a51d56","outputId":"9587724c-0329-4fcd-f72f-3d96bfe85878","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":571,"user_tz":180,"timestamp":1647389254146},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"(303, 14)"},"metadata":{},"execution_count":6}],"execution_count":6},{"cell_type":"code","source":"#Totalidad de registros por columnas\ndata.count()","metadata":{"id":"sHqBa7xHA8Vh","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"ee02b2e2c5c7465f926acf5cf2bf645c","outputId":"f2d2de50-1d7e-4f75-d14a-eb24a3e28d12","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":524,"user_tz":180,"timestamp":1647389255929},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"age         303\nsex         303\ncp          303\ntrestbps    303\nchol        303\nfbs         303\nrestecg     303\nthalach     303\nexang       303\noldpeak     303\nslope       303\nca          303\nthal        303\ntarget      303\ndtype: int64"},"metadata":{},"execution_count":7}],"execution_count":7},{"cell_type":"code","source":"#Tipo de dato de cada columna\ndata.dtypes","metadata":{"id":"QpgczxdXA8Vi","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"c5749c6562c443de9c9b97434b61c997","outputId":"c2f89d9d-f053-46e0-9b10-f8352e021b8b","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":8,"user_tz":180,"timestamp":1647389257460},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"age           int64\nsex           int64\ncp            int64\ntrestbps      int64\nchol          int64\nfbs           int64\nrestecg       int64\nthalach       int64\nexang         int64\noldpeak     float64\nslope         int64\nca            int64\nthal          int64\ntarget        int64\ndtype: object"},"metadata":{},"execution_count":8}],"execution_count":8},{"cell_type":"code","source":"#Tipo de estructura del dataset\ntype(data)","metadata":{"id":"XYOibsXBA8Vj","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"f3bcc8567f6a420ab7263340d271c153","outputId":"ebdb5f52-c592-4299-c61d-87062326224f","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":7,"user_tz":180,"timestamp":1647389259017},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"pandas.core.frame.DataFrame"},"metadata":{},"execution_count":9}],"execution_count":9},{"cell_type":"code","source":"#Principales medidas estadisticas\ndata.describe().T","metadata":{"id":"24no7Qp7A8Vk","colab":{"height":489,"base_uri":"https://localhost:8080/"},"cell_id":"49ab34b633304668983e380244b750e7","outputId":"1aa024b3-e2ee-40aa-f250-624500b99b31","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":13,"user_tz":180,"timestamp":1647389260547},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"          count        mean        std    min    25%    50%    75%    max\nage       303.0   54.366337   9.082101   29.0   47.5   55.0   61.0   77.0\nsex       303.0    0.683168   0.466011    0.0    0.0    1.0    1.0    1.0\ncp        303.0    0.966997   1.032052    0.0    0.0    1.0    2.0    3.0\ntrestbps  303.0  131.623762  17.538143   94.0  120.0  130.0  140.0  200.0\nchol      303.0  246.264026  51.830751  126.0  211.0  240.0  274.5  564.0\nfbs       303.0    0.148515   0.356198    0.0    0.0    0.0    0.0    1.0\nrestecg   303.0    0.528053   0.525860    0.0    0.0    1.0    1.0    2.0\nthalach   303.0  149.646865  22.905161   71.0  133.5  153.0  166.0  202.0\nexang     303.0    0.326733   0.469794    0.0    0.0    0.0    1.0    1.0\noldpeak   303.0    1.039604   1.161075    0.0    0.0    0.8    1.6    6.2\nslope     303.0    1.399340   0.616226    0.0    1.0    1.0    2.0    2.0\nca        303.0    0.729373   1.022606    0.0    0.0    0.0    1.0    4.0\nthal      303.0    2.313531   0.612277    0.0    2.0    2.0    3.0    3.0\ntarget    303.0    0.544554   0.498835    0.0    0.0    1.0    1.0    1.0","text/html":"\n  <div id=\"df-38bf6983-21b7-462e-aa90-d6d195aa1720\">\n    <div class=\"colab-df-container\">\n      <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>count</th>\n      <th>mean</th>\n      <th>std</th>\n      <th>min</th>\n      <th>25%</th>\n      <th>50%</th>\n      <th>75%</th>\n      <th>max</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>age</th>\n      <td>303.0</td>\n      <td>54.366337</td>\n      <td>9.082101</td>\n      <td>29.0</td>\n      <td>47.5</td>\n      <td>55.0</td>\n      <td>61.0</td>\n      <td>77.0</td>\n    </tr>\n    <tr>\n      <th>sex</th>\n      <td>303.0</td>\n      <td>0.683168</td>\n      <td>0.466011</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>cp</th>\n      <td>303.0</td>\n      <td>0.966997</td>\n      <td>1.032052</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>2.0</td>\n      <td>3.0</td>\n    </tr>\n    <tr>\n      <th>trestbps</th>\n      <td>303.0</td>\n      <td>131.623762</td>\n      <td>17.538143</td>\n      <td>94.0</td>\n      <td>120.0</td>\n      <td>130.0</td>\n      <td>140.0</td>\n      <td>200.0</td>\n    </tr>\n    <tr>\n      <th>chol</th>\n      <td>303.0</td>\n      <td>246.264026</td>\n      <td>51.830751</td>\n      <td>126.0</td>\n      <td>211.0</td>\n      <td>240.0</td>\n      <td>274.5</td>\n      <td>564.0</td>\n    </tr>\n    <tr>\n      <th>fbs</th>\n      <td>303.0</td>\n      <td>0.148515</td>\n      <td>0.356198</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>restecg</th>\n      <td>303.0</td>\n      <td>0.528053</td>\n      <td>0.525860</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>2.0</td>\n    </tr>\n    <tr>\n      <th>thalach</th>\n      <td>303.0</td>\n      <td>149.646865</td>\n      <td>22.905161</td>\n      <td>71.0</td>\n      <td>133.5</td>\n      <td>153.0</td>\n      <td>166.0</td>\n      <td>202.0</td>\n    </tr>\n    <tr>\n      <th>exang</th>\n      <td>303.0</td>\n      <td>0.326733</td>\n      <td>0.469794</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>oldpeak</th>\n      <td>303.0</td>\n      <td>1.039604</td>\n      <td>1.161075</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.8</td>\n      <td>1.6</td>\n      <td>6.2</td>\n    </tr>\n    <tr>\n      <th>slope</th>\n      <td>303.0</td>\n      <td>1.399340</td>\n      <td>0.616226</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n    </tr>\n    <tr>\n      <th>ca</th>\n      <td>303.0</td>\n      <td>0.729373</td>\n      <td>1.022606</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>4.0</td>\n    </tr>\n    <tr>\n      <th>thal</th>\n      <td>303.0</td>\n      <td>2.313531</td>\n      <td>0.612277</td>\n      <td>0.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n    </tr>\n    <tr>\n      <th>target</th>\n      <td>303.0</td>\n      <td>0.544554</td>\n      <td>0.498835</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-38bf6983-21b7-462e-aa90-d6d195aa1720')\"\n              title=\"Convert this dataframe to an interactive table.\"\n              style=\"display:none;\">\n        \n  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n       width=\"24px\">\n    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 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#3B4455;\n      fill: #D2E3FC;\n    }\n\n    [theme=dark] .colab-df-convert:hover {\n      background-color: #434B5C;\n      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n      fill: #FFFFFF;\n    }\n  </style>\n\n      <script>\n        const buttonEl =\n          document.querySelector('#df-38bf6983-21b7-462e-aa90-d6d195aa1720 button.colab-df-convert');\n        buttonEl.style.display =\n          google.colab.kernel.accessAllowed ? 'block' : 'none';\n\n        async function convertToInteractive(key) {\n          const element = document.querySelector('#df-38bf6983-21b7-462e-aa90-d6d195aa1720');\n          const dataTable =\n            await google.colab.kernel.invokeFunction('convertToInteractive',\n                                                     [key], {});\n          if (!dataTable) return;\n\n          const docLinkHtml = 'Like what you see? Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  "},"metadata":{},"execution_count":10}],"execution_count":10},{"cell_type":"code","source":"#Data Profiling\nprofile = pandas_profiling.ProfileReport(data)\nprofile","metadata":{"id":"-yi-OgAjA8Vk","colab":{"height":917,"base_uri":"https://localhost:8080/","referenced_widgets":["e7508ece71c446dabad0561533964b29","ac430facc2cc4a9e99d2040e7703c039","dabc98c2ca1c488794b7a3bb8a70bd2d","274c54b6e42144538a4f84a4e633e954","d028d4203e964b5c94fa97607106f7e4","3eaff7f963954c00b8b745e924755e39","9fa2a296198b41a58fb97e250e62e456","f861c710bd3340708fbae131de1abc0c","e9fb13f1173b4c18a6697345e3f51cd5","fcdcbc9a645042998bc670974f603ecd","693db04badb84ab18c1e1f3da49ed9ce","402f7b6f02734776862aff94ba6f38bf","6b7debfeef0a444d9155ba0a1c0b58a2","d4ecbfeceb9e40739ef33baf2b0397ba","13e85f70cd1a48198a2275009533b613","63f5ee45513f477781b0ac6aa0bb5f99","38bf1085a16f45aabf07cdec94ce2f4a","1426ee4208974ea7a67f1716e46aa3f6","8ff06df9945b43688cd3d78772a21129","5a067134a95e4a46a1ef5d65e41d516b","5f4e8179477349e7aa6683af42b50f8f","f8ffc5e216f24293ad75ee87018d933f","1c6358d81f9f47c3a3d5f67305c6dfe3","0d5ff3506700439b96c04065498b5f4e","f8d52bc8016846fb89637ae380687031","a90a8c9b22884b4da2450ca81df307a4","5b0b5266be11426ea5e517f1f228d6ac","e8650aa0419247ddac17d8956d029aa7","b889ea8b760544778ee7e79ee3c74f2c","38140d2a9b4a40e0b0b585a20aacddb6","546b04729ab440e9b504ac024fa30fb5","07479476fdca4d8d95d716ac7343ee70","ce6470b0630a4e05a1b9c7aea346e580"],"output_embedded_package_id":"1HFh4C728yYS1wOzs8UVvxXySxHxn0pMp"},"cell_id":"0b0bf60da2644461a11fedfa15535e3e","outputId":"4402d7fd-4432-42a7-e0ae-d38e08aa1458","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":21797,"user_tz":180,"timestamp":1647389286839},"deepnote_cell_type":"code"},"outputs":[{"output_type":"display_data","data":{"text/plain":"Output hidden; open in https://colab.research.google.com to view."