This notebook shows how to use CARTOframes to discover and explore datasets from CARTO's Data Observatory.
If you haven't installed CARTOframes yet, please visit our installation guide.
The notebook is organized in the following sections:
Want to learn more? Learn how to access and download datasets on the following notebooks Access Public Data and Access Premium Data.
import geopandas as gpd
import pandas as pd
pd.set_option('display.max_columns', None)
from cartoframes.auth import set_default_credentials
from cartoframes.data.observatory import *
In order to be able to use the Data Observatory via CARTOframes, you need to set your CARTO account credentials first.
Please, visit the Authentication guide for further detail.
set_default_credentials('creds.json')
Note about credentials
For security reasons, we recommend storing your credentials in an external file to prevent publishing them by accident when sharing your notebooks. You can get more information in the section Setting your credentials of the Authentication guide.
CARTO's data catalog consists of a set of datasets organized by:
In addition, datasets are classified in public and premium data.
This classification can be used to explore the Catalog and narrow down your search for the dataset most suitable for your analysis.
For example, you may start exploring by country, then filter by category and finally select a dataset based on the provider. Alternatively, you could start exploring by category or provider.
In this subsection we explore each of the four classification categories.
Note results can be displayed in Python list format or in Pandas DataFrame format.
Catalog().countries.to_dataframe().head(10)
id | name | |
---|---|---|
0 | abw | Aruba |
1 | afg | Afghanistan |
2 | ago | Angola |
3 | aia | Anguilla |
4 | alb | Albania |
5 | and | Andorra |
6 | are | United Arab Emirates |
7 | arg | Argentina |
8 | arm | Armenia |
9 | asm | American Samoa |
Catalog().categories.to_dataframe()
id | name | |
---|---|---|
0 | behavioral | Behavioral |
1 | covid19 | Covid-19 |
2 | demographics | Demographics |
3 | derived | Derived |
4 | environmental | Environmental |
5 | financial | Financial |
6 | housing | Housing |
7 | human_mobility | Human Mobility |
8 | points_of_interest | Points of Interest |
9 | road_traffic | Road Traffic |
Catalog().providers.to_dataframe().head(10)
id | name | |
---|---|---|
0 | lifesight | Lifesight |
1 | tomtom | TomTom |
2 | home_junction | Home Junction |
3 | mastercard | Mastercard |
4 | usa_bls | Bureau of Labor Statistics |
5 | dstillery | Dstillery |
6 | usa_acs | American Community Survey |
7 | safegraph | SafeGraph |
8 | vodafone | Vodafone |
9 | can_statistics | Statistics Canada |
Catalog().geographies.to_dataframe().head()
slug | name | description | country_id | provider_id | geom_type | geom_coverage | update_frequency | is_public_data | lang | version | provider_name | id | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | ne_ports_e4ee35c9 | Ports - Global | Derives from High Seas, a detailed GIS compila... | glo | natural_earth | POINT | None | None | True | eng | 410 | Natural Earth | carto-do-public-data.natural_earth.geography_g... |
1 | ne_parksandpro_dc9d5ce5 | Parks And Protected Lands Area - United States... | Data includes the 398 authorized National Park... | usa | natural_earth | MULTIPOLYGON | None | None | True | eng | 410 | Natural Earth | carto-do-public-data.natural_earth.geography_u... |
2 | mbi_small_areas_f4ab4f8e | Small Areas - South Africa | MBI Digital Boundaries for South Africa at Sma... | zaf | mbi | MULTIPOLYGON | None | yearly | False | eng | 2020 | Michael Bauer International | carto-do.mbi.geography_zaf_smallareas_2020 |
3 | mbi_parishes_309be8bc | Parishes - Jamaica | MBI Digital Boundaries for Jamaica at Parishes... | jam | mbi | MULTIPOLYGON | None | yearly | False | eng | 2020 | Michael Bauer International | carto-do.mbi.geography_jam_parishes_2020 |
4 | tigr_county_c781b68e | County - United States of America (2017) | County TIGER/Line Shapefiles from the United S... | usa | usa_tiger | MULTIPOLYGON | None | None | True | eng | 2017 | Tiger/Line geographic data from the U.S. Censu... | carto-do-public-data.usa_tiger.geography_usa_c... |
Let's now take a look at how to combine category and provider filters to get the public demographics datasets available in the US from ACS at the census tract level.
Categories available in the US.
Catalog().country('usa').categories.to_dataframe()
You can find more entities with the Global country filter. To apply that filter run: Catalog().country('glo')
id | name | |
---|---|---|
0 | behavioral | Behavioral |
1 | covid19 | Covid-19 |
2 | demographics | Demographics |
3 | derived | Derived |
4 | environmental | Environmental |
5 | financial | Financial |
6 | housing | Housing |
7 | human_mobility | Human Mobility |
8 | points_of_interest | Points of Interest |
9 | road_traffic | Road Traffic |
Providers available in the US.
Catalog().country('usa').providers.to_dataframe().head()
You can find more entities with the Global country filter. To apply that filter run: Catalog().country('glo')
id | name | |
---|---|---|
0 | lifesight | Lifesight |
1 | tomtom | TomTom |
2 | home_junction | Home Junction |
3 | mastercard | Mastercard |
4 | usa_bls | Bureau of Labor Statistics |
List of providers available in the US offering demographics data.
Catalog().country('usa').category('demographics').providers
You can find more entities with the Global country filter. To apply that filter run: Catalog().country('glo')
[<Provider.get('usa_bls')>, <Provider.get('usa_acs')>, <Provider.get('ags')>, <Provider.get('experian')>, <Provider.get('gbr_cdrc')>, <Provider.get('worldpop')>, <Provider.get('mbi')>]
List of providers available in the US offering public demographics data.
Catalog().country('usa').category('demographics').public().providers
You can find more entities with the Global country filter. To apply that filter run: Catalog().country('glo')
[<Provider.get('usa_bls')>, <Provider.get('usa_acs')>, <Provider.get('gbr_cdrc')>, <Provider.get('worldpop')>]
Let's now take a look at all the demographics datasets provided by ACS in the US.
