# How to plot the boundaries of the states on the basemap of the USA

We will plot the boundaries of the states of the USA on a basemap figure

We will see how we can plot the shape data on a map, in this case, we plot particularly the states of the United States on a basemap figure. We have seen examples of how to plot the shapefile data using geopandas. Here, we will do it using the low-level tool “shapefile”.

You can download the shapefile data for the USA states from the github repository of `joncutrer/geopandas-tutorial`: usa-states-census-2014.shp

``````git clone https://github.com/joncutrer/geopandas-tutorial.git
``````

``````import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import shapefile as shp
``````

## Define configuration for the plot

``````# configuration arguments for figure
fig_config = {'figsize': (8,4)}

## select some region of the USA
map_config = {
'projection': 'merc',   # type of map projection
'llcrnrlat': 28.,
'urcrnrlat': 50.,
'llcrnrlon': -130.,
'urcrnrlon': -95.,
'area_thresh': 10000,    #area threshold for coastlines
'resolution': 'h'}       # resolution of coastline data ('c'oarse fine for global)

save_ext = 'png'
save_kwargs = {'dpi': 150, 'bbox_inches':'tight'}
``````

## Plot map

``````
def plot_map():
"""Plot the map"""

# figure / map setup
fig = plt.figure(**fig_config)
m = Basemap(ax=ax, **map_config)
cp = m.drawmapboundary()

for idd in range(0,len(sf.records())):
shape_ex = sf.shape(idd)
x_lon = np.zeros((len(shape_ex.points),1))
y_lat = np.zeros((len(shape_ex.points),1))
for ip in range(len(shape_ex.points)):
x_lon[ip] = shape_ex.points[ip]
y_lat[ip] = shape_ex.points[ip]
# print(shape_ex)
xm_lon, ym_lat = m(x_lon, y_lat)
m.plot(xm_lon, ym_lat, zorder=6, color='k', lw=0.5)

m.drawcoastlines(zorder=6)

fname_out="usa_states.png"
print("output fname: ",fname_out)
plt.savefig(fname_out, **save_kwargs)
plt.close()
``````

## Complete script

``````#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import shapefile as shp

shp_path = 'geopandas-tutorial/data/usa-states-census-2014.shp'
print(len(sf.records()))

########################################################################
# config

# configuration arguments for figure
fig_config = {'figsize': (8,4)}

map_config = {
'projection': 'merc',   # type of map projection
'llcrnrlat': 28.,
'urcrnrlat': 50.,
'llcrnrlon': -130.,
'urcrnrlon': -95.,
'area_thresh': 10000,    #area threshold for coastlines
'resolution': 'h'}       # resolution of coastline data ('c'oarse fine for global)

save_ext = 'png'
save_kwargs = {'dpi': 150, 'bbox_inches':'tight'}

def plot_map():
"""Plot the map"""

# figure / map setup
fig = plt.figure(**fig_config)
m = Basemap(ax=ax, **map_config)
cp = m.drawmapboundary()

for idd in range(0,len(sf.records())):
shape_ex = sf.shape(idd)
x_lon = np.zeros((len(shape_ex.points),1))
y_lat = np.zeros((len(shape_ex.points),1))
for ip in range(len(shape_ex.points)):
x_lon[ip] = shape_ex.points[ip]
y_lat[ip] = shape_ex.points[ip]
# print(shape_ex)
xm_lon, ym_lat = m(x_lon, y_lat)
m.plot(xm_lon, ym_lat, zorder=6, color='k', lw=0.5)

m.drawcoastlines(zorder=6)

fname_out="usa_states.png"
print("output fname: ",fname_out)
plt.savefig(fname_out, **save_kwargs)
plt.close()

########################################################################

if __name__ == '__main__':
plot_map()

`````` Plot of arbitraily selected region of USA with the boundary plot of the states overlaid on it

## Conclusion

This script can be very handy in plotting some data that has some relation with the states in the USA. These data can be categorical such as the number of COVID cases or spatial such as the seismic tomographic maps.

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