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‎hands_on_06/.ipynb_checkpoints/Untitled-checkpoint.ipynb

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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎hands_on_06/Untitled.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"from jupyter_dash import JupyterDash\n",
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"\n",
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"import dash \n",
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"import dash_core_components as dcc \n",
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"import dash_html_components as html \n",
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"from dash.dependencies import Input, Output\n",
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"\n",
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"import plotly.express as px"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Binder向け設定\n",
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"JupyterDash.infer_jupyter_proxy_config()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"gapminder= px.data.gapminder()\n",
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"\n",
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"app = JupyterDash()\n",
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"\n",
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"app.layout = html.Div(\n",
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"[\n",
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" html.H1(\"HEllo Jupyter Dash !\"),\n",
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" \n",
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" dcc.Dropdown(id=\"xaxis\", options=[{\"value\": i, \"label\": i} for i in gapminder.columns[3:6]], value=\"gdpPercap\"),\n",
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" dcc.Dropdown(id=\"yaxis\", options=[{\"value\": i, \"label\": i} for i in gapminder.columns[3:6]], value=\"pop\"),\n",
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" \n",
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" dcc.Graph(id=\"graph\")\n",
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"]\n",
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")\n",
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"\n",
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"@app.callback(Output(\"graph\", \"figure\"), [Input(\"xaxis\", \"value\"), Input(\"yaxis\", \"value\")])\n",
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"def update_graph(xaxis_value, yaxis_value):\n",
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" return px.scatter(gapminder, x=xaxis_value, y=yaxis_value, color=\"continent\", log_x=True, log_y=True)\n",
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"\n",
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"# 出力はjuptyerlab / inline / external\n",
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"app.run_server(mode=\"jupyterlab\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>country</th>\n",
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" <th>continent</th>\n",
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" <th>year</th>\n",
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" <th>lifeExp</th>\n",
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" <th>pop</th>\n",
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" <th>gdpPercap</th>\n",
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" <th>iso_alpha</th>\n",
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" <th>iso_num</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <td>0</td>\n",
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" <td>Afghanistan</td>\n",
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" <td>Asia</td>\n",
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" <td>1952</td>\n",
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" <td>28.801</td>\n",
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" <td>8425333</td>\n",
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" <td>779.445314</td>\n",
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" <td>AFG</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>1</td>\n",
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" <td>Afghanistan</td>\n",
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" <td>Asia</td>\n",
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" <td>1957</td>\n",
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" <td>30.332</td>\n",
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" <td>9240934</td>\n",
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" <td>820.853030</td>\n",
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" <td>AFG</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>2</td>\n",
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" <td>Afghanistan</td>\n",
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" <td>Asia</td>\n",
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" <td>1962</td>\n",
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" <td>31.997</td>\n",
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" <td>10267083</td>\n",
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" <td>853.100710</td>\n",
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" <td>AFG</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>3</td>\n",
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" <td>Afghanistan</td>\n",
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" <td>Asia</td>\n",
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" <td>1967</td>\n",
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" <td>34.020</td>\n",
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" <td>11537966</td>\n",
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" <td>836.197138</td>\n",
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" <td>AFG</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>4</td>\n",
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" <td>Afghanistan</td>\n",
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" <td>Asia</td>\n",
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" <td>1972</td>\n",
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" <td>36.088</td>\n",
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" <td>13079460</td>\n",
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" <td>739.981106</td>\n",
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" <td>AFG</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>1699</td>\n",
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" <td>Zimbabwe</td>\n",
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" <td>Africa</td>\n",
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" <td>1987</td>\n",
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" <td>62.351</td>\n",
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" <td>9216418</td>\n",
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" <td>706.157306</td>\n",
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" <td>ZWE</td>\n",
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" <td>716</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>1700</td>\n",
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" <td>Zimbabwe</td>\n",
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" <td>Africa</td>\n",
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" <td>1992</td>\n",
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" <td>60.377</td>\n",
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" <td>10704340</td>\n",
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" <td>693.420786</td>\n",
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" <td>ZWE</td>\n",
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" <td>716</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>1701</td>\n",
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" <td>Zimbabwe</td>\n",
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" <td>Africa</td>\n",
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" <td>1997</td>\n",
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" <td>46.809</td>\n",
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" <td>11404948</td>\n",
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" <td>792.449960</td>\n",
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" <td>ZWE</td>\n",
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" <td>716</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>1702</td>\n",
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" <td>Zimbabwe</td>\n",
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" <td>Africa</td>\n",
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" <td>2002</td>\n",
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" <td>39.989</td>\n",
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" <td>11926563</td>\n",
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" <td>672.038623</td>\n",
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" <td>ZWE</td>\n",
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" <td>716</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>1703</td>\n",
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" <td>Zimbabwe</td>\n",
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" <td>Africa</td>\n",
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" <td>2007</td>\n",
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" <td>43.487</td>\n",
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" <td>12311143</td>\n",
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" <td>469.709298</td>\n",
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" <td>ZWE</td>\n",
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" <td>716</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>1704 rows × 8 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" country continent year lifeExp pop gdpPercap iso_alpha \\\n",
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"0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG \n",
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"1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG \n",
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"2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG \n",
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"3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG \n",
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"4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG \n",
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"... ... ... ... ... ... ... ... \n",
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"1699 Zimbabwe Africa 1987 62.351 9216418 706.157306 ZWE \n",
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"1700 Zimbabwe Africa 1992 60.377 10704340 693.420786 ZWE \n",
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"1701 Zimbabwe Africa 1997 46.809 11404948 792.449960 ZWE \n",
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"1702 Zimbabwe Africa 2002 39.989 11926563 672.038623 ZWE \n",
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"1703 Zimbabwe Africa 2007 43.487 12311143 469.709298 ZWE \n",
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"\n",
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" iso_num \n",
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"0 4 \n",
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"1 4 \n",
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"2 4 \n",
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"3 4 \n",
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"4 4 \n",
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"... ... \n",
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"1699 716 \n",
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"1700 716 \n",
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"1701 716 \n",
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"1702 716 \n",
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"1703 716 \n",
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"\n",
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"[1704 rows x 8 columns]"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"gapminder"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎hands_on_06/pmc_allsmaller.py

