infnet_dash.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "infnet_dash.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyPrZF8Qcc2Nd1EpzNGI8klL",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/naokityokoyama/infnet/blob/main/infnet_dash.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6kXh1Eh87GKd",
        "outputId": "c4508748-09eb-4116-e652-8b8fe6298b75"
      },
      "source": [
        "!pip install dash\n",
        "!pip install dash_bootstrap_components\n",
        "!pip install jupyter-dash"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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          ],
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 671
        },
        "id": "kvoTmaRiyuub",
        "outputId": "d3c1bff3-b752-45e0-a9f2-6d61ad30c8e6"
      },
      "source": [
        "from fbprophet import Prophet\n",
        "import pandas as pd\n",
        "import plotly.express as px\n",
        "from jupyter_dash import JupyterDash\n",
        "\n",
        "import dash\n",
        "import dash_core_components as dcc\n",
        "import dash_html_components as html\n",
        "import dash_bootstrap_components as dbc\n",
        "import plotly.express as px \n",
        "from dash.dependencies import Input, Output\n",
        "\n",
        "#dataset\n",
        "df = pd.read_csv('https://raw.githubusercontent.com/naokityokoyama/infnet/main/train.csv')\n",
        "\n",
        "lista_lojas = range(1,46)\n",
        "lista_semanas = range(2,6)\n",
        "\n",
        "def select_store_1(n,p):\n",
        "  data = df[df['Store']==n]\n",
        "  data = data.drop(['Dept', 'IsHoliday', 'Store'], axis=1)\n",
        "  data = data.rename(columns={'Date':'ds', 'Weekly_Sales':'y'})\n",
        "  data = data.groupby('ds').sum().reset_index()\n",
        "\n",
        "  m = Prophet(yearly_seasonality=True)\n",
        "  m.add_country_holidays(country_name='US')\n",
        "  m.fit(data)\n",
        "  future = m.make_future_dataframe(periods=p, freq='w')\n",
        "  forecast = m.predict(future)\n",
        "  return round(forecast[['ds', 'yhat']]).tail(p)\n",
        "\n",
        "def select_store_2(n,p):\n",
        "  data = df[df['Store']==n]\n",
        "  data = data.drop(['Dept', 'IsHoliday', 'Store'], axis=1)\n",
        "  data = data.rename(columns={'Date':'ds', 'Weekly_Sales':'y'})\n",
        "  data = data.groupby('ds').sum().reset_index()\n",
        "\n",
        "  m = Prophet(yearly_seasonality=True)\n",
        "  m.add_country_holidays(country_name='US')\n",
        "  m.fit(data)\n",
        "  future = m.make_future_dataframe(periods=p, freq='w')\n",
        "  forecast = m.predict(future)\n",
        "  return round(forecast[['ds', 'yhat']])\n",
        "\n",
        "app = JupyterDash(external_stylesheets=[dbc.themes.CYBORG])\n",
        "\n",
        "controls = dbc.Card(\n",
        "    [\n",
        "        dbc.FormGroup(\n",
        "            [\n",
        "                dbc.Label(\"Select Store\"),\n",
        "                dcc.Dropdown(\n",
        "                    id=\"x-variable\",\n",
        "                    value='1',\n",
        "                    options=[\n",
        "                        {\"label\": col, \"value\": col} for col in lista_lojas\n",
        "                    ]\n",
        "                 \n",
        "                )\n",
        "            ]\n",
        "        ),\n",
        "        dbc.FormGroup(\n",
        "            [\n",
        "                dbc.Label(\"Select week number\"),\n",
        "                dcc.Dropdown(\n",
        "                    id=\"y-variable\",\n",
        "                    value='2',\n",
        "                    options=[\n",
        "                        {\"label\": col, \"value\": col} for col in lista_semanas\n",
        "                    ]\n",
        "                    \n",
        "                )\n",
        "            ]\n",
        "        )\n",
        "      ],\n",
        "    #body=True,\n",