Catalog().country('usa').category('demographics').provider('usa_acs').datasets.to_dataframe().head()
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_a0c48b07 | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | County - United States of America (2015) | Shoreline clipped TIGER/Line boundaries. More ... | yearly | [2007-01-01, 2008-01-01) | yearly | True | eng | 2007 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_count... | carto-do-public-data.usa_acs.demographics_soci... |
1 | acs_sociodemogr_a03fb95f | Sociodemographics - United States of America (... | The American Community Survey (ACS) is an ongo... | demographics | usa | sociodemographics | usa_acs | Congressional District - United States of Amer... | Shoreline clipped TIGER/Line boundaries. More ... | yearly | [2017-01-01, 2018-01-01) | yearly | True | eng | 2017 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_congr... | carto-do-public-data.usa_acs.demographics_soci... |
2 | acs_sociodemogr_e7b702b0 | 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 ... | 3yrs | [2006-01-01, 2009-01-01) | yearly | True | eng | 20062008 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_cbsa_... | carto-do-public-data.usa_acs.demographics_soci... |
3 | acs_sociodemogr_e1e92d8d | 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 ... | yearly | [2013-01-01, 2014-01-01) | yearly | True | eng | 2013 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_cbsa_... | carto-do-public-data.usa_acs.demographics_soci... |
4 | acs_sociodemogr_30a865f1 | 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 ... | 3yrs | [2005-01-01, 2008-01-01) | yearly | True | eng | 20052007 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_cbsa_... | carto-do-public-data.usa_acs.demographics_soci... |
We can explore the types of geographies for which the datasets are available. In order to filter by a specific type of geography, we have to apply a filter to the geography_name column just like we would for a string column on a Pandas DataFrame.
datasets_acs_df = Catalog().country('usa').category('demographics').provider('usa_acs').datasets.to_dataframe()
You can find more entities with the Global country filter. To apply that filter run: Catalog().country('glo')
datasets_acs_df['geography_name'].unique()
array(['County - United States of America (2015)', 'Congressional District - United States of America (2019)', 'Core-based Statistical Area - United States of America (2019)', 'Census Tract - United States of America (2015)', 'Public Use Microdata Area - United States of America (2019)', 'Census Place - United States of America (2019)', 'State - United States of America (2015)', 'Census Block Group - United States of America (2015)', '5-digit Zip Code Tabulation Area - United States of America (2015)', 'School District (secondary) - United States of America (2019)', 'School District (elementary) - United States of America (2019)', 'School District (unified) - United States of America (2019)'], dtype=object)
datasets_acs_df[datasets_acs_df['geography_name'].str.contains('Census Tract')]
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 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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) | yearly | True | eng | 20122016 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
9 | 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) | yearly | True | eng | 20092013 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
35 | 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) | yearly | True | eng | 20072011 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
41 | 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) | yearly | True | eng | 20132017 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
42 | 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) | yearly | True | eng | 20062010 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
169 | 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) | yearly | True | eng | 20102014 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
201 | 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) | yearly | True | eng | 20112015 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
231 | 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 | yearly | True | eng | 20142018 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
246 | 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) | yearly | True | eng | 20082012 | Demographics | American Community Survey | carto-do-public-data.carto.geography_usa_censu... | carto-do-public-data.usa_acs.demographics_soci... |
We select the dataset acs_sociodemogr_496a0675 from the list of datasets above because it is the one with the latest data update.
CARTOframes allows you to get a first glimpse of the dataset so that you can make sure it's the right dataset for your analysis. This includes:
describe()
function in Pandas.sample_ds = Dataset.get('acs_sociodemogr_496a0675')
sample_ds.to_dict()
{'slug': 'acs_sociodemogr_496a0675', 'name': 'Sociodemographics - United States of America (Census Tract, 2017, 5yrs)', 'description': 'The American Community Survey (ACS) is an ongoing survey that provides vital information on a yearly basis about the USA and its people. This dataset contains only a subset of the variables that have been deemed most relevant. More info: https://www.census.gov/programs-surveys/acs/about.html', 'category_id': 'demographics', 'country_id': 'usa', 'data_source_id': 'sociodemographics', 'provider_id': 'usa_acs', 'geography_name': 'Census Tract - United States of America (2015)', 'geography_description': 'Shoreline clipped TIGER/Line boundaries. More info: https://carto.com/blog/tiger-shoreline-clip/', 'temporal_aggregation': '5yrs', 'time_coverage': '[2013-01-01, 2018-01-01)', 'update_frequency': 'yearly', 'is_public_data': True, 'lang': 'eng', 'version': '20132017', 'category_name': 'Demographics', 'provider_name': 'American Community Survey', 'geography_id': 'carto-do-public-data.carto.geography_usa_censustract_2015', 'id': 'carto-do-public-data.usa_acs.demographics_sociodemographics_usa_censustract_2015_5yrs_20132017'}
