In [1]:
from cartoframes.data.observatory import Catalog, Dataset
Catalog().country('usa').categories
Out[1]:
[<Category.get('covid19')>,
<Category.get('demographics')>,
<Category.get('environmental')>,
<Category.get('financial')>,
<Category.get('geosocial')>,
<Category.get('housing')>,
<Category.get('human_mobility')>,
<Category.get('points_of_interest')>,
<Category.get('road_traffic')>]
In [2]:
Catalog().country('usa').category('demographics').providers
Out[2]:
[<Provider.get('usa_bls')>,
<Provider.get('usa_acs')>,
<Provider.get('ags')>,
<Provider.get('experian')>,
<Provider.get('mbi')>]
In [3]:
datasets_acs_df = Catalog().country('usa').category('demographics').provider('usa_acs').datasets.to_dataframe()
In [4]:
datasets_acs_df.head()
Out[4]:
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_ecbce31e
Sociodemographics - United States of America (...
The American Community Survey (ACS) is an ongo...
demographics
usa
sociodemographics
usa_acs
County - United States of America
Shoreline clipped TIGER/Line boundaries. More ...
3yrs
[2007-01-01, 2010-01-01)
yearly
True
eng
20072009
Demographics
American Community Survey
carto-do-public-data.carto.geography_usa_count...
carto-do-public-data.usa_acs.demographics_soci...
1
acs_sociodemogr_516e1d44
Sociodemographics - United States of America (...
The American Community Survey (ACS) is an ongo...
demographics
usa
sociodemographics
usa_acs
County - United States of America
Shoreline clipped TIGER/Line boundaries. More ...
3yrs
[2011-01-01, 2014-01-01)
yearly
True
eng
20112013
Demographics
American Community Survey
carto-do-public-data.carto.geography_usa_count...
carto-do-public-data.usa_acs.demographics_soci...
2
acs_sociodemogr_477ca600
Sociodemographics - United States of America (...
The American Community Survey (ACS) is an ongo...
demographics
usa
sociodemographics
usa_acs
County - United States of America
Shoreline clipped TIGER/Line boundaries. More ...
yearly
[2009-01-01, 2010-01-01)
yearly
True
eng
2009
Demographics
American Community Survey
carto-do-public-data.carto.geography_usa_count...
carto-do-public-data.usa_acs.demographics_soci...
3
acs_sociodemogr_5f00d4dc
Sociodemographics - United States of America (...
The American Community Survey (ACS) is an ongo...
demographics
usa
sociodemographics
usa_acs
Core-based Statistical Area - United States of...
Shoreline clipped TIGER/Line boundaries. More ...
5yrs
[2007-01-01, 2012-01-01)
yearly
True
eng
20072011
Demographics
American Community Survey
carto-do-public-data.carto.geography_usa_cbsa_...
carto-do-public-data.usa_acs.demographics_soci...
4
acs_sociodemogr_18e867ac
Sociodemographics - United States of America (...
The American Community Survey (ACS) is an ongo...
demographics
usa
sociodemographics
usa_acs
County - United States of America
Shoreline clipped TIGER/Line boundaries. More ...
5yrs
[2011-01-01, 2016-01-01)
yearly
True
eng
20112015
Demographics
American Community Survey
carto-do-public-data.carto.geography_usa_count...
carto-do-public-data.usa_acs.demographics_soci...
In [5]:
datasets_acs_df[datasets_acs_df['geography_name'].str.contains('Block Groups')]
Out[5]:
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
In [6]:
dataset = Dataset.get('acs_sociodemogr_b758e778')
In [7]:
dataset.geom_coverage()
Out[7]:
:
StackTrace
">
In [8]:
dataset.describe()
Out[8]:
total_pop
households
male_pop
female_pop
median_age
male_under_5
male_5_to_9
male_10_to_14
male_15_to_17
male_18_to_19
...
high_school_diploma
less_one_year_college
masters_degree
one_year_more_college
employed_pop
unemployed_pop
pop_in_labor_force
not_in_labor_force
armed_forces
civilian_labor_force
avg
1.472650e+03
5.448504e+02
7.246883e+02
7.479616e+02
4.011421e+01
4.647734e+01
4.779547e+01
4.855696e+01
2.957191e+01
2.027658e+01
...
