Choropleth geopandas

geopandas-choropleth.py

import pandas as pd
import geopandas as gpd
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

# read data
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')
df.rename(columns={'code':'STUSPS'}, inplace=True)

# read US state shapefile
state_map = gpd.read_file('data/cb_2018_us_state_500k/cb_2018_us_state_500k.shp')
state_map = state_map[~state_map.STATEFP.isin(['02','15','72','60','66','69','78','11'])]
# fixing projection
state_map = state_map.to_crs('EPSG:2163')

# merging datasets
df_state_map = pd.merge(df,state_map,on='STUSPS')
df_state_map = gpd.GeoDataFrame(df_state_map)

fig, ax = plt.subplots(1, figsize=(10, 6),dpi=300,facecolor='w',edgecolor='w')
# colorbar
divider = make_axes_locatable(ax)
cax = divider.append_axes('right', size='5%', pad=0.1)
#plot
gax = df_state_map.plot(ax=ax,cax=cax, column='total exports', cmap='Oranges', legend=True, edgecolor='black', linewidth=0.5,legend_kwds={'shrink':0.6})
ax.set_axis_off()
# label the colorbar
cax.tick_params(labelsize=10)
cax.set_ylabel('Total Exports',fontsize=10)
cax.yaxis.set_label_position('left')
plt.show()