Map of the US

“If there’s a place you gotta go I’m the one you need to know. I’m the map.”

Do you know the fifty nifty United States from thirteen original colonies? If you don’t, that’s ok, because we have google!

Here is the tutorial I followed to create the US map in python.

https://jcutrer.com/python/learn-geopandas-plotting-usmaps

I’m going to go through ^ tutorial and add a couple things I couldn’t find in plain sight from the tutorial. First off, this site:

Cartographic Boundary Files

^This site has all the US area files (shapefiles/whatever that means).

1. As usual:

import pandas as pd
import geopandas
import math
import matplotlib.pyplot as plt

2. Make sure to download all the files in the states_2020 folder

I believe I used the 500,000 (national) shapefile. At first I made the mistake of only downloading the shp file. For some reason, the shp file won’t run unless all the other files in the states_2020 folder are downloaded. Make sure to extract the files from the zip file before loading into python (unless you know how to load in a zip file).

states = geopandas.read_file('states_2020/cb_2020_us_state_5m.shp')
states.head()

If you write states.shape you will notice the website provides you with 56 states/locations! states.shape should return (56, 10)

3. PolygonPatch

To install: pip install -i https://pypi.anaconda.org/mkhines/simple descartes

Descartes :: Anaconda.org

from descartes.patch import PolygonPatch

4. Make a mini plot

states.plot(); 

5. Get rid of excess states

I had to make a map for a project at work so my boss helped me with this line of code. Why did I not know ~ meant not? Oh well, I guess I’ll always be learning.

states_50 = states[~states['STUSPS'].isin(['GU', 'AS', 'AK', 'PR', 'VI', 'MP'])]
states_50.head()

Now when you do states_50.shape you will see (50,10)

states_50.plot();

6. Boundary plot

states_50.boundary.plot(figsize=(40,15))

7. Labeled US map

fig, ax = plt.subplots(figsize=(29,12))
states_50.apply(lambda x: ax.annotate(s=x.STUSPS, xy=x.geometry.centroid.coords[0], ha='center', fontsize=11, color = 'black'), axis=1);
states_50.boundary.plot(ax=ax, color='black', linewidth = .2)
states_50.plot(ax=ax, cmap = 'Blues')
plt.savefig('US_state_map')

The cool thing about cmap is all the color options! Personally, I didn’t think the flag option was that cool looking.

fig, ax = plt.subplots(figsize=(29,12))
states_50.apply(lambda x: ax.annotate(s=x.STUSPS, xy=x.geometry.centroid.coords[0], ha='center', fontsize=11, color = 'white'), axis=1);
states_50.boundary.plot(ax=ax, color='black', linewidth = .2)
states_50.plot(ax=ax, cmap = 'flag')

The following link has a list of cmap color options:

Choosing Colormaps in Matplotlib - Matplotlib 3.4.3 documentation

If you could travel to any state to get a bagel, which place in NJ would you go?