This example illustrates how to enrich polygons that are in a dataset with variables from CARTO's Data Observatory.
Note: You'll need CARTO Account credentials to reproduce this example.
from cartoframes.auth import set_default_credentials
set_default_credentials('creds.json')
from geopandas import read_file
census_track = 'http://libs.cartocdn.com/cartoframes/files/census_track.geojson'
census_track_gdf = read_file(census_track)
census_track_gdf.head(3)
OBJECTID | FULLTRACTID | TRACTID | geometry | |
---|---|---|---|---|
0 | 1 | 51013102901 | 102901 | POLYGON ((-77.09099 38.84516, -77.08957 38.844... |
1 | 2 | 51013103000 | 103000 | POLYGON ((-77.08558 38.82992, -77.08625 38.828... |
2 | 3 | 51013102902 | 102902 | POLYGON ((-77.09520 38.84499, -77.09442 38.844... |
from cartoframes.data.observatory import Catalog
Catalog().country('usa').category('demographics').geographies
You can find more entities with the Global country filter. To apply that filter run: Catalog().country('glo')
[<Geography.get('mbi_blockgroups_535aed6d')>, <Geography.get('mbi_counties_46ea8aaa')>, <Geography.get('mbi_county_subd_ba170144')>, <Geography.get('mbi_pc_5_digit_19e769c1')>, <Geography.get('cdb_blockgroup_7753dd51')>, <Geography.get('cdb_cbsa_d80f5110')>, <Geography.get('cdb_censustract_af861cba')>, <Geography.get('cdb_censustract_a6305091')>, <Geography.get('cdb_congression_4e34d9d6')>, <Geography.get('cdb_county_767e79f0')>, <Geography.get('cdb_county_8cf054d')>, <Geography.get('cdb_place_9a630135')>, <Geography.get('cdb_puma_cddf005')>, <Geography.get('cdb_schooldistr_e2feab97')>, <Geography.get('cdb_schooldistr_11e23214')>, <Geography.get('cdb_schooldistr_d07c560d')>, <Geography.get('cdb_state_cd83b434')>, <Geography.get('cdb_zcta5_f4043497')>]
datasets = Catalog().country('usa').category('demographics').geography('cdb_censustract_af861cba').datasets
datasets.to_dataframe()
You can find more entities with the Global country filter. To apply that filter run: Catalog().country('glo')
slug | name | description | category_id | country_id | data_source_id | provider_id | geography_name | geography_description | temporal_aggregation | time_coverage | update_frequency | is_public_data | lang | version | category_name | provider_name | geography_id | id | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | acs_sociodemogr_858c104e | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | Census Tract - United States of America (2015) | Shoreline clipped TIGER/Line boundaries. More ... | 5yrs | [2008-01-01, 2013-01-01) | None | True | eng | 20082012 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
1 | acs_sociodemogr_6bf5c7f4 | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | Census Tract - United States of America (2015) | Shoreline clipped TIGER/Line boundaries. More ... | 5yrs | None | None | True | eng | 20142018 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
2 | acs_sociodemogr_dda43439 | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | Census Tract - United States of America (2015) | Shoreline clipped TIGER/Line boundaries. More ... | 5yrs | [2011-01-01, 2016-01-01) | None | True | eng | 20112015 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
3 | acs_sociodemogr_97c32d1f | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | Census Tract - United States of America (2015) | Shoreline clipped TIGER/Line boundaries. More ... | 5yrs | [2010-01-01, 2015-01-01) | None | True | eng | 20102014 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
4 | acs_sociodemogr_d4b2cf03 | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | Census Tract - United States of America (2015) | Shoreline clipped TIGER/Line boundaries. More ... | 5yrs | [2006-01-01, 2011-01-01) | None | True | eng | 20062010 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
5 | acs_sociodemogr_496a0675 | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | Census Tract - United States of America (2015) | Shoreline clipped TIGER/Line boundaries. More ... | 5yrs | [2013-01-01, 2018-01-01) | None | True | eng | 20132017 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
6 | acs_sociodemogr_9ed5d625 | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | Census Tract - United States of America (2015) | Shoreline clipped TIGER/Line boundaries. More ... | 5yrs | [2007-01-01, 2012-01-01) | None | True | eng | 20072011 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
7 | acs_sociodemogr_cfeb0968 | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | Census Tract - United States of America (2015) | Shoreline clipped TIGER/Line boundaries. More ... | 5yrs | [2009-01-01, 2014-01-01) | None | True | eng | 20092013 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