},"metadata":{}}],"execution_count":11},{"cell_type":"code","source":"#Hagamos un HeatMap del df\nplt.rcParams['figure.figsize'] = (20, 15)\n\nsns.heatmap(data.corr(), annot = True, cmap = 'Wistia')\nplt.title('Heatmap for the Dataset', fontsize = 20)\nplt.show()","metadata":{"id":"M28wu-pcA8Vm","colab":{"height":698,"base_uri":"https://localhost:8080/"},"cell_id":"afe5a244b86747abaacb27679f408ab3","outputId":"81413170-6ae5-406c-9dfd-ef723e2b2c23","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":2094,"user_tz":180,"timestamp":1647389293449},"deepnote_cell_type":"code"},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1440x1080 with 2 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"execution_count":12},{"cell_type":"code","source":"# tresbps vs target\nplt.rcParams['figure.figsize'] = (12, 9)\nsns.boxplot(data['target'], data['trestbps'], palette = 'viridis')\nplt.title('Relación entre tresbps y target', fontsize = 20)\nplt.show()","metadata":{"id":"RrTTAKC5A8Vo","colab":{"height":628,"base_uri":"https://localhost:8080/"},"cell_id":"5d1bd38ad4354e69b6b9cda6fa1a6465","outputId":"6f937779-1612-4eac-8df1-445b9afc734f","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":686,"user_tz":180,"timestamp":1647389295503},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stderr","text":"/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n  FutureWarning\n"},{"output_type":"display_data","data":{"text/plain":"<Figure size 864x648 with 1 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\n"},"metadata":{"needs_background":"light"}}],"execution_count":13},{"cell_type":"markdown","source":"**tresbps**: presión arterial en reposo, la gráfica bivariada anterior entre tresbps (la presión arterial en reposo de un paciente) y target nos indica si el paciente padece la enfermedad cardíaca o no. La trama sugiere claramente que los pacientes que tienen más probabilidades de no sufrir la enfermedad tienen una presión arterial ligeramente mayor que los pacientes que tienen enfermedades cardíacas.","metadata":{"id":"6WOGZ6b3A8Vp","cell_id":"48385094994d4317a7ef48f9e5e628fd","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"# cholestrol vs target\nplt.rcParams['figure.figsize'] = (12, 9)\nsns.violinplot(data['target'], data['chol'], palette = 'colorblind')\nplt.title('Relación entre Cholestrol y Target', fontsize = 20, fontweight = 30)\nplt.show()","metadata":{"id":"uymXXwWMA8Vr","colab":{"height":628,"base_uri":"https://localhost:8080/"},"cell_id":"5e3adb539fa443f48dd1f7e09dbe41f9","outputId":"0b4b1246-d324-47e6-c4f0-8e5d052a9a68","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":14,"user_tz":180,"timestamp":1647389297413},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stderr","text":"/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n  FutureWarning\n"},{"output_type":"display_data","data":{"text/plain":"<Figure size 864x648 with 1 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\n"},"metadata":{"needs_background":"light"}}],"execution_count":14},{"cell_type":"markdown","source":"El gráfico bivariado anterior entre los niveles de colesterol y el objetivo, sugiere que los pacientes con probabilidades de sufrir enfermedades cardíacas tienen niveles de colesterol más altos en comparación con los pacientes con el target 0 (que probablemente no padezcan enfermedades cardíacas).","metadata":{"id":"KkQN4nabA8Vs","cell_id":"521ec291617d4c39b0f40cd9ffb31088","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"# Relacion entre sex and target\nsns.boxenplot(data['target'], data['sex'], palette = 'Set3')\nplt.title('Relacion entre Sex and target', fontsize = 20, fontweight = 30)\nplt.show()\n\n#https://seaborn.pydata.org/generated/seaborn.boxenplot.html","metadata":{"id":"iyqkCtnuA8Vt","colab":{"height":627,"base_uri":"https://localhost:8080/"},"cell_id":"626e3f17869b4414a77292319b31ff1c","outputId":"09a3713b-3459-4ccb-d104-548dbf98a0a3","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":477,"user_tz":180,"timestamp":1647389299756},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stderr","text":"/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n  FutureWarning\n"},{"output_type":"display_data","data":{"text/plain":"<Figure size 864x648 with 1 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\n"},"metadata":{"needs_background":"light"}}],"execution_count":15},{"cell_type":"code","source":"#Age vs chol\nsns.scatterplot(x=\"age\", y=\"chol\", data=data)\nplt.title('Relacion entre Sex and target', fontsize = 20, fontweight = 30)","metadata":{"id":"ASaO-rUEA8Vu","colab":{"height":589,"base_uri":"https://localhost:8080/"},"cell_id":"b3ded6c36e874d84aa1efa749becd3a5","outputId":"af692b60-0927-4bee-c3d4-a6586cdaf98b","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":667,"user_tz":180,"timestamp":1647389302622},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Text(0.5, 1.0, 'Relacion entre Sex and target')"},"metadata":{},"execution_count":16},{"output_type":"display_data","data":{"text/plain":"<Figure size 864x648 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"execution_count":16},{"cell_type":"markdown","source":"Efectivamente se observa una relación entre la edad y la variable colesterol de tipo positiva, esto significa que a mayor edad también se ve incrementado el colesterol de las personas.","metadata":{"id":"WGZMd4NtA8Vu","cell_id":"8a6f34eb5a4f4c3eb653a663817f7cac","deepnote_cell_type":"markdown"}},{"cell_type":"markdown","source":"# Ejemplo 2","metadata":{"id":"pCSN7zu7DeW5","cell_id":"52aefce684574a74a92cc5285a945ec9","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"#Importemos el archivo\nvg_df = pd.read_csv('Video_Games.csv')","metadata":{"id":"Jj4ebFIHDmgc","cell_id":"4e304f926d4f4246993cc28670f4b652","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":968,"user_tz":180,"timestamp":1647389380693},"deepnote_cell_type":"code"},"outputs":[],"execution_count":17},{"cell_type":"code","source":"#Head del df\nvg_df.head()","metadata":{"id":"ig2kdUiIDmge","colab":{"height":320,"base_uri":"https://localhost:8080/"},"cell_id":"97fa5d54f5864f19b36c2d86e7cdf06d","outputId":"a44b5ada-484e-4788-dc3c-2696008ca601","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":36,"user_tz":180,"timestamp":1647389382408},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"                       Name Platform  Year_of_Release         Genre Publisher  \\\n0                Wii Sports      Wii           2006.0        Sports  Nintendo   \n1         Super Mario Bros.      NES           1985.0      Platform  Nintendo   \n2            Mario Kart Wii      Wii           2008.0        Racing  Nintendo   \n3         Wii Sports Resort      Wii           2009.0        Sports  Nintendo   \n4  Pokemon Red/Pokemon Blue       GB           1996.0  Role-Playing  Nintendo   \n\n   NA_Sales  EU_Sales  JP_Sales  Other_Sales  Global_Sales  Critic_Score  \\\n0     41.36     28.96      3.77         8.45         82.53          76.0   \n1     29.08      3.58      6.81         0.77         40.24           NaN   \n2     15.68     12.76      3.79         3.29         35.52          82.0   \n3     15.61     10.93      3.28         2.95         32.77          80.0   \n4     11.27      8.89     10.22         1.00         31.37           NaN   \n\n   Critic_Count User_Score  User_Count Developer Rating  \n0          51.0          8       322.0  Nintendo      E  \n1           NaN        NaN         NaN       NaN    NaN  \n2          73.0        8.3       709.0  Nintendo      E  \n3          73.0          8       192.0  Nintendo      E  \n4           NaN        NaN         NaN       NaN    NaN  ","text/html":"\n  <div id=\"df-e6403f84-74ef-4cb5-872c-19808a097cdf\">\n    <div class=\"colab-df-container\">\n      <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>Name</th>\n      <th>Platform</th>\n      <th>Year_of_Release</th>\n      <th>Genre</th>\n      <th>Publisher</th>\n      <th>NA_Sales</th>\n      <th>EU_Sales</th>\n      <th>JP_Sales</th>\n      <th>Other_Sales</th>\n      <th>Global_Sales</th>\n      <th>Critic_Score</th>\n      <th>Critic_Count</th>\n      <th>User_Score</th>\n      <th>User_Count</th>\n      <th>Developer</th>\n      <th>Rating</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Wii Sports</td>\n      <td>Wii</td>\n      <td>2006.0</td>\n      <td>Sports</td>\n      <td>Nintendo</td>\n      <td>41.36</td>\n      <td>28.96</td>\n      <td>3.77</td>\n      <td>8.45</td>\n      <td>82.53</td>\n      <td>76.0</td>\n      <td>51.0</td>\n      <td>8</td>\n      <td>322.0</td>\n      <td>Nintendo</td>\n      <td>E</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Super Mario Bros.