geosnap: Harmonize returning nan for intensive variables

import geosnap

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geosnap.__version__

'0.3.2'

sd = geosnap.Community.from_census(county_fips='06073')

/home/serge/anaconda3/envs/geosnapdev/lib/python3.7/site-packages/pyproj/crs/crs.py:53: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6
  return _prepare_from_string(" ".join(pjargs))

sd.gdf.head()

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	geoid	n_mexican_pop	n_cuban_pop	n_puerto_rican_pop	n_total_housing_units	n_vacant_housing_units	n_occupied_housing_units	n_owner_occupied_housing_units	n_renter_occupied_housing_units	n_white_persons	...	p_irish_born_pop	p_italian_born_pop	p_poverty_rate_children	p_poverty_rate_hispanic	p_russian_born_pop	p_scandanavian_born_pop	p_scandanavian_pop	n_total_pop_sample	p_female_labor_force	p_black_persons
5188	06073019000	5094.0	2.0	5.0	2326.0	184.0	2142.0	1769.0	373.0	4898911.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
5189	06073018700	30479.0	72.0	611.0	4819.0	50.0	4769.0	250.0	4519.0	215361577.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
5205	06073019101	2497.0	0.0	9.0	1497.0	154.0	1343.0	858.0	485.0	16221375.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
5206	06073020901	4839.0	7.0	5.0	3042.0	995.0	2047.0	1430.0	617.0	4416241.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
5207	06073021000	2337.0	0.0	15.0	2457.0	1154.0	1303.0	979.0	324.0	2302215.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

5 rows × 195 columns

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extensive = ['n_total_pop', 'n_total_housing_units', 'n_vacant_housing_units']
intensive = ['median_household_income', 'p_poverty_rate']

sd.gdf['median_household_income'] = sd.gdf['median_household_income'].fillna(0)

sd.gdf['median_household_income'].isnull().sum()

0

sd.gdf['p_poverty_rate'] = sd.gdf['p_poverty_rate'].fillna(0)

sd.gdf['p_poverty_rate'].isnull().sum()

0

sd_2010 = sd.harmonize(2010,extensive_variables=extensive,
                      intensive_variables=intensive)

/home/serge/anaconda3/envs/geosnapdev/lib/python3.7/site-packages/tobler/area_weighted/area_weighted.py:249: UserWarning: Geometry is in a geographic CRS. Results from 'area' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  den = source_df["geometry"].area.values
/home/serge/anaconda3/envs/geosnapdev/lib/python3.7/site-packages/tobler/area_weighted/area_weighted.py:249: UserWarning: Geometry is in a geographic CRS. Results from 'area' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  den = source_df["geometry"].area.values
/home/serge/anaconda3/envs/geosnapdev/lib/python3.7/site-packages/tobler/area_weighted/area_weighted.py:249: UserWarning: Geometry is in a geographic CRS. Results from 'area' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  den = source_df["geometry"].area.values

sd_2010.gdf.head()

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	geoid	geometry	median_household_income	n_total_housing_units	n_total_pop	n_vacant_housing_units	p_poverty_rate	year
0	06073014901	POLYGON ((-117.01957 32.76373, -117.01562 32.7...	NaN	1876.000000	4156.000000	131.00000	NaN	2010
1	06073000300	POLYGON ((-117.16864 32.74897, -117.16602 32.7...	NaN	3046.000000	4629.000000	397.00000	NaN	2010
2	06073000800	POLYGON ((-117.14632 32.74842, -117.14250 32.7...	NaN	2702.000000	3964.000000	253.00000	NaN	2010
3	06073002201	POLYGON ((-117.11577 32.75522, -117.11362 32.7...	NaN	1321.000000	3989.000000	76.00000	NaN	2010
4	06073018509	POLYGON ((-117.37213 33.20012, -117.36902 33.2...	NaN	1700.999899	5325.999683	171.99999	NaN	2010

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