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import dash | |
import dash_core_components as dcc | |
import dash_html_components as html | |
import plotly.graph_objs as go | |
import pandas as pd | |
app = dash.Dash() | |
df = pd.read_csv( | |
'https://gist.githubusercontent.com/chriddyp/' | |
'cb5392c35661370d95f300086accea51/raw/' | |
'8e0768211f6b747c0db42a9ce9a0937dafcbd8b2/' | |
'indicators.csv') | |
available_indicators = df['Indicator Name'].unique() | |
app.layout = html.Div([ | |
html.Div([ | |
html.Div([ | |
dcc.Dropdown( | |
id='crossfilter-xaxis-column', | |
options=[{'label': i, 'value': i} for i in available_indicators], | |
value='Fertility rate, total (births per woman)' | |
), | |
dcc.RadioItems( | |
id='crossfilter-xaxis-type', | |
options=[{'label': i, 'value': i} for i in ['Linear', 'Log']], | |
value='Linear', | |
labelStyle={'display': 'inline-block'} | |
) | |
], | |
style={'width': '49%', 'display': 'inline-block'}), | |
html.Div([ | |
dcc.Dropdown( | |
id='crossfilter-yaxis-column', | |
options=[{'label': i, 'value': i} for i in available_indicators], | |
value='Life expectancy at birth, total (years)' | |
), | |
dcc.RadioItems( | |
id='crossfilter-yaxis-type', | |
options=[{'label': i, 'value': i} for i in ['Linear', 'Log']], | |
value='Linear', | |
labelStyle={'display': 'inline-block'} | |
) | |
], style={'width': '49%', 'float': 'right', 'display': 'inline-block'}) | |
], style={ | |
'borderBottom': 'thin lightgrey solid', | |
'backgroundColor': 'rgb(250, 250, 250)', | |
'padding': '10px 5px' | |
}), | |
html.Div([ | |
dcc.Graph( | |
id='crossfilter-indicator-scatter', | |
hoverData={'points': [{'customdata': 'Japan'}]} | |
) | |
], style={'width': '49%', 'display': 'inline-block', 'padding': '0 20'}), | |
html.Div([ | |
dcc.Graph(id='x-time-series'), | |
dcc.Graph(id='y-time-series'), | |
], style={'display': 'inline-block', 'width': '49%'}), | |
html.Div(dcc.Slider( | |
id='crossfilter-year--slider', | |
min=df['Year'].min(), | |
max=df['Year'].max(), | |
value=df['Year'].max(), | |
step=None, | |
marks={str(year): str(year) for year in df['Year'].unique()} | |
), style={'width': '49%', 'padding': '0px 20px 20px 20px'}) | |
]) | |
@app.callback( | |
dash.dependencies.Output('crossfilter-indicator-scatter', 'figure'), | |
[dash.dependencies.Input('crossfilter-xaxis-column', 'value'), | |
dash.dependencies.Input('crossfilter-yaxis-column', 'value'), | |
dash.dependencies.Input('crossfilter-xaxis-type', 'value'), | |
dash.dependencies.Input('crossfilter-yaxis-type', 'value'), | |
dash.dependencies.Input('crossfilter-year--slider', 'value')]) | |
def update_graph(xaxis_column_name, yaxis_column_name, | |
xaxis_type, yaxis_type, | |
year_value): | |
dff = df[df['Year'] == year_value] | |
return { | |
'data': [go.Scatter( | |
x=dff[dff['Indicator Name'] == xaxis_column_name]['Value'], | |
y=dff[dff['Indicator Name'] == yaxis_column_name]['Value'], | |
text=dff[dff['Indicator Name'] == yaxis_column_name]['Country Name'], | |
customdata=dff[dff['Indicator Name'] == yaxis_column_name]['Country Name'], | |
mode='markers', | |
marker={ | |
'size': 15, | |
'opacity': 0.5, | |
'line': {'width': 0.5, 'color': 'white'} | |
} | |
)], | |
'layout': go.Layout( | |
xaxis={ | |
'title': xaxis_column_name, | |
'type': 'linear' if xaxis_type == 'Linear' else 'log' | |
}, | |
yaxis={ | |
'title': yaxis_column_name, | |
'type': 'linear' if yaxis_type == 'Linear' else 'log' | |
}, | |
margin={'l': 40, 'b': 30, 't': 10, 'r': 0}, | |
height=450, | |
hovermode='closest' | |
) | |
} | |
def create_time_series(dff, axis_type, title): | |
return { | |
'data': [go.Scatter( | |
x=dff['Year'], | |
y=dff['Value'], | |
mode='lines+markers' | |
)], | |
'layout': { | |
'height': 225, | |
'margin': {'l': 20, 'b': 30, 'r': 10, 't': 10}, | |
'annotations': [{ | |
'x': 0, 'y': 0.85, 'xanchor': 'left', 'yanchor': 'bottom', | |
'xref': 'paper', 'yref': 'paper', 'showarrow': False, | |
'align': 'left', 'bgcolor': 'rgba(255, 255, 255, 0.5)', | |
'text': title | |
}], | |
'yaxis': {'type': 'linear' if axis_type == 'Linear' else 'log'}, | |
'xaxis': {'showgrid': False} | |
} | |
} | |
@app.callback( | |
dash.dependencies.Output('x-time-series', 'figure'), | |
[dash.dependencies.Input('crossfilter-indicator-scatter', 'hoverData'), | |
dash.dependencies.Input('crossfilter-xaxis-column', 'value'), | |
dash.dependencies.Input('crossfilter-xaxis-type', 'value')]) | |
def update_y_timeseries(hoverData, xaxis_column_name, axis_type): | |
country_name = hoverData['points'][0]['customdata'] | |
dff = df[df['Country Name'] == country_name] | |
dff = dff[dff['Indicator Name'] == xaxis_column_name] | |
title = '<b>{}</b><br>{}'.format(country_name, xaxis_column_name) | |
return create_time_series(dff, axis_type, title) | |
@app.callback( | |
dash.dependencies.Output('y-time-series', 'figure'), | |
[dash.dependencies.Input('crossfilter-indicator-scatter', 'hoverData'), | |
dash.dependencies.Input('crossfilter-yaxis-column', 'value'), | |
dash.dependencies.Input('crossfilter-yaxis-type', 'value')]) | |
def update_x_timeseries(hoverData, yaxis_column_name, axis_type): | |
dff = df[df['Country Name'] == hoverData['points'][0]['customdata']] | |
dff = dff[dff['Indicator Name'] == yaxis_column_name] | |
return create_time_series(dff, axis_type, yaxis_column_name) | |
app.css.append_css({ | |
'external_url': 'https://codepen.io/chriddyp/pen/bWLwgP.css' | |
}) | |
if __name__ == '__main__': | |
app.run_server() |
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