</td>\n      <td>NES</td>\n      <td>1985.0</td>\n      <td>Platform</td>\n      <td>Nintendo</td>\n      <td>29.08</td>\n      <td>3.58</td>\n      <td>6.81</td>\n      <td>0.77</td>\n      <td>40.24</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Mario Kart Wii</td>\n      <td>Wii</td>\n      <td>2008.0</td>\n      <td>Racing</td>\n      <td>Nintendo</td>\n      <td>15.68</td>\n      <td>12.76</td>\n      <td>3.79</td>\n      <td>3.29</td>\n      <td>35.52</td>\n      <td>82.0</td>\n      <td>73.0</td>\n      <td>8.3</td>\n      <td>709.0</td>\n      <td>Nintendo</td>\n      <td>E</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Wii Sports Resort</td>\n      <td>Wii</td>\n      <td>2009.0</td>\n      <td>Sports</td>\n      <td>Nintendo</td>\n      <td>15.61</td>\n      <td>10.93</td>\n      <td>3.28</td>\n      <td>2.95</td>\n      <td>32.77</td>\n      <td>80.0</td>\n      <td>73.0</td>\n      <td>8</td>\n      <td>192.0</td>\n      <td>Nintendo</td>\n      <td>E</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Pokemon Red/Pokemon Blue</td>\n      <td>GB</td>\n      <td>1996.0</td>\n      <td>Role-Playing</td>\n      <td>Nintendo</td>\n      <td>11.27</td>\n      <td>8.89</td>\n      <td>10.22</td>\n      <td>1.00</td>\n      <td>31.37</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e6403f84-74ef-4cb5-872c-19808a097cdf')\"\n              title=\"Convert this dataframe to an interactive table.\"\n              style=\"display:none;\">\n        \n  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n       width=\"24px\">\n    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n  </svg>\n      </button>\n      \n  <style>\n    .colab-df-container {\n      display:flex;\n      flex-wrap:wrap;\n      gap: 12px;\n    }\n\n    .colab-df-convert {\n      background-color: #E8F0FE;\n      border: none;\n      border-radius: 50%;\n      cursor: pointer;\n      display: none;\n      fill: #1967D2;\n      height: 32px;\n      padding: 0 0 0 0;\n      width: 32px;\n    }\n\n    .colab-df-convert:hover {\n      background-color: #E2EBFA;\n      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n      fill: #174EA6;\n    }\n\n    [theme=dark] .colab-df-convert {\n      background-color: #3B4455;\n      fill: #D2E3FC;\n    }\n\n    [theme=dark] .colab-df-convert:hover {\n      background-color: #434B5C;\n      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n      fill: #FFFFFF;\n    }\n  </style>\n\n      <script>\n        const buttonEl =\n          document.querySelector('#df-e6403f84-74ef-4cb5-872c-19808a097cdf button.colab-df-convert');\n        buttonEl.style.display =\n          google.colab.kernel.accessAllowed ? 'block' : 'none';\n\n        async function convertToInteractive(key) {\n          const element = document.querySelector('#df-e6403f84-74ef-4cb5-872c-19808a097cdf');\n          const dataTable =\n            await google.colab.kernel.invokeFunction('convertToInteractive',\n                                                     [key], {});\n          if (!dataTable) return;\n\n          const docLinkHtml = 'Like what you see? Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  "},"metadata":{},"execution_count":18}],"execution_count":18},{"cell_type":"code","source":"#Veamos el shape\nvg_df.shape","metadata":{"id":"nMqhS_fzDmgf","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"5a318504144f45a98588f65bbf689293","outputId":"b09ab6e7-b407-4a25-e8a5-afd5e7717a22","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":378,"user_tz":180,"timestamp":1647389384702},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"(16719, 16)"},"metadata":{},"execution_count":19}],"execution_count":19},{"cell_type":"code","source":"#Totalidad de registros por columnas\nvg_df.count()","metadata":{"id":"JpZhFP5CDmgg","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"7f46de851cc2466f9f65e66766cd25ca","outputId":"b95ce634-0893-4d64-8cf9-90f4f90276ea","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":13,"user_tz":180,"timestamp":1647389386100},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Name               16717\nPlatform           16719\nYear_of_Release    16450\nGenre              16717\nPublisher          16665\nNA_Sales           16719\nEU_Sales           16719\nJP_Sales           16719\nOther_Sales        16719\nGlobal_Sales       16719\nCritic_Score        8137\nCritic_Count        8137\nUser_Score         10015\nUser_Count          7590\nDeveloper          10096\nRating              9950\ndtype: int64"},"metadata":{},"execution_count":20}],"execution_count":20},{"cell_type":"code","source":"#Tipo de dato de cada columna\nvg_df.dtypes","metadata":{"id":"GA8OQqkSDmgh","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"237ae57e574d47728dc865aa9e399ccd","outputId":"807a4fae-aed4-4fe2-e0f2-b73a7b77e9d4","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":12,"user_tz":180,"timestamp":1647389387841},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Name                object\nPlatform            object\nYear_of_Release    float64\nGenre               object\nPublisher           object\nNA_Sales           float64\nEU_Sales           float64\nJP_Sales           float64\nOther_Sales        float64\nGlobal_Sales       float64\nCritic_Score       float64\nCritic_Count       float64\nUser_Score          object\nUser_Count         float64\nDeveloper           object\nRating              object\ndtype: object"},"metadata":{},"execution_count":21}],"execution_count":21},{"cell_type":"code","source":"#Principales medidas estadisticas\nvg_df.describe().T","metadata":{"id":"DPX4Vxb7Dmgh","colab":{"height":332,"base_uri":"https://localhost:8080/"},"cell_id":"cd8fe4ffdd054527a2b5304d08f10fdb","outputId":"57ec1877-95e6-4972-8d60-5ec99fa6b091","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":25,"user_tz":180,"timestamp":1647389389375},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"                   count         mean         std      min      25%      50%  \\\nYear_of_Release  16450.0  2006.487356    5.878995  1980.00  2003.00  2007.00   \nNA_Sales         16719.0     0.263330    0.813514     0.00     0.00     0.08   \nEU_Sales         16719.0     0.145025    0.503283     0.00     0.00     0.02   \nJP_Sales         16719.0     0.077602    0.308818     0.00     0.00     0.00   \nOther_Sales      16719.0     0.047332    0.186710     0.00     0.00     0.01   \nGlobal_Sales     16719.0     0.533543    1.547935     0.01     0.06     0.17   \nCritic_Score      8137.0    68.967679   13.938165    13.00    60.00    71.00   \nCritic_Count      8137.0    26.360821   18.980495     3.00    12.00    21.00   \nUser_Count        7590.0   162.229908  561.282326     4.00    10.00    24.00   \n\n                     75%       max  \nYear_of_Release  2010.00   2020.00  \nNA_Sales            0.24     41.36  \nEU_Sales            0.11     28.96  \nJP_Sales            0.04     10.22  \nOther_Sales         0.03     10.57  \nGlobal_Sales        0.47     82.53  \nCritic_Score       79.00     98.00  \nCritic_Count       36.00    113.00  \nUser_Count         81.00  10665.00  ","text/html":"\n  <div id=\"df-4c180b62-76e2-4135-b0ae-fc8f5d700440\">\n    <div class=\"colab-df-container\">\n      <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>count</th>\n      <th>mean</th>\n      <th>std</th>\n      <th>min</th>\n      <th>25%</th>\n      <th>50%</th>\n      <th>75%</th>\n      <th>max</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>Year_of_Release</th>\n      <td>16450.0</td>\n      <td>2006.487356</td>\n      <td>5.878995</td>\n      <td>1980.00</td>\n      <td>2003.00</td>\n      <td>2007.00</td>\n      <td>2010.00</td>\n      <td>2020.00</td>\n    </tr>\n    <tr>\n      <th>NA_Sales</th>\n      <td>16719.0</td>\n      <td>0.263330</td>\n      <td>0.813514</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.08</td>\n      <td>0.24</td>\n      <td>41.36</td>\n    </tr>\n    <tr>\n      <th>EU_Sales</th>\n      <td>16719.0</td>\n      <td>0.145025</td>\n      <td>0.503283</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.02</td>\n      <td>0.11</td>\n      <td>28.96</td>\n    </tr>\n    <tr>\n      <th>JP_Sales</th>\n      <td>16719.0</td>\n      <td>0.077602</td>\n      <td>0.308818</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.04</td>\n      <td>10.22</td>\n    </tr>\n    <tr>\n      <th>Other_Sales</th>\n      <td>16719.0</td>\n      <td>0.047332</td>\n      <td>0.186710</td>\n      <td>0.00</td>\n      <td>0.00</td>\n      <td>0.01</td>\n      <td>0.03</td>\n      <td>10.57</td>\n    </tr>\n    <tr>\n      <th>Global_Sales</th>\n      <td>16719.0</td>\n      <td>0.533543</td>\n      <td>1.547935</td>\n      <td>0.01</td>\n      <td>0.06</td>\n      <td>0.17</td>\n      <td>0.47</td>\n      <td>82.53</td>\n    </tr>\n    <tr>\n      <th>Critic_Score</th>\n      <td>8137.0</td>\n      <td>68.967679</td>\n      <td>13.938165</td>\n      <td>13.00</td>\n      <td>60.00</td>\n      <td>71.00</td>\n      <td>79.00</td>\n      <td>98.00</td>\n    </tr>\n    <tr>\n      <th>Critic_Count</th>\n      <td>8137.0</td>\n      <td>26.360821</td>\n      <td>18.980495</td>\n      <td>3.00</td>\n      <td>12.00</td>\n      <td>21.00</td>\n      <td>36.00</td>\n      <td>113.00</td>\n    </tr>\n    <tr>\n      <th>User_Count</th>\n      <td>7590.0</td>\n      <td>162.229908</td>\n      <td>561.282326</td>\n      <td>4.00</td>\n      <td>10.00</td>\n      <td>24.00</td>\n      <td>81.00</td>\n      <td>10665.00</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4c180b62-76e2-4135-b0ae-fc8f5d700440')\"\n              title=\"Convert this dataframe to an interactive table.