{"cells":[{"cell_type":"code","source":"x = 15 + 1.3\n  \nprint(x)","metadata":{"id":"vKfV2rZzXLz0","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"0191dbcbd56e4a549c9e42ee02a6b5b6","outputId":"c930536f-9b23-4c01-e316-c9cd61f6500f","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":6,"user_tz":300,"timestamp":1640315214623},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"16.3\n"}],"execution_count":null},{"cell_type":"code","source":"x = 40\ny = 12\n  \nadd = x + y\nsub = x - y\npro = x * y\ndiv = x / y\n  \nprint(add)\nprint(sub)\nprint(pro)\nprint(div)","metadata":{"id":"FbXFdY1ZasT9","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"0bfd1c25f49f42e6946b8eb2f97ad037","outputId":"208a6c91-e475-467b-bb1a-13575b445826","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":286,"user_tz":300,"timestamp":1640315408025},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"52\n28\n480\n3.3333333333333335\n"}],"execution_count":null},{"cell_type":"code","source":"a = 13\nb = 12.0\n  \nc = a + int(b)\nprint(c)","metadata":{"id":"SVN3NDWqbFHQ","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"bc07ac1206634b28ab518acf1eaeacbd","outputId":"9032a0ae-243e-4eb6-fbd9-956a0cc381cf","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":353,"user_tz":300,"timestamp":1640315509626},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"25\n"}],"execution_count":null},{"cell_type":"code","source":"a = 13\nb = 5\n  \nc = a / b\nprint(c)","metadata":{"id":"n7FX9R68bYki","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"7f80f0b1aeba4e1e82807ad0f09df7a4","outputId":"52baa332-eb33-4e18-82b3-3b88a50fde1a","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":402,"user_tz":300,"timestamp":1640315588873},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"2.6\n"}],"execution_count":null},{"cell_type":"markdown","source":"# Desafio generico","metadata":{"id":"HclmFDdpXWd4","cell_id":"6b2c303524c342088f703cae315aa2ac","deepnote_cell_type":"markdown"}},{"cell_type":"markdown","source":"# Lectura de informacion\n\nLos datos se encuentran en la siguiente link:\n[Data Acciones](https://raw.githubusercontent.com/JJTorresDS/stocks-ds-edu/main/stocks.csv)\n\n","metadata":{"id":"Ofv1tHEg7dVT","cell_id":"dc8fd04d33cd4519abd7f188ea5fabda","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"import pandas as pd\n\nurl = 'https://raw.githubusercontent.com/JJTorresDS/stocks-ds-edu/main/stocks.csv'\ndf = pd.read_csv(url, index_col=0)\nprint(df.head(5))","metadata":{"id":"UBQeIbm17wPf","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"5e6477c9a08f48f99376113cf3441cad","outputId":"5b174074-2681-44ef-d260-6d6baf1236bb","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":270,"user_tz":300,"timestamp":1639743502640},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"                       MCD        SBUX  ...          MA        PYPL\nformatted_date                          ...                        \n2021-01-01      203.187836   95.235695  ...  314.746094  234.309998\n2021-02-01      201.525894  106.273232  ...  352.569061  259.850006\n2021-03-01      220.471207  107.950699  ...  354.761108  242.839996\n2021-04-01      232.215775  113.107674  ...  380.676971  262.290009\n2021-05-01      230.061630  112.505043  ...  359.701202  260.019989\n\n[5 rows x 14 columns]\n"}],"execution_count":null},{"cell_type":"code","source":"df.head()","metadata":{"id":"nwtJItv78FYY","colab":{"height":302,"base_uri":"https://localhost:8080/"},"cell_id":"be0ebb23201a4ed790bcf32fea5953b1","outputId":"49a50a00-32b5-4149-c6bd-059f800fef1e","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":17,"user_tz":300,"timestamp":1639743503793},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"\n  <div id=\"df-4ec53355-564c-4745-a885-a5fd91dd79c0\">\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>MCD</th>\n      <th>SBUX</th>\n      <th>GOOG</th>\n      <th>AMZN</th>\n      <th>MSFT</th>\n      <th>JPM</th>\n      <th>BAC</th>\n      <th>C</th>\n      <th>MAR</th>\n      <th>HLT</th>\n      <th>RCL</th>\n      <th>V</th>\n      <th>MA</th>\n      <th>PYPL</th>\n    </tr>\n    <tr>\n      <th>formatted_date</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      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2021-01-01</th>\n      <td>203.187836</td>\n      <td>95.235695</td>\n      <td>1835.739990</td>\n      <td>3206.199951</td>\n      <td>230.031799</td>\n      <td>125.517960</td>\n      <td>29.089981</td>\n      <td>56.271671</td>\n      <td>116.309998</td>\n      <td>101.389999</td>\n      <td>65.000000</td>\n      <td>192.070175</td>\n      <td>314.746094</td>\n      <td>234.309998</td>\n    </tr>\n    <tr>\n      <th>2021-02-01</th>\n      <td>201.525894</td>\n      <td>106.273232</td>\n      <td>2036.859985</td>\n      <td>3092.929932</td>\n      <td>230.448318</td>\n      <td>144.598679</td>\n      <td>34.054409</td>\n      <td>64.472809</td>\n      <td>148.070007</td>\n      <td>123.680000</td>\n      <td>93.269997</td>\n      <td>211.093323</td>\n      <td>352.569061</td>\n      <td>259.850006</td>\n    </tr>\n    <tr>\n      <th>2021-03-01</th>\n      <td>220.471207</td>\n      <td>107.950699</td>\n      <td>2068.629883</td>\n      <td>3094.080078</td>\n      <td>234.348633</td>\n      <td>149.570267</td>\n      <td>37.959236</td>\n      <td>71.196068</td>\n      <td>148.110001</td>\n      <td>120.919998</td>\n      <td>85.610001</td>\n      <td>210.764023</td>\n      <td>354.761108</td>\n      <td>242.839996</td>\n    </tr>\n    <tr>\n      <th>2021-04-01</th>\n      <td>232.215775</td>\n      <td>113.107674</td>\n      <td>2410.120117</td>\n      <td>3467.419922</td>\n      <td>250.659698</td>\n      <td>151.122665</td>\n      <td>39.961990</td>\n      <td>69.718323</td>\n      <td>148.520004</td>\n      <td>128.699997</td>\n      <td>86.949997</td>\n      <td>232.494446</td>\n      <td>380.676971</td>\n      <td>262.290009</td>\n    </tr>\n    <tr>\n      <th>2021-05-01</th>\n      <td>230.061630</td>\n      <td>112.505043</td>\n      <td>2411.560059</td>\n      <td>3223.070068</td>\n      <td>248.174774</td>\n      <td>162.320847</td>\n      <td>41.795921</td>\n      <td>77.564484</td>\n      <td>143.580002</td>\n      <td>125.269997</td>\n      <td>93.269997</td>\n      <td>226.263016</td>\n      <td>359.701202</td>\n      <td>260.019989</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4ec53355-564c-4745-a885-a5fd91dd79c0')\"\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 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.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-4ec53355-564c-4745-a885-a5fd91dd79c0 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-4ec53355-564c-4745-a885-a5fd91dd79c0');\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  ","text/plain":"                       MCD        SBUX  ...          MA        PYPL\nformatted_date                          ...                        \n2021-01-01      203.187836   95.235695  ...  314.746094  234.309998\n2021-02-01      201.525894  106.273232  ...  352.569061  259.850006\n2021-03-01      220.471207  107.950699  ...  354.761108  242.839996\n2021-04-01      232.215775  113.107674  ...  380.676971  262.290009\n2021-05-01      230.061630  112.505043  ...  359.701202  260.019989\n\n[5 rows x 14 columns]"},"metadata":{},"execution_count":2}],"execution_count":null},{"cell_type":"markdown","source":"Miremos el tamaño de nuestro datraframe","metadata":{"id":"b2VuYDsS8Ihe","cell_id":"28884d527b294d49bb73a445c34429c2","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"df.shape","metadata":{"id":"QeyozF0i8Kfb","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"2a70b3e735f245e2959b82328e3326d8","outputId":"a9fa439b-155c-4387-e35f-38070048e8a9","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":335,"user_tz":300,"timestamp":1639743508383},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"(11, 14)"},"metadata":{},"execution_count":3}],"execution_count":null},{"cell_type":"markdown","source":"11 filas x 14 columnas","metadata":{"id":"ZJAOuD7O8LjI","cell_id":"b275a6cfff434d8e820236c0283f6a79","deepnote_cell_type":"markdown"}},{"cell_type":"markdown","source":"Las columnas son los precios de acciones de:\n\n1. MCD: Macdonals\n2. SBUX: Starbucks\n3. GOOG: Google\n4. AMZN: Amazon\n5. MSFT: Microsoft\n6. JPM: JPMorgan Chase & Co.