2.318925e+02
6.118515e+01
8.292164e+01
1.441038e+02
6.882278e+02
4.893004e+01
7.418160e+02
4.320162e+02
4.658140e+00
7.371579e+02
max
5.187200e+04
2.142900e+04
2.865800e+04
2.597700e+04
8.890000e+01
3.174000e+03
2.605000e+03
2.436000e+03
1.996000e+03
3.901000e+03
...
8.215000e+03
4.037000e+03
7.209000e+03
5.621000e+03
2.334000e+04
1.454000e+03
2.684700e+04
3.414200e+04
2.121400e+04
2.435400e+04
min
0.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
3.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
...
0.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
0.000000e+00
sum
3.244734e+08
1.200485e+08
1.596728e+08
1.648006e+08
8.791270e+06
1.024049e+07
1.053092e+07
1.069870e+07
6.515667e+06
4.467600e+06
...
5.109357e+07
1.348111e+07
1.827037e+07
3.175082e+07
1.516393e+08
1.078090e+07
1.634465e+08
9.518743e+07
1.026342e+06
1.624202e+08
range
5.187200e+04
2.142900e+04
2.865800e+04
2.597700e+04
8.590000e+01
3.174000e+03
2.605000e+03
2.436000e+03
1.996000e+03
3.901000e+03
...
8.215000e+03
4.037000e+03
7.209000e+03
5.621000e+03
2.334000e+04
1.454000e+03
2.684700e+04
3.414200e+04
2.121400e+04
2.435400e+04
stdev
9.592347e+02
3.286104e+02
4.934121e+02
4.920331e+02
9.405442e+00
5.415445e+01
5.402244e+01
5.378748e+01
3.532671e+01
5.444954e+01
...
1.627570e+02
5.603385e+01
1.046972e+02
1.159727e+02
4.794299e+02
5.098029e+01
5.128584e+02
3.242465e+02
8.417357e+01
5.031953e+02
q1
8.160000e+02
3.150000e+02
3.930000e+02
4.120000e+02
3.220000e+01
8.000000e+00
9.000000e+00
1.000000e+01
0.000000e+00
0.000000e+00
...
1.030000e+02
1.900000e+01
1.300000e+01
6.100000e+01
3.530000e+02
1.100000e+01
3.910000e+02
2.230000e+02
0.000000e+00
3.880000e+02
q3
1.441000e+03
5.390000e+02
7.090000e+02
7.340000e+02
4.200000e+01
4.200000e+01
4.500000e+01
4.500000e+01
2.700000e+01
1.400000e+01
...
2.370000e+02
6.000000e+01
6.900000e+01
1.410000e+02
6.770000e+02
4.600000e+01
7.250000e+02
4.200000e+02
0.000000e+00
7.240000e+02
median
1.107000e+03
4.180000e+02
5.370000e+02
5.610000e+02
3.700000e+01
2.300000e+01
2.500000e+01
2.600000e+01
1.400000e+01
4.000000e+00
...
1.680000e+02
3.800000e+01
3.500000e+01
9.800000e+01
5.050000e+02
2.700000e+01
5.470000e+02
3.170000e+02
0.000000e+00
5.430000e+02
interquartile_range
6.250000e+02
2.240000e+02
3.160000e+02
3.220000e+02
9.800000e+00
3.400000e+01
3.600000e+01
3.500000e+01
2.700000e+01
1.400000e+01
...
1.340000e+02
4.100000e+01
5.600000e+01
8.000000e+01
3.240000e+02
3.500000e+01
3.340000e+02
1.970000e+02
0.000000e+00
3.360000e+02
10 rows × 151 columns
Content source: CartoDB/cartoframes
Similar notebooks: