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@aapoorv-tf
aapoorv-tf committed Nov 14, 2021
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208 changes: 208 additions & 0 deletions Rainfall - Deforestation/test.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Dash is running on http://127.0.0.1:8050/\n",
"\n",
"Dash is running on http://127.0.0.1:8050/\n",
"\n",
"Dash is running on http://127.0.0.1:8050/\n",
"\n",
"Dash is running on http://127.0.0.1:8050/\n",
"\n",
" * Serving Flask app \"__main__\" (lazy loading)\n",
" * Environment: production\n",
" WARNING: This is a development server. Do not use it in a production deployment.\n",
" Use a production WSGI server instead.\n",
" * Debug mode: off\n"
]
}
],
"source": [
"import dash\n",
"import dash_core_components as dcc\n",
"import dash_html_components as html\n",
"import pandas as pd\n",
"import plotly.express as px\n",
"\n",
"external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']\n",
"\n",
"app = dash.Dash(__name__, external_stylesheets=external_stylesheets)\n",
"\n",
"df = pd.read_csv('https://plotly.github.io/datasets/country_indicators.csv')\n",
"\n",
"available_indicators = df['Indicator Name'].unique()\n",
"\n",
"app.layout = html.Div([\n",
" html.Div([\n",
"\n",
" html.Div([\n",
" dcc.Dropdown(\n",
" id='crossfilter-xaxis-column',\n",
" options=[{'label': i, 'value': i} for i in available_indicators],\n",
" value='Fertility rate, total (births per woman)'\n",
" ),\n",
" dcc.RadioItems(\n",
" id='crossfilter-xaxis-type',\n",
" options=[{'label': i, 'value': i} for i in ['Linear', 'Log']],\n",
" value='Linear',\n",
" labelStyle={'display': 'inline-block', 'marginTop': '5px'}\n",
" )\n",
" ],\n",
" style={'width': '49%', 'display': 'inline-block'}),\n",
"\n",
" html.Div([\n",
" dcc.Dropdown(\n",
" id='crossfilter-yaxis-column',\n",
" options=[{'label': i, 'value': i} for i in available_indicators],\n",
" value='Life expectancy at birth, total (years)'\n",
" ),\n",
" dcc.RadioItems(\n",
" id='crossfilter-yaxis-type',\n",
" options=[{'label': i, 'value': i} for i in ['Linear', 'Log']],\n",
" value='Linear',\n",
" labelStyle={'display': 'inline-block', 'marginTop': '5px'}\n",
" )\n",
" ], style={'width': '49%', 'float': 'right', 'display': 'inline-block'})\n",
" ], style={\n",
" 'padding': '10px 5px'\n",
" }),\n",
"\n",
" html.Div([\n",
" dcc.Graph(\n",
" id='crossfilter-indicator-scatter',\n",
" hoverData={'points': [{'customdata': 'Japan'}]}\n",
" )\n",
" ], style={'width': '49%', 'display': 'inline-block', 'padding': '0 20'}),\n",
" html.Div([\n",
" dcc.Graph(id='x-time-series'),\n",
" dcc.Graph(id='y-time-series'),\n",
" ], style={'display': 'inline-block', 'width': '49%'}),\n",
"\n",
" html.Div(dcc.Slider(\n",
" id='crossfilter-year--slider',\n",
" min=df['Year'].min(),\n",
" max=df['Year'].max(),\n",
" value=df['Year'].max(),\n",
" marks={str(year): str(year) for year in df['Year'].unique()},\n",
" step=None\n",
" ), style={'width': '49%', 'padding': '0px 20px 20px 20px'})\n",
"])\n",
"\n",
"\n",
"@app.callback(\n",
" dash.dependencies.Output('crossfilter-indicator-scatter', 'figure'),\n",
" [dash.dependencies.Input('crossfilter-xaxis-column', 'value'),\n",
" dash.dependencies.Input('crossfilter-yaxis-column', 'value'),\n",
" dash.dependencies.Input('crossfilter-xaxis-type', 'value'),\n",
" dash.dependencies.Input('crossfilter-yaxis-type', 'value'),\n",
" dash.dependencies.Input('crossfilter-year--slider', 'value')])\n",
"def update_graph(xaxis_column_name, yaxis_column_name,\n",
" xaxis_type, yaxis_type,\n",
" year_value):\n",
" dff = df[df['Year'] == year_value]\n",
"\n",
" fig = px.scatter(x=dff[dff['Indicator Name'] == xaxis_column_name]['Value'],\n",
" y=dff[dff['Indicator Name'] == yaxis_column_name]['Value'],\n",
" hover_name=dff[dff['Indicator Name'] == yaxis_column_name]['Country Name']\n",
" )\n",
"\n",
" fig.update_traces(customdata=dff[dff['Indicator Name'] == yaxis_column_name]['Country Name'])\n",
"\n",
" fig.update_xaxes(title=xaxis_column_name, type='linear' if xaxis_type == 'Linear' else 'log')\n",
"\n",
" fig.update_yaxes(title=yaxis_column_name, type='linear' if yaxis_type == 'Linear' else 'log')\n",
"\n",
" fig.update_layout(margin={'l': 40, 'b': 40, 't': 10, 'r': 0}, hovermode='closest')\n",
"\n",
" return fig\n",
"\n",
"\n",
"def create_time_series(dff, axis_type, title):\n",
"\n",
" fig = px.scatter(dff, x='Year', y='Value')\n",
"\n",
" fig.update_traces(mode='lines+markers')\n",
"\n",
" fig.update_xaxes(showgrid=False)\n",
"\n",
" fig.update_yaxes(type='linear' if axis_type == 'Linear' else 'log')\n",
"\n",
" fig.add_annotation(x=0, y=0.85, xanchor='left', yanchor='bottom',\n",
" xref='paper', yref='paper', showarrow=False, align='left',\n",
" text=title)\n",
"\n",
" fig.update_layout(height=225, margin={'l': 20, 'b': 30, 'r': 10, 't': 10})\n",
"\n",
" return fig\n",
"\n",
"\n",
"@app.callback(\n",
" dash.dependencies.Output('x-time-series', 'figure'),\n",
" [dash.dependencies.Input('crossfilter-indicator-scatter', 'hoverData'),\n",
" dash.dependencies.Input('crossfilter-xaxis-column', 'value'),\n",
" dash.dependencies.Input('crossfilter-xaxis-type', 'value')])\n",
"def update_y_timeseries(hoverData, xaxis_column_name, axis_type):\n",
" country_name = hoverData['points'][0]['customdata']\n",
" dff = df[df['Country Name'] == country_name]\n",
" dff = dff[dff['Indicator Name'] == xaxis_column_name]\n",
" title = '<b>{}</b><br>{}'.format(country_name, xaxis_column_name)\n",
" return create_time_series(dff, axis_type, title)\n",
"\n",
"\n",
"@app.callback(\n",
" dash.dependencies.Output('y-time-series', 'figure'),\n",
" [dash.dependencies.Input('crossfilter-indicator-scatter', 'hoverData'),\n",
" dash.dependencies.Input('crossfilter-yaxis-column', 'value'),\n",
" dash.dependencies.Input('crossfilter-yaxis-type', 'value')])\n",
"def update_x_timeseries(hoverData, yaxis_column_name, axis_type):\n",
" dff = df[df['Country Name'] == hoverData['points'][0]['customdata']]\n",
" dff = dff[dff['Indicator Name'] == yaxis_column_name]\n",
" return create_time_series(dff, axis_type, yaxis_column_name)\n",
"\n",
"\n",
"if __name__ == '__main__':\n",
" app.run_server(debug=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"interpreter": {
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"kernelspec": {
"display_name": "Python 3.7.9 64-bit ('base': conda)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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"orig_nbformat": 4
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"nbformat": 4,
"nbformat_minor": 2
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