\n7. BAC: Bank of America Corp\n8. C: Citigroup\n9. MAR: Pharma MAr\n10. HLT: Hoteles Hilton\n11. RCL: Royal Caribbean Cruises\n12. V: Visa Inc.\n13. MA: Mastercard \n14. PYPL: Paypal","metadata":{"id":"ytyHdFzvC6ed","cell_id":"58e9c33ee4dd47369b2ce6e3bbe9ce0f","deepnote_cell_type":"markdown"}},{"cell_type":"markdown","source":"# Parte 1","metadata":{"id":"TUW-Dq0oXRSf","cell_id":"78e2a47bbea34694adc6db2034e6ada9","deepnote_cell_type":"markdown"}},{"cell_type":"markdown","source":"# Analizando el comportamiento de una serie de tiempo","metadata":{"id":"b9n7zuxd8Njf","cell_id":"1d89f0eadc024f95b83d0635184cd222","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"df['GOOG'].plot(kind='line',figsize=(10,6),xlabel='Fecha', ylabel='Precio Accion', title='Precio Accion vs Fecha')","metadata":{"id":"bDXqJ3mW8RLY","colab":{"height":421,"base_uri":"https://localhost:8080/"},"cell_id":"4d6bdd806f7f463d840d2c8523d74fce","outputId":"465e6f32-4928-4968-e351-feb38b19883e","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":1134,"user_tz":300,"timestamp":1639743529507},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 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\n","text/plain":"<Figure size 720x432 with 1 Axes>"},"metadata":{"needs_background":"light"}}],"execution_count":null},{"cell_type":"markdown","source":"Se observa un comportamiento creciente entre el 01/01/21 hasta el 11/01/2021 ","metadata":{"id":"h5j609z182p2","cell_id":"795197758a7947718e066ab5c927cad2","deepnote_cell_type":"markdown"}},{"cell_type":"markdown","source":"# Extraccion usando indices booleanos","metadata":{"id":"YXP3OX7KVPpJ","cell_id":"610de933714b4432b72944452d080d04","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"columnas=list(df.columns)\ngoogle= [x for x in columnas if x =='GOOG']\ngoogle","metadata":{"id":"oxKuxq5mVg7-","cell_id":"416ad2a83aa94bab920053f14862c124","deepnote_cell_type":"code"},"outputs":[],"execution_count":null},{"cell_type":"code","source":"indice_col=list(df.columns=='GOOG')\ndf_goog=df.loc[:,indice_col]\ndf_goog # Hemos terminado","metadata":{"id":"c4uPOHZDVRpm","colab":{"height":426,"base_uri":"https://localhost:8080/"},"cell_id":"94112ba7add24dcfb9d5f57c26f66a81","outputId":"5aa86b32-5860-4782-f0f1-682862a7aeed","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":431,"user_tz":300,"timestamp":1639743796992},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"\n  <div id=\"df-f1083207-0013-400b-a9ad-630f015e9f85\">\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>GOOG</th>\n    </tr>\n    <tr>\n      <th>formatted_date</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2021-01-01</th>\n      <td>1835.739990</td>\n    </tr>\n    <tr>\n      <th>2021-02-01</th>\n      <td>2036.859985</td>\n    </tr>\n    <tr>\n      <th>2021-03-01</th>\n      <td>2068.629883</td>\n    </tr>\n    <tr>\n      <th>2021-04-01</th>\n      <td>2410.120117</td>\n    </tr>\n    <tr>\n      <th>2021-05-01</th>\n      <td>2411.560059</td>\n    </tr>\n    <tr>\n      <th>2021-06-01</th>\n      <td>2506.320068</td>\n    </tr>\n    <tr>\n      <th>2021-07-01</th>\n      <td>2704.419922</td>\n    </tr>\n    <tr>\n      <th>2021-08-01</th>\n      <td>2909.239990</td>\n    </tr>\n    <tr>\n      <th>2021-09-01</th>\n      <td>2665.310059</td>\n    </tr>\n    <tr>\n      <th>2021-10-01</th>\n      <td>2965.409912</td>\n    </tr>\n    <tr>\n      <th>2021-11-01</th>\n      <td>2849.040039</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f1083207-0013-400b-a9ad-630f015e9f85')\"\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      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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  ","text/plain":"                       GOOG\nformatted_date             \n2021-01-01      1835.739990\n2021-02-01      2036.859985\n2021-03-01      2068.629883\n2021-04-01      2410.120117\n2021-05-01      2411.560059\n2021-06-01      