N14) Visualizaciones_ Plotly.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"14) Visualizaciones: Plotly.ipynb","provenance":[],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["# PLotly"],"metadata":{"id":"EW8Mb9rGd7mO"}},{"cell_type":"code","source":["!pip install chart_studio"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jjWuSL0EeOK7","outputId":"b7cabe02-f1c0-4faa-d2da-fecb4cdd4d56","executionInfo":{"status":"ok","timestamp":1658689960373,"user_tz":240,"elapsed":10912,"user":{"displayName":"David Francisco Bustos Usta","userId":"09471607480253994520"}}},"execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Collecting chart_studio\n","  Downloading chart_studio-1.1.0-py3-none-any.whl (64 kB)\n","\u001b[K     |████████████████████████████████| 64 kB 913 kB/s \n","\u001b[?25hRequirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from chart_studio) (1.15.0)\n","Requirement already satisfied: plotly in /usr/local/lib/python3.7/dist-packages (from chart_studio) (5.5.0)\n","Collecting retrying>=1.3.3\n","  Downloading retrying-1.3.3.tar.gz (10 kB)\n","Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from chart_studio) (2.23.0)\n","Requirement already satisfied: tenacity>=6.2.0 in /usr/local/lib/python3.7/dist-packages (from plotly->chart_studio) (8.0.1)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->chart_studio) (2022.6.15)\n","Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->chart_studio) (1.24.3)\n","Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->chart_studio) (2.10)\n","Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->chart_studio) (3.0.4)\n","Building wheels for collected packages: retrying\n","  Building wheel for retrying (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for retrying: filename=retrying-1.3.3-py3-none-any.whl size=11447 sha256=eb9c8a284a70da8dcb4e3795b0c290e8d20fe9121f4e0b06f5478f62c5d15904\n","  Stored in directory: /root/.cache/pip/wheels/f9/8d/8d/f6af3f7f9eea3553bc2fe6d53e4b287dad18b06a861ac56ddf\n","Successfully built retrying\n","Installing collected packages: retrying, chart-studio\n","Successfully installed chart-studio-1.1.0 retrying-1.3.3\n"]}]},{"cell_type":"code","source":["# Importar librerias\n","import pandas as pd\n","import numpy as np\n","import chart_studio.plotly as py\n","import seaborn as sns\n","import plotly.express as px\n","#from plotly.offline import download_plotlyjs, init_notebook_mode,plot,plot, iplot\n","#init_notebook_mode(connected=True)"],"metadata":{"id":"4EDegYgEeBAN","executionInfo":{"status":"ok","timestamp":1658689971336,"user_tz":240,"elapsed":3005,"user":{"displayName":"David Francisco Bustos Usta","userId":"09471607480253994520"}}},"execution_count":2,"outputs":[]},{"cell_type":"markdown","source":["## Elementos basicos"],"metadata":{"id":"P6nkPUNufDDT"}},{"cell_type":"code","source":["arr= np.random.randn(50,4)\n","df= pd.DataFrame(arr, columns=['A','B','C','D'])\n","df.head()\n","df.plot()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":284},"id":"Ny9iFUVDfEWg","outputId":"7ac9ffc9-e15d-4f8a-9764-cd99697125d9","executionInfo":{"status":"ok","timestamp":1658689989470,"user_tz":240,"elapsed":611,"user":{"displayName":"David Francisco Bustos Usta","userId":"09471607480253994520"}}},"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f0b1b7effd0>"]},"metadata":{},"execution_count":3},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["df_stocks = px.data.stocks()\n","df_stocks"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":424},"id":"l6pgVUBboNoE","executionInfo":{"status":"ok","timestamp":1658690007054,"user_tz":240,"elapsed":277,"user":{"displayName":"David Francisco Bustos Usta","userId":"09471607480253994520"}},"outputId":"248f2f67-0c9e-47a6-85d4-eb1704bd986c"},"execution_count":4,"outputs":[{"output_type":"execute_result","data":{"text/plain":["           date      GOOG      AAPL      AMZN        FB      NFLX      MSFT\n","0    2018-01-01  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000\n","1    2018-01-08  1.018172  1.011943  1.061881  0.959968  1.053526  1.015988\n","2    2018-01-15  1.032008  1.019771  1.053240  0.970243  1.049860  1.020524\n","3    2018-01-22  1.066783  0.980057  1.140676  1.016858  1.307681  1.066561\n","4    2018-01-29  1.008773  0.917143  1.163374  1.018357  1.273537  1.040708\n","..          ...       ...       ...       ...       ...       ...       ...