\"\n              style=\"display:none;\">\n        \n  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n       width=\"24px\">\n    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n  </svg>\n      </button>\n      \n  <style>\n    .colab-df-container {\n      display:flex;\n      flex-wrap:wrap;\n      gap: 12px;\n    }\n\n    .colab-df-convert {\n      background-color: #E8F0FE;\n      border: none;\n      border-radius: 50%;\n      cursor: pointer;\n      display: none;\n      fill: #1967D2;\n      height: 32px;\n      padding: 0 0 0 0;\n      width: 32px;\n    }\n\n    .colab-df-convert:hover {\n      background-color: #E2EBFA;\n      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n      fill: #174EA6;\n    }\n\n    [theme=dark] .colab-df-convert {\n      background-color: #3B4455;\n      fill: #D2E3FC;\n    }\n\n    [theme=dark] .colab-df-convert:hover {\n      background-color: #434B5C;\n      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n      fill: #FFFFFF;\n    }\n  </style>\n\n      <script>\n        const buttonEl =\n          document.querySelector('#df-4c180b62-76e2-4135-b0ae-fc8f5d700440 button.colab-df-convert');\n        buttonEl.style.display =\n          google.colab.kernel.accessAllowed ? 'block' : 'none';\n\n        async function convertToInteractive(key) {\n          const element = document.querySelector('#df-4c180b62-76e2-4135-b0ae-fc8f5d700440');\n          const dataTable =\n            await google.colab.kernel.invokeFunction('convertToInteractive',\n                                                     [key], {});\n          if (!dataTable) return;\n\n          const docLinkHtml = 'Like what you see? Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  "},"metadata":{},"execution_count":22}],"execution_count":22},{"cell_type":"code","source":"#Data Profiling\nprofile = pandas_profiling.ProfileReport(vg_df)\nprofile","metadata":{"id":"XWVi7c4pDmgi","colab":{"height":917,"base_uri":"https://localhost:8080/","referenced_widgets":["bc209a15143741969eef0fe694177380","dd1d4414e0104c8c8410c8d7ef39902e","9d3644c928c04975b90c588b5a34660e","80bfccdb6cf448ffa121adfdccc71b3d","69bb32ba55364b6bbdab79594eee58e3","87a8ed29b8a5451aa5581a333602dacc","3955e1aaa857470e9b8fe3411f740635","ed6995455ed94266ae5d2e95569171af","f1172da064a44284ade37f34eb8f0131","a00e1b6ea4f045e0ba045d1da18962ab","145c0ceae12845e6a28f3de9c76a0413","4067beaed262412fb31094c50159c3a8","c31d2c7e120840c2ad189b5dbec4406f","3048d81cb3504269b3828e967053aebd","eee46a966f2247d6bc2f413ea30e5069","d40976c961e042dc9c60280531895fd5","7eb9cc7d63d842c4bf761316bc06062c","21f9779dcaf84dda939dfb0cdaf925fa","a01c11dd5ecd4a35ab5f887c72c8560a","b667cf8fd1fe45bdbc93a224345009a5","dcfcc25be52e48d695a663bf3ea1319a","95eaadfca0594c29a314c093886f7cea","7423288b57c44b549667fd0cbbbeace2","102e6b3f36884532bb17f97bb29c582e","65c5558f94cc4e81b31e605b2097eaec","34d8e51bd1a54a6ea827a92c69fa4147","8471e68ba4694a80b377cc28c2286f96","cf5671190f7940748f2037aaeae96e6e","75307880011d46a4a1269e55f4846eb9","85d834714c2d41d18e31634a797ecb57","7171bb9b676f49e78f9777db94e601c4","6040669b09454defa771c78a4a060131","0c0ca611fd274db8a51d58d3730aa1b1"],"output_embedded_package_id":"1jlv7IKTBy5l0Yv7UeHPzXZZSiFYixcxk"},"cell_id":"b4e1f62e9a504d0d83ceed60db4d5315","outputId":"df752966-5715-4751-92e6-dd28e01fcd4a","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":36369,"user_tz":180,"timestamp":1647389426939},"deepnote_cell_type":"code"},"outputs":[{"output_type":"display_data","data":{"text/plain":"Output hidden; open in https://colab.research.google.com to view."},"metadata":{}}],"execution_count":23},{"cell_type":"code","source":"#Correlaciones\nplt.figure(figsize=(12, 8))\n\nvg_corr = vg_df.corr()\nsns.heatmap(vg_corr, \n            xticklabels = vg_corr.columns.values,\n            yticklabels = vg_corr.columns.values,\n            annot = True);","metadata":{"id":"HhpjpPo3Dmgj","colab":{"height":556,"base_uri":"https://localhost:8080/"},"cell_id":"17e370ab42a8426da603935ccecca806","outputId":"111c1d76-fb71-439a-c698-5b17d627baf1","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":1325,"user_tz":180,"timestamp":1647389455791},"deepnote_cell_type":"code"},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 864x576 with 2 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"execution_count":24},{"cell_type":"code","source":"#Ejemplo: Categórica vs. categórica\npd.crosstab(vg_df.Genre, vg_df.Rating)","metadata":{"id":"zBBOfALpDmgk","colab":{"height":457,"base_uri":"https://localhost:8080/"},"cell_id":"b3fed55cdab24572906a8cbc2891f919","outputId":"b1ee60b4-27a6-4fbf-8a54-4d4ff4e8e3f5","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":40,"user_tz":180,"timestamp":1647389456346},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Rating        AO     E  E10+  EC  K-A    M  RP    T\nGenre                                              \nAction         1   416   481   1    0  608   0  681\nAdventure      0   162    68   2    0   99   0  115\nFighting       0     8    19   0    0   49   0  362\nMisc           0   457   167   5    1   13   0  239\nPlatform       0   358   144   0    0    3   0   64\nPuzzle         0   289    43   0    0    0   0   10\nRacing         0   585    96   0    0   18   1  172\nRole-Playing   0    84   111   0    0  162   0  420\nShooter        0    48    58   0    0  565   0  348\nSimulation     0   326    48   0    0    5   0  190\nSports         0  1188   107   0    0   16   0  198\nStrategy       0    70    78   0    2   25   2  162","text/html":"\n  <div id=\"df-1fb7be53-1c24-454f-9bc5-448f3cf32cba\">\n    <div class=\"colab-df-container\">\n      <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>Rating</th>\n      <th>AO</th>\n      <th>E</th>\n      <th>E10+</th>\n      <th>EC</th>\n      <th>K-A</th>\n      <th>M</th>\n      <th>RP</th>\n      <th>T</th>\n    </tr>\n    <tr>\n      <th>Genre</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>Action</th>\n      <td>1</td>\n      <td>416</td>\n      <td>481</td>\n      <td>1</td>\n      <td>0</td>\n      <td>608</td>\n      <td>0</td>\n      <td>681</td>\n    </tr>\n    <tr>\n      <th>Adventure</th>\n      <td>0</td>\n      <td>162</td>\n      <td>68</td>\n      <td>2</td>\n      <td>0</td>\n      <td>99</td>\n      <td>0</td>\n      <td>115</td>\n    </tr>\n    <tr>\n      <th>Fighting</th>\n      <td>0</td>\n      <td>8</td>\n      <td>19</td>\n      <td>0</td>\n      <td>0</td>\n      <td>49</td>\n      <td>0</td>\n      <td>362</td>\n    </tr>\n    <tr>\n      <th>Misc</th>\n      <td>0</td>\n      <td>457</td>\n      <td>167</td>\n      <td>5</td>\n      <td>1</td>\n      <td>13</td>\n      <td>0</td>\n      <td>239</td>\n    </tr>\n    <tr>\n      <th>Platform</th>\n      <td>0</td>\n      <td>358</td>\n      <td>144</td>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>0</td>\n      <td>64</td>\n    </tr>\n    <tr>\n      <th>Puzzle</th>\n      <td>0</td>\n      <td>289</td>\n      <td>43</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>10</td>\n    </tr>\n    <tr>\n      <th>Racing</th>\n      <td>0</td>\n      <td>585</td>\n      <td>96</td>\n      <td>0</td>\n      <td>0</td>\n      <td>18</td>\n      <td>1</td>\n      <td>172</td>\n    </tr>\n    <tr>\n      <th>Role-Playing</th>\n      <td>0</td>\n      <td>84</td>\n      <td>111</td>\n      <td>0</td>\n      <td>0</td>\n      <td>162</td>\n      <td>0</td>\n      <td>420</td>\n    </tr>\n    <tr>\n      <th>Shooter</th>\n      <td>0</td>\n      <td>48</td>\n      <td>58</td>\n      <td>0</td>\n      <td>0</td>\n      <td>565</td>\n      <td>0</td>\n      <td>348</td>\n    </tr>\n    <tr>\n      <th>Simulation</th>\n      <td>0</td>\n      <td>326</td>\n      <td>48</td>\n      <td>0</td>\n      <td>0</td>\n      <td>5</td>\n      <td>0</td>\n      <td>190</td>\n    </tr>\n    <tr>\n      <th>Sports</th>\n      <td>0</td>\n      <td>1188</td>\n      <td>107</td>\n      <td>0</td>\n      <td>0</td>\n      <td>16</td>\n      <td>0</td>\n      <td>198</td>\n    </tr>\n    <tr>\n      <th>Strategy</th>\n      <td>0</td>\n      <td>70</td>\n      <td>78</td>\n      <td>0</td>\n      <td>2</td>\n      <td>25</td>\n      <td>2</td>\n      <td>162</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1fb7be53-1c24-454f-9bc5-448f3cf32cba')\"\n              title=\"Convert this dataframe to an interactive table.