Harmonize returning nan for intensive variables
See original GitHub issueimport 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
</div>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 |
Issue Analytics
- State:
- Created 3 years ago
- Comments:21 (10 by maintainers)
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i think i see whats going on
no i just installed it from master