sample_ds.variables.to_dataframe().head(5)
slug | name | description | db_type | agg_method | column_name | variable_group_id | dataset_id | id | |
---|---|---|---|---|---|---|---|---|---|
0 | geoid_e99a58c1 | geoid | US Census Block Groups Geoids | STRING | None | geoid | None | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
1 | do_date_45f076c2 | do_date | First day of the year the survey was issued | DATE | None | do_date | None | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
2 | total_pop_17ea032f | Total Population | Total Population. The total number of all peop... | FLOAT | SUM | total_pop | None | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
3 | households_a12defd5 | Number of households | Households. A count of the number of household... | FLOAT | SUM | households | None | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
4 | male_pop_eac43e5a | male_pop | Male Population. The number of people within e... | FLOAT | SUM | male_pop | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... | carto-do-public-data.usa_acs.demographics_soci... |
sample_ds.head()
geoid | no_car | do_date | male_20 | male_21 | no_cars | one_car | poverty | children | male_pop | two_cars | asian_pop | black_pop | female_20 | female_21 | in_school | pop_25_64 | total_pop | white_pop | female_pop | gini_index | households | male_60_61 | male_62_64 | median_age | three_cars | male_5_to_9 | median_rent | pop_16_over | pop_widowed | armed_forces | employed_pop | hispanic_pop | male_under_5 | mobile_homes | pop_divorced | female_5_to_9 | housing_units | male_10_to_14 | male_15_to_17 | male_18_to_19 | male_22_to_24 | male_25_to_29 | male_30_to_34 | male_35_to_39 | male_40_to_44 | male_45_to_49 | male_45_to_64 | male_50_to_54 | male_55_to_59 | male_65_to_66 | male_67_to_69 | male_70_to_74 | male_75_to_79 | male_80_to_84 | median_income | pop_separated | amerindian_pop | female_under_5 | four_more_cars | group_quarters | masters_degree | other_race_pop | unemployed_pop | walked_to_work | worked_at_home | female_10_to_14 | female_15_to_17 | female_18_to_19 | female_22_to_24 | female_25_to_29 | female_30_to_34 | female_35_to_39 | female_40_to_44 | female_45_to_49 | female_50_to_54 | female_55_to_59 | female_60_to_61 | female_62_to_64 | female_65_to_66 | female_67_to_69 | female_70_to_74 | female_75_to_79 | female_80_to_84 | pop_15_and_over | pop_now_married | asian_male_45_54 | asian_male_55_64 | bachelors_degree | black_male_45_54 | black_male_55_64 | commute_5_9_mins | commuters_by_bus | in_grades_1_to_4 | in_grades_5_to_8 | male_85_and_over | not_hispanic_pop | pop_5_years_over | white_male_45_54 | white_male_55_64 | associates_degree | commuters_16_over | dwellings_2_units | family_households | hispanic_any_race | in_grades_9_to_12 | income_less_10000 | income_per_capita | pop_25_years_over | pop_never_married | bachelors_degree_2 | commute_10_14_mins | commute_15_19_mins | commute_20_24_mins | commute_25_29_mins | commute_30_34_mins | commute_35_39_mins | commute_35_44_mins | commute_40_44_mins | commute_45_59_mins | commute_60_89_mins | female_85_and_over | income_10000_14999 | income_15000_19999 | income_20000_24999 | income_25000_29999 | income_30000_34999 | income_35000_39999 | income_40000_44999 | income_45000_49999 | income_50000_59999 | income_60000_74999 | income_75000_99999 | married_households | not_in_labor_force | not_us_citizen_pop | pop_in_labor_force | high_school_diploma | hispanic_male_45_54 | hispanic_male_55_64 | occupation_services | workers_16_and_over | civilian_labor_force | commute_60_more_mins | commute_90_more_mins | commute_less_10_mins | commuters_by_carpool | employed_information | in_undergrad_college | income_100000_124999 | income_125000_149999 | income_150000_199999 | male_male_households | nonfamily_households | rent_over_50_percent | vacant_housing_units | commuters_drove_alone | employed_construction | employed_retail_trade | income_200000_or_more | less_one_year_college | male_45_64_grade_9_12 | one_year_more_college | rent_10_to_15_percent | rent_15_to_20_percent | rent_20_to_25_percent | rent_25_to_30_percent | rent_30_to_35_percent | rent_35_to_40_percent | rent_40_to_50_percent | rent_under_10_percent | sales_office_employed | speak_spanish_at_home | two_or_more_races_pop | dwellings_3_to_4_units | dwellings_5_to_9_units | employed_manufacturing | male_45_64_high_school | occupied_housing_units | male_45_64_some_college | mortgaged_housing_units | occupation_sales_office | population_3_years_over | asian_including_hispanic | black_including_hispanic | dwellings_10_to_19_units | dwellings_20_to_49_units | employed_wholesale_trade | female_female_households | rent_burden_not_computed | white_including_hispanic | high_school_including_ged | commuters_by_car_truck_van | dwellings_1_units_attached | dwellings_1_units_detached | dwellings_50_or_more_units | housing_built_2000_to_2004 | male_45_64_graduate_degree | occupation_management_arts | population_1_year_and_over | speak_only_english_at_home | housing_built_2005_or_later | male_45_64_bachelors_degree | median_year_structure_built | children_in_single_female_hh | families_with_young_children | graduate_professional_degree | households_retirement_income | male_45_64_associates_degree | male_45_64_less_than_9_grade | million_dollar_housing_units | owner_occupied_housing_units | percent_income_spent_on_rent | aggregate_travel_time_to_work | amerindian_including_hispanic | housing_built_1939_or_earlier | housing_units_renter_occupied | pop_determined_poverty_status | vacant_housing_units_for_rent | vacant_housing_units_for_sale | employed_public_administration | less_than_high_school_graduate | commuters_by_subway_or_elevated | bachelors_degree_or_higher_25_64 | employed_education_health_social | speak_spanish_at_home_low_english | commuters_by_public_transportation | different_house_year_ago_same_city | some_college_and_associates_degree | households_public_asst_or_food_stamps | management_business_sci_arts_employed | employed_finance_insurance_real_estate | different_house_year_ago_different_city | employed_science_management_admin_waste | one_parent_families_with_young_children | two_parent_families_with_young_children | employed_other_services_not_public_admin | owner_occupied_housing_units_median_value | employed_transportation_warehousing_utilities | occupation_production_transportation_material | father_one_parent_families_with_young_children | owner_occupied_housing_units_lower_value_quartile | owner_occupied_housing_units_upper_value_quartile | employed_agriculture_forestry_fishing_hunting_mining | occupation_natural_resources_construction_maintenance | two_parents_in_labor_force_families_with_young_children | employed_arts_entertainment_recreation_accommodation_food | renter_occupied_housing_units_paying_cash_median_gross_rent | two_parents_not_in_labor_force_families_with_young_children | father_in_labor_force_one_parent_families_with_young_children | two_parents_father_in_labor_force_families_with_young_children | two_parents_mother_in_labor_force_families_with_young_children | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 47157005000 | 76.0 | 20132017 | 0.0 | 0.0 | 151.0 | 122.0 | 552.0 | 316.0 | 415.0 | 64.0 | 0.0 | 1004.0 | 19.0 | 42.0 | 331.0 | 328.0 | 1042.0 | 16.0 | 627.0 | 0.4372 | 343.0 | 0.0 | 2.0 | 28.9 | 0.0 | 38.0 | 391.0 | 749.0 | None | 0.0 | 233.0 | 0.0 | 44.0 | 5.0 | None | 76.0 | 465.0 | 27.0 | 26.0 | 30.0 | 22.0 | 11.0 | 13.0 | 31.0 | 11.0 | 15.0 | 79.0 | 21.0 | 41.0 | 0.0 | 5.0 | 26.0 | 5.0 | 31.0 | 14410.0 | None | 0.0 | 24.0 | 6.0 | 45.0 | 13.0 | 0.0 | 71.0 | 7.0 | 0.0 | 47.0 | 34.0 | 17.0 | 32.0 | 34.0 | 13.0 | 38.0 | 19.0 | 25.0 | 26.0 | 22.0 | 0.0 | 6.0 | 22.0 | 38.0 | 36.0 | 13.0 | 6.0 | None | None | 0.0 | 0.0 | 0.0 | 23.0 | 35.0 | 7.0 | 52.0 | 90.0 | 41.0 | 16.0 | 1042.0 | None | 13.0 | 3.0 | 28.0 | 233.0 | 13.0 | 183.0 | 0.0 | 111.0 | 79.0 | 8747.0 | 564.0 | None | 0.0 | 4.0 | 59.0 | 108.0 | 10.0 | 20.0 | 0.0 | 7.0 | 7.0 | 13.0 | 0.0 | 38.0 | 105.0 | 44.0 | 38.0 | 13.0 | 18.0 | 11.0 | 0.0 | 0.0 | 7.0 | 10.0 | 18.0 | 26.0 | 445.0 | 0.0 | 304.0 | 188.0 | 0.0 | 0.0 | 58.0 | 233.0 | 304.0 | 5.0 | 5.0 | 7.0 | 21.0 | 0.0 | 63.0 | 0.0 | 0.0 | 0.0 | 0.0 | 160.0 | 38.0 | 122.0 | 141.0 | 24.0 | 19.0 | 0.0 | 22.0 | 18.0 | 85.0 | 11.0 | 42.0 | 39.0 | 33.0 | 47.0 | 9.0 | 41.0 | 0.0 | 30.0 | None | 22.0 | 63.0 | 69.0 | 16.0 | 41.0 | 343.0 | 10.0 | 20.0 | 30.0 | 999.0 | 0.0 | 1004.0 | 40.0 | 25.0 | 2.0 | 0.0 | 18.0 | 16.0 | 235.0 | 162.0 | 0.0 | 195.0 | 55.0 | 10.0 | 1.0 | 54.0 | 1019.0 | None | 0.0 | 0.0 | 1981.0 | 278.0 | 75.0 | 13.0 | 47.0 | 7.0 | 2.0 | 0.0 | 65.0 | 30.5 | None | 0.0 | 81.0 | 278.0 | 1042.0 | 14.0 | 0.0 | 4.0 | 181.0 | 0.0 | 1.0 | 57.0 | None | 52.0 | 38.0 | 135.0 | 147.0 | 54.0 | 0.0 | 15.0 | 33.0 | 75.0 | 0.0 | 14.0 | None | 43.0 | 80.0 | 0.0 | 26600.0 | 231300.0 | 0.0 | 11.0 | 0.0 | 21.0 | 507.0 | 0.0 | 0.0 | 0.0 | 0.0 |
1 | 72051990021 | 0.0 | 20132017 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | None | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | NaN | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | None | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 |
2 | 72071990000 | 0.0 | 20132017 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | None | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | NaN | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | None | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 |
3 | 01097990000 | 0.0 | 20132017 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 |
4 | 18127980001 | 0.0 | 20132017 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 |
5 | 47157980100 | 0.0 | 20132017 | 0.0 | 6.0 | 0.0 | 0.0 | 58.0 | 0.0 | 38.0 | 0.0 | 0.0 | 4.0 | 0.0 | 0.0 | 0.0 | 54.0 | 74.0 | 70.0 | 36.0 | NaN | 0.0 | 0.0 | 0.0 | 31.3 | 0.0 | 0.0 | NaN | 74.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 6.0 | 0.0 | 0.0 | 6.0 | 12.0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 4.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 74.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 4.0 | 18.0 | 6.0 | 0.0 | 0.0 | 0.0 | 5.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 74.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5896.0 | 58.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 74.0 | 0.0 | 0.0 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 18.0 | 0.0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 74.0 | 0.0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 70.0 | 18.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 74.0 | None | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 74.0 | 0.0 | 0.0 | 0.0 | 18.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 22.0 | 0.0 | 0.0 | 0.0 | 63.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 |