\"\n              style=\"display:none;\">\n        \n  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n       width=\"24px\">\n    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n   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'block' : 'none';\n\n        async function convertToInteractive(key) {\n          const element = document.querySelector('#df-1fb7be53-1c24-454f-9bc5-448f3cf32cba');\n          const dataTable =\n            await google.colab.kernel.invokeFunction('convertToInteractive',\n                                                     [key], {});\n          if (!dataTable) return;\n\n          const docLinkHtml = 'Like what you see? Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  "},"metadata":{},"execution_count":25}],"execution_count":25},{"cell_type":"code","source":"pd.crosstab(vg_df.Genre, vg_df.Rating, normalize=True) #Agregamos los valores en relativo","metadata":{"id":"Kbc74PWIDmgm","colab":{"height":457,"base_uri":"https://localhost:8080/"},"cell_id":"1117d29483b3446bad54517f53881cbb","outputId":"3523fbb8-99cb-46c4-d675-feb876e5004a","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":443,"user_tz":180,"timestamp":1647389459405},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Rating              AO         E      E10+        EC       K-A         M  \\\nGenre                                                                      \nAction        0.000101  0.041809  0.048342  0.000101  0.000000  0.061106   \nAdventure     0.000000  0.016281  0.006834  0.000201  0.000000  0.009950   \nFighting      0.000000  0.000804  0.001910  0.000000  0.000000  0.004925   \nMisc          0.000000  0.045930  0.016784  0.000503  0.000101  0.001307   \nPlatform      0.000000  0.035980  0.014472  0.000000  0.000000  0.000302   \nPuzzle        0.000000  0.029045  0.004322  0.000000  0.000000  0.000000   \nRacing        0.000000  0.058794  0.009648  0.000000  0.000000  0.001809   \nRole-Playing  0.000000  0.008442  0.011156  0.000000  0.000000  0.016281   \nShooter       0.000000  0.004824  0.005829  0.000000  0.000000  0.056784   \nSimulation    0.000000  0.032764  0.004824  0.000000  0.000000  0.000503   \nSports        0.000000  0.119397  0.010754  0.000000  0.000000  0.001608   \nStrategy      0.000000  0.007035  0.007839  0.000000  0.000201  0.002513   \n\nRating              RP         T  \nGenre                             \nAction        0.000000  0.068442  \nAdventure     0.000000  0.011558  \nFighting      0.000000  0.036382  \nMisc          0.000000  0.024020  \nPlatform      0.000000  0.006432  \nPuzzle        0.000000  0.001005  \nRacing        0.000101  0.017286  \nRole-Playing  0.000000  0.042211  \nShooter       0.000000  0.034975  \nSimulation    0.000000  0.019095  \nSports        0.000000  0.019899  \nStrategy      0.000201  0.016281  ","text/html":"\n  <div id=\"df-0242549a-71c3-4b0d-bf2e-d70777e3305b\">\n    <div class=\"colab-df-container\">\n      <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>Rating</th>\n      <th>AO</th>\n      <th>E</th>\n      <th>E10+</th>\n      <th>EC</th>\n      <th>K-A</th>\n      <th>M</th>\n      <th>RP</th>\n      <th>T</th>\n    </tr>\n    <tr>\n      <th>Genre</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>Action</th>\n      <td>0.000101</td>\n      <td>0.041809</td>\n      <td>0.048342</td>\n      <td>0.000101</td>\n      <td>0.000000</td>\n      <td>0.061106</td>\n      <td>0.000000</td>\n      <td>0.068442</td>\n    </tr>\n    <tr>\n      <th>Adventure</th>\n      <td>0.000000</td>\n      <td>0.016281</td>\n      <td>0.006834</td>\n      <td>0.000201</td>\n      <td>0.000000</td>\n      <td>0.009950</td>\n      <td>0.000000</td>\n      <td>0.011558</td>\n    </tr>\n    <tr>\n      <th>Fighting</th>\n      <td>0.000000</td>\n      <td>0.000804</td>\n      <td>0.001910</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.004925</td>\n      <td>0.000000</td>\n      <td>0.036382</td>\n    </tr>\n    <tr>\n      <th>Misc</th>\n      <td>0.000000</td>\n      <td>0.045930</td>\n      <td>0.016784</td>\n      <td>0.000503</td>\n      <td>0.000101</td>\n      <td>0.001307</td>\n      <td>0.000000</td>\n      <td>0.024020</td>\n    </tr>\n    <tr>\n      <th>Platform</th>\n      <td>0.000000</td>\n      <td>0.035980</td>\n      <td>0.014472</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000302</td>\n      <td>0.000000</td>\n      <td>0.006432</td>\n    </tr>\n    <tr>\n      <th>Puzzle</th>\n      <td>0.000000</td>\n      <td>0.029045</td>\n      <td>0.004322</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.001005</td>\n    </tr>\n    <tr>\n      <th>Racing</th>\n      <td>0.000000</td>\n      <td>0.058794</td>\n      <td>0.009648</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.001809</td>\n      <td>0.000101</td>\n      <td>0.017286</td>\n    </tr>\n    <tr>\n      <th>Role-Playing</th>\n      <td>0.000000</td>\n      <td>0.008442</td>\n      <td>0.011156</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.016281</td>\n      <td>0.000000</td>\n      <td>0.042211</td>\n    </tr>\n    <tr>\n      <th>Shooter</th>\n      <td>0.000000</td>\n      <td>0.004824</td>\n      <td>0.005829</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.056784</td>\n      <td>0.000000</td>\n      <td>0.034975</td>\n    </tr>\n    <tr>\n      <th>Simulation</th>\n      <td>0.000000</td>\n      <td>0.032764</td>\n      <td>0.004824</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000503</td>\n      <td>0.000000</td>\n      <td>0.019095</td>\n    </tr>\n    <tr>\n      <th>Sports</th>\n      <td>0.000000</td>\n      <td>0.119397</td>\n      <td>0.010754</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.001608</td>\n      <td>0.000000</td>\n      <td>0.019899</td>\n    </tr>\n    <tr>\n      <th>Strategy</th>\n      <td>0.000000</td>\n      <td>0.007035</td>\n      <td>0.007839</td>\n      <td>0.000000</td>\n      <td>0.000201</td>\n      <td>0.002513</td>\n      <td>0.000201</td>\n      <td>0.016281</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0242549a-71c3-4b0d-bf2e-d70777e3305b')\"\n              title=\"Convert this dataframe to an interactive table.\"\n              style=\"display:none;\">\n        \n  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n       width=\"24px\">\n    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n  </svg>\n      </button>\n      \n  <style>\n    .colab-df-container {\n      display:flex;\n      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=\n          google.colab.kernel.accessAllowed ? 'block' : 'none';\n\n        async function convertToInteractive(key) {\n          const element = document.querySelector('#df-0242549a-71c3-4b0d-bf2e-d70777e3305b');\n          const dataTable =\n            await google.colab.kernel.invokeFunction('convertToInteractive',\n                                                     [key], {});\n          if (!dataTable) return;\n\n          const docLinkHtml = 'Like what you see? Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  "},"metadata":{},"execution_count":26}],"execution_count":26},{"cell_type":"code","source":"#Análisis de numérica vs. categórica\nvg_df.groupby('Genre')['Global_Sales'].mean()","metadata":{"id":"s0SjxZtfDmgn","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"8bf0b848c9924f608567f28d6877761c","outputId":"62275084-08d0-4313-d764-b6a19dd2ec98","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":19,"user_tz":180,"timestamp":1647389461150},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Genre\nAction          0.517884\nAdventure       0.182417\nFighting        0.527067\nMisc            0.458960\nPlatform        0.932523\nPuzzle          0.419000\nRacing          0.583587\nRole-Playing    0.622933\nShooter         0.795873\nSimulation      0.446705\nSports          0.567291\nStrategy        0.255490\nName: Global_Sales, dtype: float64"},"metadata":{},"execution_count":27}],"execution_count":27},{"cell_type":"code","source":"vg_df.groupby('Genre')['Critic_Score'].mean()","metadata":{"id":"ku_In-BfDmgo","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"817703e0f9774b4494e5939aac6298c4","outputId":"202731e2-8401-4c65-ca83-a0ebd6451aee","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":6,"user_tz":180,"timestamp":1647389462715},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Genre\nAction          66.629101\nAdventure       65.331269\nFighting        69.217604\nMisc            66.619503\nPlatform        68.058350\nPuzzle          67.424107\nRacing          67.963612\nRole-Playing    72.652646\nShooter         70.181144\nSimulation      68.619318\nSports          71.968174\nStrategy        72.086093\nName: Critic_Score, dtype: