precincts

Areal interpolation: Tracts to Voting Precincts

This notebook demonstrates the interpolation of an intensive variable (Pct Youth) measured for the census tracts tracts in Riverside and San Bernardino counties in California to the voting precincts in the respective counties.

import tobler
import matplotlib.pyplot as plt
%matplotlib inline

import geopandas

tracts = geopandas.read_file("https://ndownloader.figshare.com/files/20460645")

tracts.shape

(822, 8)

There are 822 tracts in the two counties.

tracts.head()

	STATEFP	COUNTYFP	TRACTCE	GEOID	IE_NAME	IE_pct_you	pct Youth	geometry
0	06	071	004201	06071004201	Census Tract 42.01, San Bernardino County, Cal...	0.214690	0.21	POLYGON ((-117.34794 34.13602, -117.34725 34.1...
1	06	071	004202	06071004202	Census Tract 42.02, San Bernardino County, Cal...	0.204101	0.20	POLYGON ((-117.32259 34.11639, -117.32259 34.1...
2	06	071	004401	06071004401	Census Tract 44.01, San Bernardino County, Cal...	0.237707	0.24	POLYGON ((-117.35944 34.09045, -117.35944 34.0...
3	06	065	041912	06065041912	Census Tract 419.12, Riverside County, California	0.198622	0.20	POLYGON ((-117.65093 33.87887, -117.65086 33.8...
4	06	065	043822	06065043822	Census Tract 438.22, Riverside County, California	0.127917	0.13	POLYGON ((-117.21237 34.00421, -117.20705 34.0...

tracts.plot(facecolor='none', edgecolor='g')

<matplotlib.axes._subplots.AxesSubplot at 0x7fa40853ac88>

Precincts

precincts = geopandas.read_file("https://ndownloader.figshare.com/files/20460549")

precincts.shape

(3780, 11)

For the 3780 precincts in the two counties, we wish to obtain estimates of the percentage of the population that is youth.

precincts.plot(facecolor='none', edgecolor='r')

<matplotlib.axes._subplots.AxesSubplot at 0x7fa407b4c128>

Interpolation

estimates = tobler.area_weighted.area_interpolate(tracts, precincts, intensive_variables=['pct Youth'])

Source and target dataframes have different crs. Please correct.

Notice the warning about different crs.

estimates

As a result of the different crs, tobler will not carry out the interpolation. We need to fix the crs issue first by setting the tract geometries to use the precincts crs

tracts = tracts.to_crs(precincts.crs)

/home/serge/anaconda3/envs/tobler/lib/python3.7/site-packages/pyproj/crs.py:77: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method.
  return _prepare_from_string(" ".join(pjargs))

estimates = tobler.area_weighted.area_interpolate(tracts, precincts, intensive_variables=['pct Youth'])

nan values in variable: pct Youth, replacing with 0.0

estimates

(array([], dtype=float64), array([[0.42896819],
        [0.23996352],
        [0.70018814],
        ...,
        [0.18013979],
        [0.11000376],
        [0.22      ]]))

f, ax = plt.subplots(1, figsize=(8, 8))
ax = tracts.plot(column='pct Youth', ax=ax, legend=True, alpha=0.5, scheme='Quantiles', k=10)
plt.show()

precincts['pct Youth'] = estimates[-1]
f, ax = plt.subplots(1, figsize=(8, 8))
ax = precincts.plot(column='pct Youth', ax=ax, legend=True, alpha=0.5, scheme='Quantiles', k=10)
plt.show()