        ")\n",
        "\n",
        "grafico1 = dcc.Graph(id='grafico1', config={'displayModeBar':False})\n",
        "grafico2 = dcc.Graph(id='grafico2', config={'displayModeBar':False})\n",
        "\n",
        "\n",
        "grid1 = html.Div([\n",
        "                  \n",
        "    #dbc.Row(dbc.Col(dbc.Alert('Barra de inicio', color='primary')))\n",
        "#])\n",
        "\n",
        "    dbc.Alert(\n",
        "            [\n",
        "                html.H4(\"Dash Wallmart\"),\n",
        "                #html.A(\"examplo link\", href=\"#\", className=\"alert-heading\"),\n",
        "                html.Img(src='https://www.feltex.com.br/felix/wp-content/uploads/2014/03/Infnet-Logo.png',\n",
        "                         style={\n",
        "                'maxWidth': '10%',\n",
        "                'maxHeight': '10%',\n",
        "                'marginLeft': '900px',\n",
        "                'marginRight': 'auto',\n",
        "                'marginUp': '1%'},\n",
        "                )\n",
        "            ]\n",
        "           , color=\"primary\",\n",
        "     )])\n",
        "\n",
        "grid2 = html.Div([\n",
        "    dbc.Row([\n",
        "        dbc.Col(controls, md=2),\n",
        "        dbc.Col(grafico1, md=4),\n",
        "        dbc.Col(grafico2, md=6)\n",
        "     ], align='center')\n",
        "])\n",
        "\n",
        "app.layout = html.Div([\n",
        "    grid1, grid2\n",
        "    ])\n",
        "\n",
        "#callback Grafico 1\n",
        "@app.callback(\n",
        "    Output('grafico1', 'figure'),\n",
        "    [Input('x-variable', 'value'),\n",
        "     Input('y-variable', 'value')]\n",
        ")\n",
        "\n",
        "#Grafico 1\n",
        "def criando_grafico(x,y):\n",
        "    \n",
        "    filtro_df = select_store_1(x,y)\n",
        "    fig = px.line(filtro_df,  x='ds', y='yhat', title=f\"Serie week {y} of store {x}\", labels={'ds':'Date', 'yhat':'Sales'})\n",
        "    fig.update_layout({'paper_bgcolor':'rgb(28,28,28)'})\n",
        "    fig.update_layout(font=dict(\n",
        "        family=\"Courier New, monospace\",\n",
        "        size=14,\n",
        "        color=\"White\"))\n",
        "    return fig\n",
        "\n",
        "#callback Grafico 2\n",
        "@app.callback(\n",
        "    Output('grafico2', 'figure'),\n",
        "    [Input('x-variable', 'value'),\n",
        "     Input('y-variable', 'value')]\n",
        ")\n",
        "\n",
        "#grafico 2\n",
        "def criando_grafico(x,y):\n",
        "    \n",
        "    filtro_df = select_store_2(x,y)\n",
        "    fig = px.line(filtro_df,  x='ds', y='yhat', title=f\"series history of store {x} \", labels={'ds':'Date', 'yhat':'Sales'})\n",
        "    fig.update_layout({'paper_bgcolor':'rgb(28,28,28)'})\n",
        "    fig.update_layout(font=dict(\n",
        "        family=\"Courier New, monospace\",\n",
        "        size=14,\n",
        "        color=\"White\"))\n",
        "    return fig    \n",
        "\n",
        "if __name__ == '__main__':\n",
        "  app.run_server(mode='inline')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "(async (port, path, width, height, cache, element) => {\n",
              "    if (!google.colab.kernel.accessAllowed && !cache) {\n",
              "      return;\n",
              "    }\n",
              "    element.appendChild(document.createTextNode(''));\n",
              "    const url = await google.colab.kernel.proxyPort(port, {cache});\n",
              "    const iframe = document.createElement('iframe');\n",
              "    iframe.src = new URL(path, url).toString();\n",
              "    iframe.height = height;\n",
              "    iframe.width = width;\n",
              "    iframe.style.border = 0;\n",
              "    element.appendChild(iframe);\n",
              "  })(8050, \"/\", \"100%\", 650, false, window.element)"
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}