6 | 55071990000 | 0.0 | 20132017 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 |
7 | 25025990101 | 0.0 | 20132017 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 58.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 29.0 | 23.0 | 71.0 | 0.0 | 13.0 | NaN | 13.0 | 0.0 | 0.0 | 24.0 | 13.0 | 0.0 | NaN | 71.0 | None | 0.0 | 71.0 | 71.0 | 0.0 | 0.0 | None | 0.0 | 13.0 | 0.0 | 0.0 | 16.0 | 19.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 23.0 | 0.0 | 23.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 71.0 | 0.0 | 13.0 | 71.0 | 0.0 | 0.0 | 17785.0 | 23.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 36.0 | 0.0 | 0.0 | 0.0 | 0.0 | 35.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 13.0 | 0.0 | 0.0 | 0.0 | 71.0 | 71.0 | 23.0 | 0.0 | 23.0 | 13.0 | 71.0 | 71.0 | 35.0 | 0.0 | 0.0 | 0.0 | 0.0 | 29.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 13.0 | 0.0 | 0.0 | 23.0 | 13.0 | 0.0 | 0.0 | 0.0 | 71.0 | 0.0 | 19.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 52.0 | 23.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 16.0 | 71.0 | None | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 13.0 | 71.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 29.0 | None | 71.0 | 0.0 | 0.0 | 13.0 | 16.0 | 0.0 | 19.0 | 0.0 | 0.0 | 0.0 | 23.0 | None | 19.0 | 19.0 | 0.0 | NaN | NaN | 0.0 | 23.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 |
8 | 55025991703 | 0.0 | 20132017 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 |
9 | 26041990000 | 0.0 | 20132017 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | NaN | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | None | 0.0 | 0.0 | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 |
sample_ds.counts()
rows 7.400100e+04 cells 1.864825e+07 null_cells 7.901830e+05 null_cells_percent 4.237303e+00 dtype: float64
sample_ds.fields_by_type()
float 250 string 2 dtype: int64
sample_ds.describe()
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 | male_20 | male_21 | male_22_to_24 | male_25_to_29 | male_30_to_34 | male_35_to_39 | male_40_to_44 | male_45_to_49 | male_50_to_54 | male_55_to_59 | male_65_to_66 | male_67_to_69 | male_70_to_74 | male_75_to_79 | male_80_to_84 | male_85_and_over | female_under_5 | female_5_to_9 | female_10_to_14 | female_15_to_17 | female_18_to_19 | female_20 | female_21 | female_22_to_24 | female_25_to_29 | female_30_to_34 | female_35_to_39 | female_40_to_44 | female_45_to_49 | female_50_to_54 | female_55_to_59 | female_60_to_61 | female_62_to_64 | female_65_to_66 | female_67_to_69 | female_70_to_74 | female_75_to_79 | female_80_to_84 | female_85_and_over | white_pop | population_1_year_and_over | population_3_years_over | pop_5_years_over | pop_15_and_over | pop_16_over | pop_25_years_over | pop_25_64 | pop_never_married | pop_now_married | pop_separated | pop_widowed | pop_divorced | not_us_citizen_pop | black_pop | asian_pop | hispanic_pop | amerindian_pop | other_race_pop | two_or_more_races_pop | hispanic_any_race | not_hispanic_pop | asian_male_45_54 | asian_male_55_64 | black_male_45_54 | black_male_55_64 | hispanic_male_45_54 | hispanic_male_55_64 | white_male_45_54 | white_male_55_64 | median_income | income_per_capita | income_less_10000 | income_10000_14999 | income_15000_19999 | income_20000_24999 | income_25000_29999 | income_30000_34999 | income_35000_39999 | income_40000_44999 | income_45000_49999 | income_50000_59999 | income_60000_74999 | income_75000_99999 | income_100000_124999 | income_125000_149999 | income_150000_199999 | income_200000_or_more | pop_determined_poverty_status | poverty | gini_index | housing_units | renter_occupied_housing_units_paying_cash_median_gross_rent | owner_occupied_housing_units_lower_value_quartile | owner_occupied_housing_units_median_value | owner_occupied_housing_units_upper_value_quartile | occupied_housing_units | housing_units_renter_occupied | vacant_housing_units | vacant_housing_units_for_rent | vacant_housing_units_for_sale | dwellings_1_units_detached | dwellings_1_units_attached | dwellings_2_units | dwellings_3_to_4_units | dwellings_5_to_9_units | dwellings_10_to_19_units | dwellings_20_to_49_units | dwellings_50_or_more_units | mobile_homes | housing_built_2005_or_later | housing_built_2000_to_2004 | housing_built_1939_or_earlier | median_year_structure_built | married_households | nonfamily_households | family_households | households_public_asst_or_food_stamps | male_male_households | female_female_households | children | children_in_single_female_hh | median_rent | percent_income_spent_on_rent | rent_burden_not_computed | rent_over_50_percent | rent_40_to_50_percent | rent_35_to_40_percent | rent_30_to_35_percent | rent_25_to_30_percent | rent_20_to_25_percent | rent_15_to_20_percent | rent_10_to_15_percent | rent_under_10_percent | owner_occupied_housing_units | million_dollar_housing_units | mortgaged_housing_units | different_house_year_ago_different_city | different_house_year_ago_same_city | families_with_young_children | two_parent_families_with_young_children | two_parents_in_labor_force_families_with_young_children | two_parents_father_in_labor_force_families_with_young_children | two_parents_mother_in_labor_force_families_with_young_children | two_parents_not_in_labor_force_families_with_young_children | one_parent_families_with_young_children | father_one_parent_families_with_young_children | father_in_labor_force_one_parent_families_with_young_children | commute_less_10_mins | commute_10_14_mins | commute_15_19_mins | commute_20_24_mins | commute_25_29_mins | commute_30_34_mins | commute_35_44_mins | commute_45_59_mins | commute_60_more_mins | commuters_16_over | walked_to_work | worked_at_home | no_car | no_cars | one_car | two_cars | three_cars | four_more_cars | aggregate_travel_time_to_work | commuters_by_public_transportation | commuters_by_bus | commuters_by_car_truck_van | commuters_by_carpool | commuters_by_subway_or_elevated | commuters_drove_alone | group_quarters | associates_degree | bachelors_degree | high_school_diploma | less_one_year_college | masters_degree | one_year_more_college | less_than_high_school_graduate | high_school_including_ged | bachelors_degree_2 | bachelors_degree_or_higher_25_64 | graduate_professional_degree | some_college_and_associates_degree | male_45_64_associates_degree | male_45_64_bachelors_degree | male_45_64_graduate_degree | male_45_64_less_than_9_grade | male_45_64_grade_9_12 | male_45_64_high_school | male_45_64_some_college | male_45_to_64 | employed_pop | unemployed_pop | pop_in_labor_force | not_in_labor_force | workers_16_and_over | armed_forces | civilian_labor_force | employed_agriculture_forestry_fishing_hunting_mining | employed_arts_entertainment_recreation_accommodation_food | employed_construction | employed_education_health_social | employed_finance_insurance_real_estate | employed_information | employed_manufacturing | employed_other_services_not_public_admin | employed_public_administration | employed_retail_trade | employed_science_management_admin_waste | employed_transportation_warehousing_utilities | employed_wholesale_trade | occupation_management_arts | occupation_natural_resources_construction_maintenance | occupation_production_transportation_material | occupation_sales_office | occupation_services | management_business_sci_arts_employed | sales_office_employed | in_grades_1_to_4 | in_grades_5_to_8 | in_grades_9_to_12 | in_school | in_undergrad_college | speak_only_english_at_home | speak_spanish_at_home | speak_spanish_at_home_low_english | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
avg | 4.384716e+03 | 1.622255e+03 | 2.157711e+03 | 2.227005e+03 | 3.930112e+01 | 1.383831e+02 | 1.423078e+02 | 1.445751e+02 | 8.804836e+01 | 6.037216e+01 | 3.276450e+01 | 3.217450e+01 | 9.285125e+01 | 1.552524e+02 | 1.483501e+02 | 1.388303e+02 | 1.375463e+02 | 1.416246e+02 | 1.482727e+02 | 1.423548e+02 | 4.490084e+01 | 5.796503e+01 | 7.306170e+01 | 5.008765e+01 | 3.334291e+01 | 2.886338e+01 | 1.322310e+02 | 1.365999e+02 | 1.383163e+02 | 8.401951e+01 | 5.756660e+01 | 3.088993e+01 | 3.041858e+01 | 8.833956e+01 | 1.505691e+02 | 1.468783e+02 | 1.396495e+02 | 1.393065e+02 | 1.446716e+02 | 1.538896e+02 | 1.514543e+02 | 5.749201e+01 | 7.940259e+01 | 4.982987e+01 | 6.520221e+01 | 8.553553e+01 | 6.253888e+01 | 4.708153e+01 | 5.512231e+01 | 2.666237e+03 | 4.342539e+03 | 4.225816e+03 | None | None | 3.495006e+03 | 2.954858e+03 | 2.301326e+03 | None | None | None | None | None | 3.057622e+02 | 5.330768e+02 | 2.296153e+02 | 8.100321e+02 | 2.836241e+01 | 9.694369 | 1.007309e+02 | 8.100321e+02 | 3.574684e+03 | 1.491637e+01 | 11.693788 | 3.440143e+01 | 2.904223e+01 | 4.700662e+01 | 3.048543e+01 | 1.883150e+02 | 1.926332e+02 | 6.120650e+04 | 3.065180e+04 | 1.120286e+02 | 7.990310e+01 | 7.906576e+01 | 8.121069e+01 | 7.699035e+01 | 7.811121e+01 | 7.282273e+01 | 7.298924e+01 | 6.437017e+01 | 1.248865e+02 | 1.605002e+02 | 1.984182e+02 | 1.391279e+02 | 8.701426e+01 | 9.380035e+01 | 1.010161e+02 | 4.276775e+03 | 6.377423e+02 | 0.425911 | 1.850797e+03 | 1.058678e+03 | 1.765685e+05 | 2.443280e+05 | 3.329604e+05 | 1.622255e+03 | 5.861794e+02 | 2.285420e+02 | 3.884688e+01 | 1.863187e+01 | 1.143346e+03 | 1.092662e+02 | 6.762999e+01 | 8.112938e+01 | 8.797462e+01 | 8.248062e+01 | 6.591754e+01 | 9.643179e+01 | 1.150671e+02 | 1.610305e+01 | 4.221539e+01 | 9.403019e+01 | 1.971950e+03 | 7.829447e+02 | 5.526839e+02 | 1.069572e+03 | 2.201474e+02 | 2.847543 | 2.909866 | 1.004481e+03 | 2.549481e+02 | 8.960611e+02 | 3.075703e+01 | 4.549625e+01 | 1.383322e+02 | 4.980808e+01 | 3.622229e+01 | 4.936739e+01 | 6.223202e+01 | 6.874649e+01 | 6.792566e+01 | 4.691335e+01 | 2.113569e+01 | 1.036076e+03 | 1.498115e+01 | 6.556553e+02 | 4.115417e+02 | 1.951105e+02 | 3.127425e+02 | 2.018102e+02 | 1.182977e+02 | 7.417954e+01 | 6.340941 | 2.991987 | 1.109323e+02 | 2.560057e+01 | 2.281514e+01 | 2.433403e+02 | 2.615797e+02 | 2.943585e+02 | 2.800684e+02 | 1.222793e+02 | 2.636407e+02 | 1.311400e+02 | 1.560668e+02 | 1.717179e+02 | 1.924192e+03 | 5.515674e+01 | 9.526220e+01 | 8.728505e+01 | 1.442299e+02 | 5.405044e+02 | 6.048036e+02 | 2.295713e+02 | 1.031463e+02 | 5.934150e+04 | 1.031013e+02 | 5.114798e+01 | 1.729272e+03 | 1.847843e+02 | 3.818269e+01 | 1.544488e+03 | 1.098196e+02 | 2.452862e+02 | 5.649029e+02 | 6.904443e+02 | 1.821747e+02 | 2.468936e+02 | 4.290593e+02 | 3.755628e+02 | 8.088810e+02 | 5.663747e+02 | 7.435482e+02 | 3.491915e+02 | 8.603443e+02 | 4.302832e+01 | 1.000650e+02 | 6.498545e+01 | 3.009663e+01 | 4.223971e+01 | 1.648105e+02 | 1.128077e+02 | 5.580332e+02 | 2.049152e+03 | 1.456859e+02 | 2.208707e+03 | 1.286299e+03 | 2.019454e+03 | 1.386930e+01 | 2.194838e+03 | 3.827483e+01 | 1.984437e+02 | 1.299722e+02 | 4.733737e+02 | 1.346475e+02 | 4.315308e+01 | 2.104029e+02 | 1.003838e+02 | 9.616204e+01 | 2.338625e+02 | 2.311254e+02 | 1.043314e+02 | 5.501904e+01 | 7.665854e+02 | 1.820007e+02 | 2.491306e+02 | 4.828023e+02 | 3.686331e+02 | 7.665854e+02 | 4.828023e+02 | 2.228999e+02 | 2.253273e+02 | 2.322261e+02 | 1.116528e+03 | 2.557242e+02 | None | None | None |