8 | acs_sociodemogr_30d1f53 | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | Census Tract - United States of America (2015) | Shoreline clipped TIGER/Line boundaries. More ... | 5yrs | [2012-01-01, 2017-01-01) | None | True | eng | 20122016 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
from cartoframes.data.observatory import Dataset
dataset = Dataset.get('acs_sociodemogr_d4b2cf03')
variables_df = dataset.variables.to_dataframe()
variables_df[variables_df['description'].str.contains('car', case=False, na=False)]
slug | name | description | db_type | agg_method | column_name | variable_group_id | dataset_id | id | |
---|---|---|---|---|---|---|---|---|---|
79 | median_income_57be5af4 | Median Income | Median Household Income in the past 12 Months.... | FLOAT | AVG | median_income | None | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
165 | no_car_2207f034 | no_car | Workers age 16 and over with no vehicle. All p... | FLOAT | SUM | no_car | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
166 | no_cars_3a983c4e | no_cars | Car-free households. The number of households ... | FLOAT | SUM | no_cars | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
167 | one_car_13b3a60b | one_car | One car households. The number of households w... | FLOAT | SUM | one_car | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
168 | two_cars_fec37223 | two_cars | Two car households. The number of households w... | FLOAT | SUM | two_cars | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
169 | three_cars_32e541e7 | three_cars | Three car households. The number of households... | FLOAT | SUM | three_cars | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
170 | four_more_cars_297e8a8a | four_more_cars | Four car households. The number of households ... | FLOAT | SUM | four_more_cars | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
174 | commuters_by_ca_120481e3 | commuters_by_car_truck_van | Commuters by Car, Truck, or Van. The number of... | FLOAT | SUM | commuters_by_car_truck_van | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
175 | commuters_by_ca_59febe6f | commuters_by_carpool | Commuters by Carpool. The number of workers ag... | FLOAT | SUM | commuters_by_carpool | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
177 | commuters_drove_acf77a1 | commuters_drove_alone | Commuters who drove alone. The number of worke... | FLOAT | SUM | commuters_drove_alone | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
197 | employed_educat_958fdcfe | employed_education_health_social | Workers employed in firms in educational servi... | FLOAT | SUM | employed_education_health_social | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
201 | employed_other__a5acf594 | employed_other_services_not_public_admin | Workers employed in firms in other services ex... | FLOAT | SUM | employed_other_services_not_public_admin | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
205 | employed_transp_66aedbfd | employed_transportation_warehousing_utilities | Workers employed in firms in transportation, w... | FLOAT | SUM | employed_transportation_warehousing_utilities | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
from cartoframes.data.observatory import Variable
variable = Variable.get('no_car_2207f034')
variable.to_dict()
{'slug': 'no_car_2207f034', 'name': 'no_car', 'description': 'Workers age 16 and over with no vehicle. All people in a geographic area over the age of 16 who do not own a car.', 'db_type': 'FLOAT', 'agg_method': 'SUM', 'column_name': 'no_car', 'variable_group_id': 'carto-do-public-data.usa_acs.demographics_sociodemographics_usa_censustract_2015_5yrs_20062010.car_ownership', 'dataset_id': 'carto-do-public-data.usa_acs.demographics_sociodemographics_usa_censustract_2015_5yrs_20062010', 'id': 'carto-do-public-data.usa_acs.demographics_sociodemographics_usa_censustract_2015_5yrs_20062010.no_car'}
from cartoframes.data.observatory import Enrichment
enrichment = Enrichment()
enriched_dataset_gdf = enrichment.enrich_polygons(
census_track_gdf,
variables=[variable],
aggregation='SUM'
)
enriched_dataset_gdf.head(3)
OBJECTID | FULLTRACTID | TRACTID | geometry | no_car | |
---|---|---|---|---|---|
0 | 1 | 51013102901 | 102901 | POLYGON ((-77.09099 38.84516, -77.08957 38.844... | 0.657821 |
1 | 2 | 51013103000 | 103000 | POLYGON ((-77.08558 38.82992, -77.08625 38.828... | 87.516848 |
2 | 3 | 51013102902 | 102902 | POLYGON ((-77.09520 38.84499, -77.09442 38.844... | 123.512837 |
from cartoframes.viz import Layer, color_continuous_style
Layer(enriched_dataset_gdf, color_continuous_style('no_car'))