\n","100  2019-12-02  1.216280  1.546914  1.425061  1.075997  1.463641  1.720717\n","101  2019-12-09  1.222821  1.572286  1.432660  1.038855  1.421496  1.752239\n","102  2019-12-16  1.224418  1.596800  1.453455  1.104094  1.604362  1.784896\n","103  2019-12-23  1.226504  1.656000  1.521226  1.113728  1.567170  1.802472\n","104  2019-12-30  1.213014  1.678000  1.503360  1.098475  1.540883  1.788185\n","\n","[105 rows x 7 columns]"],"text/html":["\n","  <div id=\"df-4dbc755d-7d8f-4de7-9016-189cd73eb409\">\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>date</th>\n","      <th>GOOG</th>\n","      <th>AAPL</th>\n","      <th>AMZN</th>\n","      <th>FB</th>\n","      <th>NFLX</th>\n","      <th>MSFT</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>2018-01-01</td>\n","      <td>1.000000</td>\n","      <td>1.000000</td>\n","      <td>1.000000</td>\n","      <td>1.000000</td>\n","      <td>1.000000</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2018-01-08</td>\n","      <td>1.018172</td>\n","      <td>1.011943</td>\n","      <td>1.061881</td>\n","      <td>0.959968</td>\n","      <td>1.053526</td>\n","      <td>1.015988</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2018-01-15</td>\n","      <td>1.032008</td>\n","      <td>1.019771</td>\n","      <td>1.053240</td>\n","      <td>0.970243</td>\n","      <td>1.049860</td>\n","      <td>1.020524</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>2018-01-22</td>\n","      <td>1.066783</td>\n","      <td>0.980057</td>\n","      <td>1.140676</td>\n","      <td>1.016858</td>\n","      <td>1.307681</td>\n","      <td>1.066561</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>2018-01-29</td>\n","      <td>1.008773</td>\n","      <td>0.917143</td>\n","      <td>1.163374</td>\n","      <td>1.018357</td>\n","      <td>1.273537</td>\n","      <td>1.040708</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>100</th>\n","      <td>2019-12-02</td>\n","      <td>1.216280</td>\n","      <td>1.546914</td>\n","      <td>1.425061</td>\n","      <td>1.075997</td>\n","      <td>1.463641</td>\n","      <td>1.720717</td>\n","    </tr>\n","    <tr>\n","      <th>101</th>\n","      <td>2019-12-09</td>\n","      <td>1.222821</td>\n","      <td>1.572286</td>\n","      <td>1.432660</td>\n","      <td>1.038855</td>\n","      <td>1.421496</td>\n","      <td>1.752239</td>\n","    </tr>\n","    <tr>\n","      <th>102</th>\n","      <td>2019-12-16</td>\n","      <td>1.224418</td>\n","      <td>1.596800</td>\n","      <td>1.453455</td>\n","      <td>1.104094</td>\n","      <td>1.604362</td>\n","      <td>1.784896</td>\n","    </tr>\n","    <tr>\n","      <th>103</th>\n","      <td>2019-12-23</td>\n","      <td>1.226504</td>\n","      <td>1.656000</td>\n","      <td>1.521226</td>\n","      <td>1.113728</td>\n","      <td>1.567170</td>\n","      <td>1.802472</td>\n","    </tr>\n","    <tr>\n","      <th>104</th>\n","      <td>2019-12-30</td>\n","      <td>1.213014</td>\n","      <td>1.678000</td>\n","      <td>1.503360</td>\n","      <td>1.098475</td>\n","      <td>1.540883</td>\n","      <td>1.788185</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>105 rows × 7 columns</p>\n","</div>\n","      <button 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<td>Asia</td>\n","      <td>1957</td>\n","      <td>30.332</td>\n","      <td>9240934</td>\n","      <td>820.853030</td>\n","      <td>AFG</td>\n","      <td>4</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>Afghanistan</td>\n","      <td>Asia</td>\n","      <td>1962</td>\n","      <td>31.997</td>\n","      <td>10267083</td>\n","      <td>853.100710</td>\n","      <td>AFG</td>\n","      <td>4</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Afghanistan</td>\n","      <td>Asia</td>\n","      <td>1967</td>\n","      <td>34.020</td>\n","      <td>11537966</td>\n","      <td>836.197138</td>\n","      <td>AFG</td>\n","      <td>4</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Afghanistan</td>\n","      <td>Asia</td>\n","      <td>1972</td>\n","      <td>36.088</td>\n","      <td>13079460</td>\n","      <td>739.981106</td>\n","      <td>AFG</td>\n","      <td>4</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>1699</th>\n","      <td>Zimbabwe</td>\n","      <td>Africa</td>\n","      <td>1987</td>\n","      <td>62.351</td>\n","      <td>9216418</td>\n","      <td>706.157306</td>\n","      <td>ZWE</td>\n","      <td>716</td>\n","    </tr>\n","    <tr>\n","      <th>1700</th>\n","      <td>Zimbabwe</td>\n","      <td>Africa</td>\n","      <td>1992</td>\n","      <td>60.377</td>\n","      <td>10704340</td>\n","      <td>693.420786</td>\n","      <td>ZWE</td>\n","      <td>716</td>\n","    </tr>\n","    <tr>\n","      <th>1701</th>\n","      <td>Zimbabwe</td>\n","      <td>Africa</td>\n","      <td>1997</td>\n","      <td>46.809</td>\n","      <td>11404948</td>\n","      <td>792.449960</td>\n","      <td>ZWE</td>\n","      <td>716</td>\n","    </tr>\n","    <tr>\n","      <th>1702</th>\n","      <td>Zimbabwe</td>\n","      <td>Africa</td>\n","      <td>2002</td>\n","      <td>39.989</td>\n","      <td>11926563</td>\n","      <td>672.038623</td>\n","      <td>ZWE</td>\n","      <td>716</td>\n","    </tr>\n","    <tr>\n","      <th>1703</th>\n","      <td>Zimbabwe</td>\n","      <td>Africa</td>\n","      <td>2007</td>\n","      <td>43.487</td>\n","      <td>12311143</td>\n","      <td>469.709298</td>\n","      <td>ZWE</td>\n","      <td>716</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>1704 rows × 8 columns</p>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e47ab0e8-82a3-4444-a134-6da499a908ed')\"\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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Usta","userId":"09471607480253994520"}}},"execution_count":28,"outputs":[{"output_type":"stream","name":"stdout","text":["Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Collecting gapminder\n","  Downloading gapminder-0.1-py3-none-any.whl (32 kB)\n","Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from gapminder) (1.3.5)\n","Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas->gapminder) (2022.1)\n","Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.7/dist-packages (from pandas->gapminder) (1.21.6)\n","Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->gapminder) (2.8.2)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->gapminder) (1.15.0)\n","Installing collected packages: gapminder\n","Successfully installed gapminder-0.1\n"]}]},{"cell_type":"code","source":["from gapminder import gapminder\n","gapminder.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"S35RPpq3zq1t","outputId":"10cc3b99-d67f-4ba8-cfad-cc838ee79894","executionInfo":{"status":"ok","timestamp":1658691082780,"user_tz":240,"elapsed":21,"user":{"displayName":"David Francisco Bustos Usta","userId":"09471607480253994520"}}},"execution_count":29,"outputs":[{"output_type":"execute_result","data":{"text/plain":["       country continent  year  lifeExp       pop   gdpPercap\n","0  Afghanistan      Asia  1952   28.801   8425333  779.445314\n","1  Afghanistan      Asia  1957   30.332   9240934  820.853030\n","2  Afghanistan      Asia  1962   31.997  10267083  853.100710\n","3  Afghanistan      Asia  1967   34.020  11537966  836.197138\n","4  Afghanistan      Asia  1972   36.088  13079460  739.981106"],"text/html":["\n","  <div id=\"df-1fdc584b-d8d9-45e6-9a7c-b0803c2a0d63\">\n","    <div 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<td>30.332</td>\n","      <td>9240934</td>\n","      <td>820.853030</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>Afghanistan</td>\n","      <td>Asia</td>\n","      <td>1962</td>\n","      <td>31.997</td>\n","      <td>10267083</td>\n","      <td>853.100710</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Afghanistan</td>\n","      <td>Asia</td>\n","      <td>1967</td>\n","      <td>34.020</td>\n","      <td>11537966</td>\n","      <td>836.197138</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Afghanistan</td>\n","      <td>Asia</td>\n","      <td>1972</td>\n","      <td>36.088</td>\n","      <td>13079460</td>\n","      <td>739.981106</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1fdc584b-d8d9-45e6-9a7c-b0803c2a0d63')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              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<td>2002</td>\n","      <td>39.989</td>\n","      <td>11926563</td>\n","      <td>672.038623</td>\n","    </tr>\n","    <tr>\n","      <th>1703</th>\n","      <td>Zimbabwe</td>\n","      <td>Africa</td>\n","      <td>2007</td>\n","      <td>43.487</td>\n","      <td>12311143</td>\n","      <td>469.709298</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-61159c74-50dc-4cc7-bcf9-506975ec42d5')\"\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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Usta","userId":"09471607480253994520"}}},"execution_count":32,"outputs":[{"output_type":"display_data","data":{"text/html":["<html>\n","<head><meta charset=\"utf-8\" /></head>\n","<body>\n","    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n","        <script src=\"https://cdn.plot.ly/plotly-2.8.3.min.js\"></script>                <div id=\"3def955f-76b5-4bba-831d-1ced40b2f729\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"3def955f-76b5-4bba-831d-1ced40b2f729\")) {                   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