float64"},"metadata":{},"execution_count":28}],"execution_count":28},{"cell_type":"code","source":"vg_df.groupby('Genre')['EU_Sales'].mean()","metadata":{"id":"KZbj1WPMDmgp","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"dc91d4c5943748f497703e12a09ed6e0","outputId":"3cc906e3-07e7-4817-eeaf-0fa50cd24081","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":7,"user_tz":180,"timestamp":1647389463839},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Genre\nAction          0.154045\nAdventure       0.048764\nFighting        0.118174\nMisc            0.121566\nPlatform        0.225619\nPuzzle          0.086224\nRacing          0.189359\nRole-Playing    0.125807\nShooter         0.239864\nSimulation      0.129886\nSports          0.160473\nStrategy        0.066135\nName: EU_Sales, dtype: float64"},"metadata":{},"execution_count":29}],"execution_count":29},{"cell_type":"code","source":"vg_df.groupby('Genre')['EU_Sales'].mean().sort_values(ascending=False) #Ordenamiento descendiente","metadata":{"id":"H71JD9YvDmgp","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"ad95dd564ccf4be68ec085275fac3d05","outputId":"fa51a968-9deb-4343-cea3-bdf71a24cfcb","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":553,"user_tz":180,"timestamp":1647389466242},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Genre\nShooter         0.239864\nPlatform        0.225619\nRacing          0.189359\nSports          0.160473\nAction          0.154045\nSimulation      0.129886\nRole-Playing    0.125807\nMisc            0.121566\nFighting        0.118174\nPuzzle          0.086224\nStrategy        0.066135\nAdventure       0.048764\nName: EU_Sales, dtype: float64"},"metadata":{},"execution_count":30}],"execution_count":30},{"cell_type":"code","source":"vg_df.groupby('Genre')['Critic_Score'].describe()","metadata":{"id":"7d2eEmtJDmgp","colab":{"height":457,"base_uri":"https://localhost:8080/"},"cell_id":"00cb9ef81d4c4431b0034c9657a0407b","outputId":"1e9d3f02-e940-47d0-e2ab-6989dbef7824","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":18,"user_tz":180,"timestamp":1647389466786},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"               count       mean        std   min    25%   50%   75%   max\nGenre                                                                    \nAction        1890.0  66.629101  14.206877  19.0  57.00  68.0  77.0  98.0\nAdventure      323.0  65.331269  13.920756  17.0  57.00  66.0  76.0  93.0\nFighting       409.0  69.217604  14.280079  23.0  61.00  72.0  80.0  98.0\nMisc           523.0  66.619503  14.152649  19.0  58.50  69.0  77.0  93.0\nPlatform       497.0  68.058350  13.213760  19.0  59.00  69.0  77.0  97.0\nPuzzle         224.0  67.424107  12.735444  25.0  60.75  70.0  76.0  90.0\nRacing         742.0  67.963612  14.248234  13.0  59.00  69.0  79.0  96.0\nRole-Playing   737.0  72.652646  11.999835  35.0  65.00  74.0  82.0  96.0\nShooter        944.0  70.181144  14.552571  22.0  61.00  73.0  81.0  97.0\nSimulation     352.0  68.619318  12.409558  31.0  62.00  70.0  77.0  92.0\nSports        1194.0  71.968174  13.878433  19.0  64.00  75.0  82.0  98.0\nStrategy       302.0  72.086093  11.828475  35.0  65.00  73.0  80.0  94.0","text/html":"\n  <div id=\"df-077d2daf-1c5d-45be-b145-856201750c8f\">\n    <div class=\"colab-df-container\">\n      <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>count</th>\n      <th>mean</th>\n      <th>std</th>\n      <th>min</th>\n      <th>25%</th>\n      <th>50%</th>\n      <th>75%</th>\n      <th>max</th>\n    </tr>\n    <tr>\n      <th>Genre</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>Action</th>\n      <td>1890.0</td>\n      <td>66.629101</td>\n      <td>14.206877</td>\n      <td>19.0</td>\n      <td>57.00</td>\n      <td>68.0</td>\n      <td>77.0</td>\n      <td>98.0</td>\n    </tr>\n    <tr>\n      <th>Adventure</th>\n      <td>323.0</td>\n      <td>65.331269</td>\n      <td>13.920756</td>\n      <td>17.0</td>\n      <td>57.00</td>\n      <td>66.0</td>\n      <td>76.0</td>\n      <td>93.0</td>\n    </tr>\n    <tr>\n      <th>Fighting</th>\n      <td>409.0</td>\n      <td>69.217604</td>\n      <td>14.280079</td>\n      <td>23.0</td>\n      <td>61.00</td>\n      <td>72.0</td>\n      <td>80.0</td>\n      <td>98.0</td>\n    </tr>\n    <tr>\n      <th>Misc</th>\n      <td>523.0</td>\n      <td>66.619503</td>\n      <td>14.152649</td>\n      <td>19.0</td>\n      <td>58.50</td>\n      <td>69.0</td>\n      <td>77.0</td>\n      <td>93.0</td>\n    </tr>\n    <tr>\n      <th>Platform</th>\n      <td>497.0</td>\n      <td>68.058350</td>\n      <td>13.213760</td>\n      <td>19.0</td>\n      <td>59.00</td>\n      <td>69.0</td>\n      <td>77.0</td>\n      <td>97.0</td>\n    </tr>\n    <tr>\n      <th>Puzzle</th>\n      <td>224.0</td>\n      <td>67.424107</td>\n      <td>12.735444</td>\n      <td>25.0</td>\n      <td>60.75</td>\n      <td>70.0</td>\n      <td>76.0</td>\n      <td>90.0</td>\n    </tr>\n    <tr>\n      <th>Racing</th>\n      <td>742.0</td>\n      <td>67.963612</td>\n      <td>14.248234</td>\n      <td>13.0</td>\n      <td>59.00</td>\n      <td>69.0</td>\n      <td>79.0</td>\n      <td>96.0</td>\n    </tr>\n    <tr>\n      <th>Role-Playing</th>\n      <td>737.0</td>\n      <td>72.652646</td>\n      <td>11.999835</td>\n      <td>35.0</td>\n      <td>65.00</td>\n      <td>74.0</td>\n      <td>82.0</td>\n      <td>96.0</td>\n    </tr>\n    <tr>\n      <th>Shooter</th>\n      <td>944.0</td>\n      <td>70.181144</td>\n      <td>14.552571</td>\n      <td>22.0</td>\n      <td>61.00</td>\n      <td>73.0</td>\n      <td>81.0</td>\n      <td>97.0</td>\n    </tr>\n    <tr>\n      <th>Simulation</th>\n      <td>352.0</td>\n      <td>68.619318</td>\n      <td>12.409558</td>\n      <td>31.0</td>\n      <td>62.00</td>\n      <td>70.0</td>\n      <td>77.0</td>\n      <td>92.0</td>\n    </tr>\n    <tr>\n      <th>Sports</th>\n      <td>1194.0</td>\n      <td>71.968174</td>\n      <td>13.878433</td>\n      <td>19.0</td>\n      <td>64.00</td>\n      <td>75.0</td>\n      <td>82.0</td>\n      <td>98.0</td>\n    </tr>\n    <tr>\n      <th>Strategy</th>\n      <td>302.0</td>\n      <td>72.086093</td>\n      <td>11.828475</td>\n      <td>35.0</td>\n      <td>65.00</td>\n      <td>73.0</td>\n      <td>80.0</td>\n      <td>94.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-077d2daf-1c5d-45be-b145-856201750c8f')\"\n              title=\"Convert this dataframe to an interactive table.\"\n              style=\"display:none;\">\n        \n  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n       width=\"24px\">\n    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 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Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  "},"metadata":{},"execution_count":31}],"execution_count":31},{"cell_type":"code","source":"#Boxplot\nplt.figure(figsize=(20,20)) #defino el tamaño del grafico\nsns.boxplot(y = 'Critic_Score', x = 'Genre', data = vg_df)\nplt.show()","metadata":{"id":"QYZ6G8fXDmgq","colab":{"height":1000,"base_uri":"https://localhost:8080/"},"cell_id":"8b6f8999a9b84454987117b11e5ace3d","outputId":"d229824f-e74a-407e-e2cf-13e4186d001a","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":754,"user_tz":180,"timestamp":1647389469167},"deepnote_cell_type":"code"},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1440x1440 with 1 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\n"},"metadata":{"needs_background":"light"}}],"execution_count":32},{"cell_type":"markdown","source":"# Ejemplo 3","metadata":{"id":"QnGI-0uWEG4s","cell_id":"83046b05100a4b0899f9becf51cecfec","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"import pandas as pd\npokemon = pd.read_csv(\"Pokemon.csv\", index_col=0)","metadata":{"id":"pDqfZiIxEKyh","cell_id":"d357469d53604265b917b7b097dbd4c8","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":1013,"user_tz":180,"timestamp":1647389518064},"deepnote_cell_type":"code"},"outputs":[],"execution_count":33},{"cell_type":"code","source":"#Head del df\npokemon.head()","metadata":{"id":"jDgMDxIcEKyl","colab":{"height":238,"base_uri":"https://localhost:8080/"},"cell_id":"73e82086e3cb43688cd617f31e199b48","outputId":"0d1b809c-61ef-4f5b-f5bc-cb8ee2d9d775","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":21,"user_tz":180,"timestamp":1647389519051},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"                    Name Type 1  Type 2  Total  HP  Attack  Defense  Sp. Atk  \\\n#                                                                              \n1              Bulbasaur  Grass  Poison    318  45      49       49       65   \n2                Ivysaur  Grass  Poison    405  60      62       63       80   \n3               Venusaur  Grass  Poison    525  80      82       83      100   \n3  VenusaurMega Venusaur  Grass  Poison    625  80     100      123      122   \n4             Charmander   Fire     NaN    309  39      52       43       60   \n\n   Sp. Def  Speed  Generation  Legendary  \n#                                         \n1       65     