2506.320068\n2021-07-01      2704.419922\n2021-08-01      2909.239990\n2021-09-01      2665.310059\n2021-10-01      2965.409912\n2021-11-01      2849.040039"},"metadata":{},"execution_count":14}],"execution_count":null},{"cell_type":"markdown","source":"# Grafico interactivo\n\n","metadata":{"id":"PL8pbOGgFgZn","cell_id":"f36e2908319e46b2863ab19932b2ca28","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"df_n= df_goog.copy()\ndf_n['Fecha']= df_n.index \ndf_n= df_n.reset_index(drop=True)\ndf_n['Fecha']=pd.to_datetime(df_n['Fecha'])\ndf_n","metadata":{"id":"nSGh5VWcWVMh","colab":{"height":395,"base_uri":"https://localhost:8080/"},"cell_id":"7d494e8314bd4a9ab7241d35cb696cdc","outputId":"26ae9d00-1b20-452f-bd31-135668c0a3ae","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":23,"user_tz":300,"timestamp":1639743909398},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"\n  <div id=\"df-463a237f-98ff-4030-b0c4-c74d053e8448\">\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>GOOG</th>\n      <th>Fecha</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1835.739990</td>\n      <td>2021-01-01</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2036.859985</td>\n      <td>2021-02-01</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2068.629883</td>\n      <td>2021-03-01</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2410.120117</td>\n      <td>2021-04-01</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2411.560059</td>\n      <td>2021-05-01</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2506.320068</td>\n      <td>2021-06-01</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2704.419922</td>\n      <td>2021-07-01</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>2909.239990</td>\n      <td>2021-08-01</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>2665.310059</td>\n      <td>2021-09-01</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>2965.409912</td>\n      <td>2021-10-01</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>2849.040039</td>\n      <td>2021-11-01</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-463a237f-98ff-4030-b0c4-c74d053e8448')\"\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 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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  ","text/plain":"           GOOG      Fecha\n0   1835.739990 2021-01-01\n1   2036.859985 2021-02-01\n2   2068.629883 2021-03-01\n3   2410.120117 2021-04-01\n4   2411.560059 2021-05-01\n5   2506.320068 2021-06-01\n6   2704.419922 2021-07-01\n7   2909.239990 2021-08-01\n8   2665.310059 2021-09-01\n9   2965.409912 2021-10-01\n10  2849.040039 2021-11-01"},"metadata":{},"execution_count":18}],"execution_count":null},{"cell_type":"code","source":"import plotly.express as px\n\n\nfig=px.line(data_frame=df_n,x='Fecha',y='GOOG',title='Comportamiento GOOGLE',\\\n             labels={\n                     \"Fecha\": \"Fecha_dias\",\n                     \"value\": \"Precio (USD)\"\n                 })\nfig.update_layout(paper_bgcolor=\"#FFFFFF\",plot_bgcolor='#FFFFFF',)\n\nfig.show()","metadata":{"id":"tcyOiOxrEMJn","colab":{"height":542,"base_uri":"https://localhost:8080/"},"cell_id":"791f7185b9bb419dbf134a3e976e34bb","outputId":"0b1cf388-60df-49b7-8a3f-0cd66943f0f4","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos 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2","metadata":{"id":"BST8_-IOXUBC","cell_id":"75dd9306d09e448da88549167cc16b73","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"df_n","metadata":{"id":"b2mWGzfsXVLB","colab":{"height":395,"base_uri":"https://localhost:8080/"},"cell_id":"93d8f2d97b434598afdb61f6a30eaa4e","outputId":"70aef985-8151-4f12-e159-f4a805742509","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":256,"user_tz":300,"timestamp":1639744143968},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"\n  <div id=\"df-30d67d75-617c-4186-8ad0-33b8e2b0b92f\">\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 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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  ","text/plain":"           GOOG      Fecha\n0   1835.739990 2021-01-01\n1   2036.859985 2021-02-01\n2   2068.629883 2021-03-01\n3   2410.120117 2021-04-01\n4   2411.560059 2021-05-01\n5   2506.320068 2021-06-01\n6   2704.419922 2021-07-01\n7   2909.239990 2021-08-01\n8   2665.310059 2021-09-01\n9   2965.409912 2021-10-01\n10  2849.040039 2021-11-01"},"metadata":{},"execution_count":20}],"execution_count":null},{"cell_type":"code","source":"pasos = 2\ndef my_fun(x):\n    return x.iloc[-1] - x.iloc[0]\n\ndf_n['Dif']=df_n['GOOG'].rolling(window=pasos).apply(my_fun) # Hacemos la diferencia del valor actual - anterior\ndf_n","metadata":{"id":"D-9MK3XXXgem","colab":{"height":395,"base_uri":"https://localhost:8080/"},"cell_id":"a953c7a2d79b492dab281fcedc64200f","outputId":"853eff9d-e8a3-4722-b8fb-4f545c6efa16","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":239,"user_tz":300,"timestamp":1639744193648},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"\n  <div id=\"df-426fcd95-1b65-4ad2-9ce1-65a4d1c56398\">\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>GOOG</th>\n      <th>Fecha</th>\n      <th>Dif</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1835.739990</td>\n      <td>2021-01-01</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2036.859985</td>\n      <td>2021-02-01</td>\n      <td>201.119995</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2068.629883</td>\n      <td>2021-03-01</td>\n      <td>31.769897</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2410.120117</td>\n      <td>2021-04-01</td>\n      <td>341.490234</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2411.560059</td>\n      <td>2021-05-01</td>\n      <td>1.439941</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2506.320068</td>\n      <td>2021-06-01</td>\n      <td>94.760010</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2704.419922</td>\n      <td>2021-07-01</td>\n      <td>198.099854</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>2909.239990</td>\n      <td>2021-08-01</td>\n      <td>204.820068</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>2665.310059</td>\n      <td>2021-09-01</td>\n      <td>-243.929932</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>2965.409912</td>\n      <td>2021-10-01</td>\n      <td>300.099854</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>2849.040039</td>\n      <td>2021-11-01</td>\n      <td>-116.369873</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-426fcd95-1b65-4ad2-9ce1-65a4d1c56398')\"\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-426fcd95-1b65-4ad2-9ce1-65a4d1c56398 button.colab-df-convert');\n        buttonEl.style.display =\n          google.colab.kernel.accessAllowed ? 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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  ","text/plain":"           GOOG      Fecha         Dif\n0   1835.739990 2021-01-01         NaN\n1   2036.859985 2021-02-01  201.119995\n2   2068.629883 2021-03-01   31.769897\n3   2410.120117 2021-04-01  341.490234\n4   2411.560059 2021-05-01    1.439941\n5   2506.320068 2021-06-01   94.760010\n6   2704.419922 2021-07-01  198.099854\n7   2909.239990 2021-08-01  204.820068\n8   2665.310059 2021-09-01 -243.929932\n9   2965.409912 2021-10-01  300.099854\n10  2849.040039 2021-11-01 -116.369873"},"metadata":{},"execution_count":22}],"execution_count":null},{"cell_type":"code","source":"# HAcemos un filtro de cuando los valores de Dif <0\nindex_bool= df_n.Dif<0\nindex_bool","metadata":{"id":"ZxtSlKy9XwY5","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"23eee262f4a347b6849d025eaa901a4b","outputId":"2fff4ea1-113a-4dbc-931a-75786ead1bcb","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":253,"user_tz":300,"timestamp":1639744242875},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"0     False\n1     False\n2     False\n3     False\n4     False\n5     False\n6     False\n7     False\n8      True\n9     False\n10     True\nName: Dif, dtype: bool"},"metadata":{},"execution_count":23}],"execution_count":null},{"cell_type":"code","source":"# Ahora podemos aplicar el filtro sobre el objeto data frame\ndf_neg=df_n.loc[index_bool,:]\ndf_neg","metadata":{"id":"SkkegY8gX5Vn","colab":{"height":112,"base_uri":"https://localhost:8080/"},"cell_id":"a4c699ec1328428580bcc6a35c327f6e","outputId":"d5218286-4c7b-4103-d458-b1d1cf20a893","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":436,"user_tz":300,"timestamp":1639744336196},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"\n  <div id=\"df-618ea721-4f00-49c9-ade2-d94d7e57f759\">\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>GOOG</th>\n      <th>Fecha</th>\n      <th>Dif</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>8</th>\n      <td>2665.310059</td>\n      <td>2021-09-01</td>\n      <td>-243.929932</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>2849.040039</td>\n      <td>2021-11-01</td>\n      <td>-116.369873</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-618ea721-4f00-49c9-ade2-d94d7e57f759')\"\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-618ea721-4f00-49c9-ade2-d94d7e57f759 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-618ea721-4f00-49c9-ade2-d94d7e57f759');\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  ","text/plain":"           GOOG      Fecha         Dif\n8   2665.310059 2021-09-01 -243.929932\n10  2849.040039 2021-11-01 -116.369873"},"metadata":{},"execution_count":25}],"execution_count":null},{"cell_type":"markdown","source":"Solo existieron dos días donde la accion bajo de precio","metadata":{"id":"1UtVGx91YDRx","cell_id":"48bd6f80330f40289bc2ef7ffd8170e9","deepnote_cell_type":"markdown"}},{"cell_type":"markdown","source":"# Graficando fechas donde ocurrio la bajada","metadata":{"id":"cJ-yd5CiYHL5","cell_id":"c75ebb78e7e944b797f73824169fdfac","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"import matplotlib.pyplot as plt\nfig,ax= plt.subplots(figsize=(10,6))\nax.plot(df_n.Fecha,df_n.GOOG)\nax.scatter(x=df_neg.Fecha, y= df_neg.GOOG, s=20, color='red', label='R')\nax.set_xlabel('Fecha')\nax.set_ylabel('Precio')\nax.set_title('Precio Accion vs tiempo')\nax.legend(loc='upper left')","metadata":{"id":"4hx_iT3AYJ2z","colab":{"height":421,"base_uri":"https://localhost:8080/"},"cell_id":"544139cfead64496af823da98e675d47","outputId":"e680c7ee-89ac-4587-de55-e04d7e0a29af","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":743,"user_tz":300,"timestamp":1639744655956},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"<matplotlib.legend.Legend at 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\n","text/plain":"<Figure size 720x432 with 1 Axes>"},"metadata":{"needs_background":"light"}}],"execution_count":null},{"cell_type":"markdown","source":"# Desafio\n\nIntenten hacer le mismo procedimiento para AMZN y observen si existe el mismo patron","metadata":{"id":"E-AyDhc8ZlMx","cell_id":"64c8d88f116a4c6b9587d263cdd1b849","deepnote_cell_type":"markdown"}},{"cell_type":"markdown","source":"Con esto entonces podemos monitorear cuando una accion puede disminuir su valor","metadata":{"id":"r06BKUeeZeJ0","cell_id":"940fefb6064242059ef0e8433f8ec38f","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"","metadata":{"id":"HbZoJTaiX8Qa","cell_id":"e205341e6c154e8a9cfbc6f96d921899","deepnote_cell_type":"code"},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<a style='text-decoration:none;line-height:16px;display:flex;color:#5B5B62;padding:10px;justify-content:end;' href='https://deepnote.com?utm_source=created-in-deepnote-cell&projectId=4f9037d8-f2e9-4683-9ce3-67576f784ec7' target=\"_blank\">\n<img alt='Created in deepnote.com' style='display:inline;max-height:16px;margin:0px;margin-right:7.5px;' src='data:image/svg+xml;base64,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' > </img>\nCreated in <span style='font-weight:600;margin-left:4px;'>Deepnote</span></a>","metadata":{"created_in_deepnote_cell":true,"deepnote_cell_type":"markdown"}}],"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[]},"deepnote":{},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"deepnote_notebook_id":"76ed2b833b7748599d5574f6330c8879","deepnote_execution_queue":[]}}