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import dash
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import dash_core_components as dcc
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import dash_html_components as html
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from dash.dependencies import Input, Output, State, MATCH, ALL, ALLSMALLER
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import pandas as pd
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df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminder2007.csv')
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app = dash.Dash(__name__, suppress_callback_exceptions=True)
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app.layout = html.Div([
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html.Button('Add Filter', id='add-filter-ex3', n_clicks=0),
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html.Div(id='container-ex3', children=[]),
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])
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@app.callback(
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Output('container-ex3', 'children'),
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[Input('add-filter-ex3', 'n_clicks')],
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[State('container-ex3', 'children')])
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def display_dropdowns(n_clicks, existing_children):
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existing_children.append(html.Div([
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dcc.Dropdown(
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id={
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'type': 'filter-dropdown-ex3',
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'index': f"test_{n_clicks}"
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},
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options=[{'label': i, 'value': i} for i in df['country'].unique()],
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value=df['country'].unique()[n_clicks]
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),
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html.Div(id={
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'type': 'output-ex3',
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'index': f"test_{n_clicks}"
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})
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]))
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return existing_children
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@app.callback(
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Output({'type': 'output-ex3', 'index': MATCH}, 'children'),
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[Input({'type': 'filter-dropdown-ex3', 'index': MATCH}, 'value'),
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Input({'type': 'filter-dropdown-ex3', 'index': ALLSMALLER}, 'value')],
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)
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def display_output(matching_value, previous_values):
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previous_values_in_reversed_order = previous_values[::-1]
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all_values = [matching_value] + previous_values_in_reversed_order
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dff = df[df['country'].str.contains('|'.join(all_values))]
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avgLifeExp = dff['lifeExp'].mean()
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# Return a slightly different string depending on number of values
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if len(all_values) == 1:
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return html.Div('{:.2f} is the life expectancy of {}'.format(
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avgLifeExp, matching_value
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))
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elif len(all_values) == 2:
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return html.Div('{:.2f} is the average life expectancy of {}'.format(
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avgLifeExp, ' and '.join(all_values)
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))
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else:
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return html.Div('{:.2f} is the average life expectancy of {}, and {}'.format(
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avgLifeExp, ', '.join(all_values[:-1]), all_values[-1]
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))
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if __name__ == '__main__':
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app.run_server(debug=True)

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