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#The demonstation of building a friendly red-green map according to the dataset.

#The code is shown below:

gdf = gpd.read_file(url);

gdf.crs = 'epsg:4326';

gplt.polyplot(gdf, figsize=(20, 4));

gplt.choropleth( gdf, hue="Median_PriceToRentRatio_AllHomes", edgecolor='white', linewidth=1, cmap="PiYG_r", legend=True, figsize=(50, 20))

Name		Name	Last commit message	Last commit date
Latest commit History 30 Commits
README.md		README.md
State_time_series.csv		State_time_series.csv
airport_Edges_GC.csv		airport_Edges_GC.csv
airport_Nodes_GC.csv		airport_Nodes_GC.csv
asymmetric_adjacency matrix_Edge Information_istm682.csv		asymmetric_adjacency matrix_Edge Information_istm682.csv
filtered_data.csv		filtered_data.csv
geneNetwork_rawPCNCI.csv		geneNetwork_rawPCNCI.csv
geoData.csv		geoData.csv
histology_subtype.csv		histology_subtype.csv
micro robot uci-secom pass_result _.csv		micro robot uci-secom pass_result _.csv
new_data_texas011.csv		new_data_texas011.csv
primaryschool_003.csv		primaryschool_003.csv
signal_mutation.csv		signal_mutation.csv
sources.txt		sources.txt
uci-secom.csv		uci-secom.csv
us_map.json		us_map.json

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