45           1      False  \n2       80     60           1      False  \n3      100     80           1      False  \n3      120     80           1      False  \n4       50     65           1      False  ","text/html":"\n  <div id=\"df-cc26a1d7-13a2-4b4a-9431-09b42d20b974\">\n    <div class=\"colab-df-container\">\n      <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>Name</th>\n      <th>Type 1</th>\n      <th>Type 2</th>\n      <th>Total</th>\n      <th>HP</th>\n      <th>Attack</th>\n      <th>Defense</th>\n      <th>Sp. Atk</th>\n      <th>Sp. Def</th>\n      <th>Speed</th>\n      <th>Generation</th>\n      <th>Legendary</th>\n    </tr>\n    <tr>\n      <th>#</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>Bulbasaur</td>\n      <td>Grass</td>\n      <td>Poison</td>\n      <td>318</td>\n      <td>45</td>\n      <td>49</td>\n      <td>49</td>\n      <td>65</td>\n      <td>65</td>\n      <td>45</td>\n      <td>1</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Ivysaur</td>\n      <td>Grass</td>\n      <td>Poison</td>\n      <td>405</td>\n      <td>60</td>\n      <td>62</td>\n      <td>63</td>\n      <td>80</td>\n      <td>80</td>\n      <td>60</td>\n      <td>1</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Venusaur</td>\n      <td>Grass</td>\n      <td>Poison</td>\n      <td>525</td>\n      <td>80</td>\n      <td>82</td>\n      <td>83</td>\n      <td>100</td>\n      <td>100</td>\n      <td>80</td>\n      <td>1</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>VenusaurMega Venusaur</td>\n      <td>Grass</td>\n      <td>Poison</td>\n      <td>625</td>\n      <td>80</td>\n      <td>100</td>\n      <td>123</td>\n      <td>122</td>\n      <td>120</td>\n      <td>80</td>\n      <td>1</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Charmander</td>\n      <td>Fire</td>\n      <td>NaN</td>\n      <td>309</td>\n      <td>39</td>\n      <td>52</td>\n      <td>43</td>\n      <td>60</td>\n      <td>50</td>\n      <td>65</td>\n      <td>1</td>\n      <td>False</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cc26a1d7-13a2-4b4a-9431-09b42d20b974')\"\n              title=\"Convert this dataframe to an interactive table.\"\n              style=\"display:none;\">\n        \n  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n       width=\"24px\">\n    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n  </svg>\n      </button>\n      \n  <style>\n    .colab-df-container {\n      display:flex;\n      flex-wrap:wrap;\n      gap: 12px;\n    }\n\n    .colab-df-convert {\n      background-color: #E8F0FE;\n      border: none;\n      border-radius: 50%;\n      cursor: pointer;\n      display: none;\n      fill: #1967D2;\n      height: 32px;\n      padding: 0 0 0 0;\n      width: 32px;\n    }\n\n    .colab-df-convert:hover {\n      background-color: #E2EBFA;\n      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n      fill: #174EA6;\n    }\n\n    [theme=dark] .colab-df-convert {\n      background-color: #3B4455;\n      fill: #D2E3FC;\n    }\n\n    [theme=dark] .colab-df-convert:hover {\n      background-color: #434B5C;\n      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n      fill: #FFFFFF;\n    }\n  </style>\n\n      <script>\n        const buttonEl =\n          document.querySelector('#df-cc26a1d7-13a2-4b4a-9431-09b42d20b974 button.colab-df-convert');\n        buttonEl.style.display =\n          google.colab.kernel.accessAllowed ? 'block' : 'none';\n\n        async function convertToInteractive(key) {\n          const element = document.querySelector('#df-cc26a1d7-13a2-4b4a-9431-09b42d20b974');\n          const dataTable =\n            await google.colab.kernel.invokeFunction('convertToInteractive',\n                                                     [key], {});\n          if (!dataTable) return;\n\n          const docLinkHtml = 'Like what you see? Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  "},"metadata":{},"execution_count":34}],"execution_count":34},{"cell_type":"code","source":"#Veamos el shape\npokemon.shape","metadata":{"id":"WXdAoVfDEKym","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"6ee005d8212e4fe0a627932fa57617e3","outputId":"45d9e73b-9fd5-4cca-9f46-4cf854ad99a5","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":611,"user_tz":180,"timestamp":1647389522006},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"(800, 12)"},"metadata":{},"execution_count":35}],"execution_count":35},{"cell_type":"code","source":"#Totalidad de registros por columnas\npokemon.count()","metadata":{"id":"5Ba_sRxwEKyn","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"73d58b9a8a0b49a280d786402991e83f","outputId":"fa60cd25-f360-4078-f2a5-173b7a9c0d91","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":7,"user_tz":180,"timestamp":1647389522671},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Name          800\nType 1        800\nType 2        414\nTotal         800\nHP            800\nAttack        800\nDefense       800\nSp. Atk       800\nSp. Def       800\nSpeed         800\nGeneration    800\nLegendary     800\ndtype: int64"},"metadata":{},"execution_count":36}],"execution_count":36},{"cell_type":"code","source":"#Tipo de dato de cada columna\npokemon.dtypes","metadata":{"id":"4aEboW3REKyp","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"a22b26087ade42a0a5960bdbcd0bcc5a","outputId":"0c6a5059-697f-48d7-ff03-103c0a6c342d","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":419,"user_tz":180,"timestamp":1647389523593},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Name          object\nType 1        object\nType 2        object\nTotal          int64\nHP             int64\nAttack         int64\nDefense        int64\nSp. Atk        int64\nSp. Def        int64\nSpeed          int64\nGeneration     int64\nLegendary       bool\ndtype: object"},"metadata":{},"execution_count":37}],"execution_count":37},{"cell_type":"code","source":"#Principales medidas estadisticas\npokemon.describe().T","metadata":{"id":"e7cmpN-OEKyq","colab":{"height":301,"base_uri":"https://localhost:8080/"},"cell_id":"80ce8597c91545019046ea181b86ae15","outputId":"0aed9515-da9a-4a6e-d9dc-374ab0e8b6d0","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":20,"user_tz":180,"timestamp":1647389525080},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"            count       mean         std    min     25%    50%    75%    max\nTotal       800.0  435.10250  119.963040  180.0  330.00  450.0  515.0  780.0\nHP          800.0   69.25875   25.534669    1.0   50.00   65.0   80.0  255.0\nAttack      800.0   79.00125   32.457366    5.0   55.00   75.0  100.0  190.0\nDefense     800.0   73.84250   31.183501    5.0   50.00   70.0   90.0  230.0\nSp. Atk     800.0   72.82000   32.722294   10.0   49.75   65.0   95.0  194.0\nSp. Def     800.0   71.90250   27.828916   20.0   50.00   70.0   90.0  230.0\nSpeed       800.0   68.27750   29.060474    5.0   45.00   65.0   90.0  180.0\nGeneration  800.0    3.32375    1.661290    1.0    2.00    3.0    5.0    6.0","text/html":"\n  <div id=\"df-64daa468-9cf4-46aa-82e6-7a5edb556ce4\">\n    <div class=\"colab-df-container\">\n      <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>count</th>\n      <th>mean</th>\n      <th>std</th>\n      <th>min</th>\n      <th>25%</th>\n      <th>50%</th>\n      <th>75%</th>\n      <th>max</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>Total</th>\n      <td>800.0</td>\n      <td>435.10250</td>\n      <td>119.963040</td>\n      <td>180.0</td>\n      <td>330.00</td>\n      <td>450.0</td>\n      <td>515.0</td>\n      <td>780.0</td>\n    </tr>\n    <tr>\n      <th>HP</th>\n      <td>800.0</td>\n      <td>69.25875</td>\n      <td>25.534669</td>\n      <td>1.0</td>\n      <td>50.00</td>\n      <td>65.0</td>\n      <td>80.0</td>\n      <td>255.0</td>\n    </tr>\n    <tr>\n      <th>Attack</th>\n      <td>800.0</td>\n      <td>79.00125</td>\n      <td>32.457366</td>\n      <td>5.0</td>\n      <td>55.00</td>\n      <td>75.0</td>\n      <td>100.0</td>\n      <td>190.0</td>\n    </tr>\n    <tr>\n      <th>Defense</th>\n      <td>800.0</td>\n      <td>73.84250</td>\n      <td>31.183501</td>\n      <td>5.0</td>\n      <td>50.00</td>\n      <td>70.0</td>\n      <td>90.0</td>\n      <td>230.0</td>\n    </tr>\n    <tr>\n      <th>Sp. Atk</th>\n      <td>800.0</td>\n      <td>72.82000</td>\n      <td>32.722294</td>\n      <td>10.0</td>\n      <td>49.75</td>\n      <td>65.0</td>\n      <td>95.0</td>\n      <td>194.0</td>\n    </tr>\n    <tr>\n      <th>Sp. Def</th>\n      <td>800.0</td>\n      <td>71.90250</td>\n      <td>27.828916</td>\n      <td>20.0</td>\n      <td>50.00</td>\n      <td>70.0</td>\n      <td>90.0</td>\n      <td>230.0</td>\n    </tr>\n    <tr>\n      <th>Speed</th>\n      <td>800.0</td>\n      <td>68.27750</td>\n      <td>29.060474</td>\n      <td>5.0</td>\n      <td>45.00</td>\n      <td>65.0</td>\n      <td>90.0</td>\n      <td>180.0</td>\n    </tr>\n    <tr>\n      <th>Generation</th>\n      <td>800.0</td>\n      <td>3.32375</td>\n      <td>1.661290</td>\n      <td>1.0</td>\n      <td>2.00</td>\n      <td>3.0</td>\n      <td>5.0</td>\n      <td>6.