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+web: python mapping.py

mapping.py

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+from dash import Dash, dcc, html, Input, Output
+import plotly.express as px
+import pandas as pd
+import geopandas as gpd
+
+gdf = pd.read_csv('https://raw.githubusercontent.com/LIRNEasia/d3-visualizations/master/resources/complete_data.csv')
+
+geo_json = gpd.read_file("https://raw.githubusercontent.com/LIRNEasia/d3-visualizations/master/resources/dsd_topology.json")
+
+
+geo_df = geo_json.merge(gdf, on="code_4").set_index('dsd_name_x')
+
+app = Dash(__name__)
+
+
+app.layout = html.Div([
+ html.H4('Choropleth map of Sri Lanka based on ASWSUM data'),
+ html.P("Poverty category:"),
+ dcc.RadioItems(
+ id='candidate',
+ options=["Severely Poor", "Poor", "Transient", "Vulnerable"],
+ value="Poor",
+ inline=True
+ ),
+ dcc.Graph(id="graph"),
+])
+
+
+@app.callback(
+ Output("graph", "figure"),
+ Input("candidate", "value"))
+def display_choropleth(candidate):
+
+ fig = px.choropleth(geo_df,
+ geojson=geo_df.geometry,
+ color= candidate,
+ locations=geo_df.index,
+ #featureidkey= geo_df.index,
+ projection="mercator",range_color=[0, 6500])
+ fig.update_geos(fitbounds="locations", visible=False)
+ fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
+ return fig
+
+
+
+app.run_server(host='0.0.0.0', port=8050)

requirements.txt

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+dash==2.12.0
+plotly==5.16.0