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-64daa468-9cf4-46aa-82e6-7a5edb556ce4')\"\n              title=\"Convert this dataframe to an interactive table.\"\n              style=\"display:none;\">\n        \n  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n       width=\"24px\">\n    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n  </svg>\n      </button>\n      \n  <style>\n    .colab-df-container {\n      display:flex;\n      flex-wrap:wrap;\n      gap: 12px;\n    }\n\n    .colab-df-convert {\n      background-color: #E8F0FE;\n      border: none;\n      border-radius: 50%;\n      cursor: pointer;\n      display: none;\n      fill: #1967D2;\n      height: 32px;\n      padding: 0 0 0 0;\n      width: 32px;\n    }\n\n    .colab-df-convert:hover {\n      background-color: #E2EBFA;\n      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n      fill: #174EA6;\n    }\n\n    [theme=dark] .colab-df-convert {\n      background-color: #3B4455;\n      fill: #D2E3FC;\n    }\n\n    [theme=dark] .colab-df-convert:hover {\n      background-color: #434B5C;\n      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n      fill: #FFFFFF;\n    }\n  </style>\n\n      <script>\n        const buttonEl =\n          document.querySelector('#df-64daa468-9cf4-46aa-82e6-7a5edb556ce4 button.colab-df-convert');\n        buttonEl.style.display =\n          google.colab.kernel.accessAllowed ? 'block' : 'none';\n\n        async function convertToInteractive(key) {\n          const element = document.querySelector('#df-64daa468-9cf4-46aa-82e6-7a5edb556ce4');\n          const dataTable =\n            await google.colab.kernel.invokeFunction('convertToInteractive',\n                                                     [key], {});\n          if (!dataTable) return;\n\n          const docLinkHtml = 'Like what you see? Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  "},"metadata":{},"execution_count":38}],"execution_count":38},{"cell_type":"code","source":"#Scatterplot\npokemon.plot.scatter(x='Attack', y='Defense')","metadata":{"id":"a3ugzU8GEKyr","colab":{"height":568,"base_uri":"https://localhost:8080/"},"cell_id":"3acb9d68c6c844bd82fe2055e83d1401","outputId":"f665f9b5-b76f-4438-851a-9c394ce14004","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":25,"user_tz":180,"timestamp":1647389526889},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 0x7fe402e3b290>"},"metadata":{},"execution_count":39},{"output_type":"display_data","data":{"text/plain":"<Figure size 864x648 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"execution_count":39},{"cell_type":"markdown","source":"Hexplot\n\nUna gráfica hexagonal agrega puntos en el espacio en hexágonos y luego colorea esos hexágonos según los valores dentro de ellos.","metadata":{"id":"A33nYUS4EKys","cell_id":"4188498cb1134942a53b55ce06e03ca6","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"pokemon.plot.hexbin(x='Attack', y='Defense', gridsize=15)","metadata":{"id":"ISEqLXvUEKyt","colab":{"height":543,"base_uri":"https://localhost:8080/"},"cell_id":"9229dba5b8aa470aa9024f2ed45ddc57","outputId":"e54897a4-85b1-49f8-af1e-9677cf020628","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":810,"user_tz":180,"timestamp":1647389529212},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 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\n"},"metadata":{"needs_background":"light"}}],"execution_count":40},{"cell_type":"code","source":"#Filtramos la data y realizamos una agrupacion\npokemon_stats_legendary = pokemon.groupby(['Legendary', 'Generation']).mean()[['Attack', 'Defense']]\npokemon_stats_legendary","metadata":{"id":"jFQFblGbEKyv","colab":{"height":457,"base_uri":"https://localhost:8080/"},"cell_id":"9359e088d0af41b8bf8e938aeb2df383","outputId":"7b186f61-5436-495f-c945-874ee5a9a09a","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":8,"user_tz":180,"timestamp":1647389529951},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"                          Attack     Defense\nLegendary Generation                        \nFalse     1            74.981250   70.175000\n          2            70.693069   72.118812\n          3            76.971831   69.901408\n          4            79.620370   75.074074\n          5            78.246667   70.486667\n          6            70.459459   74.013514\nTrue      1           120.833333   89.166667\n          2            99.000000   99.000000\n          3           118.333333  107.222222\n          4           109.846154  103.538462\n          5           120.266667   90.733333\n          6           125.250000  101.375000","text/html":"\n  <div id=\"df-c8b62ee0-3d98-4f44-a8ba-76773e3d60e1\">\n    <div class=\"colab-df-container\">\n      <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></th>\n      <th>Attack</th>\n      <th>Defense</th>\n    </tr>\n    <tr>\n      <th>Legendary</th>\n      <th>Generation</th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th rowspan=\"6\" valign=\"top\">False</th>\n      <th>1</th>\n      <td>74.981250</td>\n      <td>70.175000</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>70.693069</td>\n      <td>72.118812</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>76.971831</td>\n      <td>69.901408</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>79.620370</td>\n      <td>75.074074</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>78.246667</td>\n      <td>70.486667</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>70.459459</td>\n      <td>74.013514</td>\n    </tr>\n    <tr>\n      <th rowspan=\"6\" valign=\"top\">True</th>\n      <th>1</th>\n      <td>120.833333</td>\n      <td>89.166667</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>99.000000</td>\n      <td>99.000000</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>118.333333</td>\n      <td>107.222222</td>\n    </tr>\n    <tr>\n      <th>4</th>\n     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"},"metadata":{},"execution_count":41}],"execution_count":41},{"cell_type":"code","source":"pokemon_stats_legendary.plot.bar(stacked=True)","metadata":{"id":"J0Q-ANB0EKyw","colab":{"height":604,"base_uri":"https://localhost:8080/"},"cell_id":"868ec5da428e40189680144b5534fee7","outputId":"85a5064d-8210-44e7-e5fe-8cf64935516c","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":462,"user_tz":180,"timestamp":1647389532480},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 0x7fe40368cf90>"},"metadata":{},"execution_count":42},{"output_type":"display_data","data":{"text/plain":"<Figure size 864x648 with 1 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\n"},"metadata":{"needs_background":"light"}}],"execution_count":42},{"cell_type":"code","source":"#Generamos otro dataset\npokemon_stats_by_generation = pokemon.groupby('Generation').mean()[['HP', 'Attack', 'Defense', 'Sp. Atk', 'Sp. Def', 'Speed']]\npokemon_stats_by_generation","metadata":{"id":"gxgjnJZYEKyy","colab":{"height":269,"base_uri":"https://localhost:8080/"},"cell_id":"c662de719f8c4f2796154ab4109f9615","outputId":"c717c7a2-5776-42e3-c57d-30ca0b23ebcd","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":32,"user_tz":180,"timestamp":1647389533852},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"                   HP     Attack    Defense    Sp. Atk    Sp. Def      Speed\nGeneration                                                                  \n1           65.819277  76.638554  70.861446  71.819277  69.090361  72.584337\n2           71.207547  72.028302  73.386792  65.943396  73.905660  61.811321\n3           66.543750  81.625000  74.100000  75.806250  71.225000  66.925000\n4           73.082645  82.867769  78.132231  76.404959  77.190083  71.338843\n5           71.787879  82.066667  72.327273  71.987879  68.739394  68.078788\n6           68.268293  75.804878  76.682927  74.292683  74.890244  66.439024","text/html":"\n  <div id=\"df-54cdf822-29a4-48e5-921b-a0b58d91cb6c\">\n    <div class=\"colab-df-container\">\n      <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>HP</th>\n      <th>Attack</th>\n      <th>Defense</th>\n      <th>Sp. Atk</th>\n      <th>Sp. 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"},"metadata":{},"execution_count":43}],"execution_count":43},{"cell_type":"code","source":"pokemon_stats_by_generation.plot.line()","metadata":{"id":"apqP2eMuEKyz","colab":{"height":568,"base_uri":"https://localhost:8080/"},"cell_id":"8f53dd7df4ad4f18a47f2d23d866e054","outputId":"af887a27-137f-48f0-c149-a753b618ee32","executionInfo":{"user":{"userId":"09471607480253994520","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjvGjd5VpSUEHTxlxXRYAinh8eCspL5nxvcW9wD=s64","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":49,"user_tz":180,"timestamp":1647389536213},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 0x7fe4035c27d0>"},"metadata":{},"execution_count":44},{"output_type":"display_data","data":{"text/plain":"<Figure size 864x648 with 1 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