max | 6.552800e+04 | 2.142900e+04 | 3.226600e+04 | 3.326200e+04 | 8.570000e+01 | 3.297000e+03 | 3.464000e+03 | 3.137000e+03 | 2.416000e+03 | 3.909000e+03 | 2.845000e+03 | 3.025000e+03 | 6.083000e+03 | 3.956000e+03 | 2.143000e+03 | 3.146000e+03 | 3.718000e+03 | 2.652000e+03 | 2.300000e+03 | 1.741000e+03 | 1.244000e+03 | 3.225000e+03 | 4.708000e+03 | 3.287000e+03 | 1.666000e+03 | 6.670000e+02 | 2.829000e+03 | 3.509000e+03 | 3.667000e+03 | 1.601000e+03 | 4.815000e+03 | 1.586000e+03 | 1.330000e+03 | 2.045000e+03 | 2.410000e+03 | 2.840000e+03 | 3.450000e+03 | 3.586000e+03 | 3.628000e+03 | 1.756000e+03 | 1.445000e+03 | 8.730000e+02 | 2.105000e+03 | 2.147000e+03 | 3.661000e+03 | 5.268000e+03 | 2.481000e+03 | 1.166000e+03 | 1.337000e+03 | 3.868400e+04 | 6.480300e+04 | 6.243800e+04 | None | None | 4.464200e+04 | 3.948600e+04 | 3.425800e+04 | None | None | None | None | None | 1.223200e+04 | 1.665500e+04 | 1.371200e+04 | 2.868300e+04 | 9.644000e+03 | 1385.000000 | 3.611000e+03 | 2.868300e+04 | 5.047700e+04 | 1.301000e+03 | 745.000000 | 1.094000e+03 | 1.122000e+03 | 1.464000e+03 | 7.770000e+02 | 2.189000e+03 | 2.545000e+03 | 2.500010e+05 | 2.202530e+05 | 1.550000e+03 | 9.300000e+02 | 7.610000e+02 | 1.009000e+03 | 8.760000e+02 | 8.640000e+02 | 1.530000e+03 | 1.118000e+03 | 8.610000e+02 | 2.054000e+03 | 2.789000e+03 | 3.368000e+03 | 2.704000e+03 | 2.157000e+03 | 3.878000e+03 | 5.386000e+03 | 6.533200e+04 | 9.440000e+03 | 0.829000 | 2.652600e+04 | 3.501000e+03 | 2.000001e+06 | 2.000001e+06 | 2.000001e+06 | 2.142900e+04 | 8.039000e+03 | 1.192400e+04 | 4.472000e+03 | 5.470000e+02 | 2.552700e+04 | 4.280000e+03 | 1.999000e+03 | 1.629000e+03 | 1.863000e+03 | 5.280000e+03 | 4.283000e+03 | 1.151800e+04 | 3.314000e+03 | 2.502000e+03 | 7.206000e+03 | 6.177000e+03 | 2.016000e+03 | 1.510500e+04 | 6.883000e+03 | 1.681300e+04 | 2.325000e+03 | 355.000000 | 174.000000 | 2.360800e+04 | 2.863000e+03 | 3.501000e+03 | 5.000000e+01 | 1.100000e+03 | 3.487000e+03 | 9.720000e+02 | 6.410000e+02 | 8.600000e+02 | 9.990000e+02 | 1.382000e+03 | 1.879000e+03 | 1.098000e+03 | 9.120000e+02 | 2.047300e+04 | 1.453000e+03 | 1.267200e+04 | 1.306400e+04 | 5.347000e+03 | 6.700000e+03 | 6.517000e+03 | 3.989000e+03 | 3.888000e+03 | 1308.000000 | 285.000000 | 1.418000e+03 | 5.020000e+02 | 5.020000e+02 | 1.162100e+04 | 5.838000e+03 | 7.095000e+03 | 4.886000e+03 | 2.205000e+03 | 4.880000e+03 | 3.178000e+03 | 5.390000e+03 | 6.070000e+03 | 2.648200e+04 | 1.162100e+04 | 7.043000e+03 | 8.111000e+03 | 5.847000e+03 | 1.554800e+04 | 1.201200e+04 | 3.231000e+03 | 1.107000e+03 | 9.731600e+05 | 7.759000e+03 | 3.940000e+03 | 2.501200e+04 | 3.023000e+03 | 5.945000e+03 | 2.198900e+04 | 1.642100e+04 | 4.070000e+03 | 1.376700e+04 | 8.215000e+03 | 4.037000e+03 | 7.767000e+03 | 5.621000e+03 | 5.363000e+03 | 8.929000e+03 | 1.376700e+04 | 2.285600e+04 | 1.037400e+04 | 1.274500e+04 | 8.550000e+02 | 2.547000e+03 | 2.448000e+03 | 9.000000e+02 | 1.626000e+03 | 2.084000e+03 | 1.628000e+03 | 6.993000e+03 | 2.894500e+04 | 1.607000e+03 | 3.055200e+04 | 3.414200e+04 | 2.825200e+04 | 2.121400e+04 | 3.055200e+04 | 4.197000e+03 | 5.211000e+03 | 1.950000e+03 | 9.127000e+03 | 2.853000e+03 | 1.141000e+03 | 3.993000e+03 | 1.175000e+03 | 1.816000e+03 | 2.808000e+03 | 5.115000e+03 | 1.465000e+03 | 1.294000e+03 | 1.909700e+04 | 3.973000e+03 | 2.495000e+03 | 6.162000e+03 | 3.948000e+03 | 1.909700e+04 | 6.162000e+03 | 5.927000e+03 | 5.674000e+03 | 4.965000e+03 | 2.398900e+04 | 1.298500e+04 | None | None | None |
min | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 7.700000e+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 | 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 | 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 | 0.000000e+00 | 0.000000e+00 | None | None | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | None | None | None | None | None | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 2.499000e+03 | 3.200000e+01 | 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 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000700 | 0.000000e+00 | 9.900000e+01 | 9.999000e+03 | 9.999000e+03 | 9.999000e+03 | 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 | 0.000000e+00 | 0.000000e+00 | 1.939000e+03 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000 | 0.000000 | 0.000000e+00 | 0.000000e+00 | 9.900000e+01 | 1.000000e+01 | 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 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000 | 0.000000 | 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 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 6.500000e+01 | 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 | 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 | 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 | 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 | None | None | None |
sum | 3.244734e+08 | 1.200485e+08 | 1.596728e+08 | 1.648006e+08 | 2.879751e+06 | 1.024049e+07 | 1.053092e+07 | 1.069870e+07 | 6.515667e+06 | 4.467600e+06 | 2.424606e+06 | 2.380945e+06 | 6.871085e+06 | 1.148883e+07 | 1.097806e+07 | 1.027358e+07 | 1.017856e+07 | 1.048036e+07 | 1.097233e+07 | 1.053440e+07 | 3.322707e+06 | 4.289470e+06 | 5.406639e+06 | 3.706536e+06 | 2.467409e+06 | 2.135919e+06 | 9.785223e+06 | 1.010853e+07 | 1.023555e+07 | 6.217528e+06 | 4.259986e+06 | 2.285886e+06 | 2.251005e+06 | 6.537216e+06 | 1.114227e+07 | 1.086914e+07 | 1.033420e+07 | 1.030882e+07 | 1.070584e+07 | 1.138799e+07 | 1.120777e+07 | 4.254466e+06 | 5.875871e+06 | 3.687460e+06 | 4.825029e+06 | 6.329715e+06 | 4.627940e+06 | 3.484080e+06 | 4.079106e+06 | 1.973042e+08 | 3.172486e+08 | 3.127146e+08 | None | None | 2.586340e+08 | 2.186624e+08 | 1.703004e+08 | None | None | None | None | None | 2.233776e+07 | 3.944822e+07 | 1.699176e+07 | 5.994318e+07 | 2.098847e+06 | 717393.000000 | 7.454186e+06 | 5.994318e+07 | 2.645302e+08 | 1.103826e+06 | 865352.000000 | 2.545740e+06 | 2.149154e+06 | 3.478537e+06 | 2.255952e+06 | 1.393550e+07 | 1.425505e+07 | 4.464586e+09 | 2.245429e+09 | 8.290228e+06 | 5.912909e+06 | 5.850945e+06 | 6.009672e+06 | 5.697363e+06 | 5.780308e+06 | 5.388955e+06 | 5.401277e+06 | 4.763457e+06 | 9.241728e+06 | 1.187718e+07 | 1.468315e+07 | 1.029560e+07 | 6.439142e+06 | 6.941320e+06 | 7.475296e+06 | 3.164856e+08 | 4.719356e+07 | 31111.100500 | 1.369609e+08 | 7.612849e+07 | 1.258933e+10 | 1.758746e+10 | 2.396882e+10 | 1.200485e+08 | 4.337786e+07 | 1.691234e+07 | 2.874708e+06 | 1.378777e+06 | 8.460878e+07 | 8.085807e+06 | 5.004687e+06 | 6.003655e+06 | 6.510210e+06 | 6.103648e+06 | 4.877964e+06 | 7.136049e+06 | 8.515077e+06 | 1.191642e+06 | 3.123981e+06 | 6.958328e+06 | 1.429487e+08 | 5.793869e+07 | 4.089916e+07 | 7.914937e+07 | 1.629113e+07 | 210721.000000 | 215333.000000 | 7.433261e+07 | 1.886641e+07 | 6.427357e+07 | 2.225702e+06 | 3.366768e+06 | 1.023672e+07 | 3.685848e+06 | 2.680486e+06 | 3.653236e+06 | 4.605232e+06 | 5.087309e+06 | 5.026567e+06 | 3.471635e+06 | 1.564062e+06 | 7.667066e+07 | 1.108620e+06 | 4.851915e+07 | 3.006559e+07 | 1.425400e+07 | 2.314326e+07 | 1.493416e+07 | 8.754150e+06 | 5.489360e+06 | 469236.000000 | 221410.000000 | 8.209099e+06 | 1.894468e+06 | 1.688343e+06 | 1.800742e+07 | 1.935716e+07 | 2.178282e+07 | 2.072534e+07 | 9.048793e+06 | 1.950968e+07 | 9.704493e+06 | 1.154910e+07 | 1.270730e+07 | 1.423921e+08 | 4.081654e+06 | 7.049498e+06 | 6.459181e+06 | 1.067316e+07 | 3.999786e+07 | 4.475607e+07 | 1.698850e+07 | 7.632928e+06 | 2.970754e+09 | 7.629599e+06 | 3.785002e+06 | 1.279679e+08 | 1.367422e+07 | 2.825557e+06 | 1.142936e+08 | 8.126758e+06 | 1.815143e+07 | 4.180338e+07 | 5.109357e+07 | 1.348111e+07 | 1.827037e+07 | 3.175082e+07 | 2.743711e+07 | 5.909361e+07 | 4.137707e+07 | 5.502331e+07 | 2.551054e+07 | 6.285332e+07 | 3.184139e+06 | 7.404907e+06 | 4.808988e+06 | 2.227181e+06 | 3.125781e+06 | 1.219614e+07 | 8.347879e+06 | 4.129502e+07 | 1.516393e+08 | 1.078090e+07 | 1.634465e+08 | 9.518743e+07 | 1.494416e+08 | 1.026342e+06 | 1.624202e+08 | 2.832376e+06 | 1.468503e+07 | 9.618071e+06 | 3.503013e+07 | 9.964050e+06 | 3.193371e+06 | 1.557002e+07 | 7.428501e+06 | 7.116087e+06 | 1.730606e+07 | 1.710351e+07 | 7.720629e+06 | 4.071464e+06 | 5.672809e+07 | 1.346823e+07 | 1.843592e+07 | 3.572785e+07 | 2.727922e+07 | 5.672809e+07 | 3.572785e+07 | 1.649482e+07 | 1.667444e+07 | 1.718497e+07 | 8.262417e+07 | 1.892385e+07 | None | None | None |
range | 6.552800e+04 | 2.142900e+04 | 3.226600e+04 | 3.326200e+04 | 7.800000e+01 | 3.297000e+03 | 3.464000e+03 | 3.137000e+03 | 2.416000e+03 | 3.909000e+03 | 2.845000e+03 | 3.025000e+03 | 6.083000e+03 | 3.956000e+03 | 2.143000e+03 | 3.146000e+03 | 3.718000e+03 | 2.652000e+03 | 2.300000e+03 | 1.741000e+03 | 1.244000e+03 | 3.225000e+03 | 4.708000e+03 | 3.287000e+03 | 1.666000e+03 | 6.670000e+02 | 2.829000e+03 | 3.509000e+03 | 3.667000e+03 | 1.601000e+03 | 4.815000e+03 | 1.586000e+03 | 1.330000e+03 | 2.045000e+03 | 2.410000e+03 | 2.840000e+03 | 3.450000e+03 | 3.586000e+03 | 3.628000e+03 | 1.756000e+03 | 1.445000e+03 | 8.730000e+02 | 2.105000e+03 | 2.147000e+03 | 3.661000e+03 | 5.268000e+03 | 2.481000e+03 | 1.166000e+03 | 1.337000e+03 | 3.868400e+04 | 6.480300e+04 | 6.243800e+04 | None | None | 4.464200e+04 | 3.948600e+04 | 3.425800e+04 | None | None | None | None | None | 1.223200e+04 | 1.665500e+04 | 1.371200e+04 | 2.868300e+04 | 9.644000e+03 | 1385.000000 | 3.611000e+03 | 2.868300e+04 | 5.047700e+04 | 1.301000e+03 | 745.000000 | 1.094000e+03 | 1.122000e+03 | 1.464000e+03 | 7.770000e+02 | 2.189000e+03 | 2.545000e+03 | 2.475020e+05 | 2.202210e+05 | 1.550000e+03 | 9.300000e+02 | 7.610000e+02 | 1.009000e+03 | 8.760000e+02 | 8.640000e+02 | 1.530000e+03 | 1.118000e+03 | 8.610000e+02 | 2.054000e+03 | 2.789000e+03 | 3.368000e+03 | 2.704000e+03 | 2.157000e+03 | 3.878000e+03 | 5.386000e+03 | 6.533200e+04 | 9.440000e+03 | 0.828300 | 2.652600e+04 | 3.402000e+03 | 1.990002e+06 | 1.990002e+06 | 1.990002e+06 | 2.142900e+04 | 8.039000e+03 | 1.192400e+04 | 4.472000e+03 | 5.470000e+02 | 2.552700e+04 | 4.280000e+03 | 1.999000e+03 | 1.629000e+03 | 1.863000e+03 | 5.280000e+03 | 4.283000e+03 | 1.151800e+04 | 3.314000e+03 | 2.502000e+03 | 7.206000e+03 | 6.177000e+03 | 7.700000e+01 | 1.510500e+04 | 6.883000e+03 | 1.681300e+04 | 2.325000e+03 | 355.000000 | 174.000000 | 2.360800e+04 | 2.863000e+03 | 3.402000e+03 | 4.000000e+01 | 1.100000e+03 | 3.487000e+03 | 9.720000e+02 | 6.410000e+02 | 8.600000e+02 | 9.990000e+02 | 1.382000e+03 | 1.879000e+03 | 1.098000e+03 | 9.120000e+02 | 2.047300e+04 | 1.453000e+03 | 1.267200e+04 | 1.306400e+04 | 5.347000e+03 | 6.700000e+03 | 6.517000e+03 | 3.989000e+03 | 3.888000e+03 | 1308.000000 | 285.000000 | 1.418000e+03 | 5.020000e+02 | 5.020000e+02 | 1.162100e+04 | 5.838000e+03 | 7.095000e+03 | 4.886000e+03 | 2.205000e+03 | 4.880000e+03 | 3.178000e+03 | 5.390000e+03 | 6.070000e+03 | 2.648200e+04 | 1.162100e+04 | 7.043000e+03 | 8.111000e+03 | 5.847000e+03 | 1.554800e+04 | 1.201200e+04 | 3.231000e+03 | 1.107000e+03 | 9.730950e+05 | 7.759000e+03 | 3.940000e+03 | 2.501200e+04 | 3.023000e+03 | 5.945000e+03 | 2.198900e+04 | 1.642100e+04 | 4.070000e+03 | 1.376700e+04 | 8.215000e+03 | 4.037000e+03 | 7.767000e+03 | 5.621000e+03 | 5.363000e+03 | 8.929000e+03 | 1.376700e+04 | 2.285600e+04 | 1.037400e+04 | 1.274500e+04 | 8.550000e+02 | 2.547000e+03 | 2.448000e+03 | 9.000000e+02 | 1.626000e+03 | 2.084000e+03 | 1.628000e+03 | 6.993000e+03 | 2.894500e+04 | 1.607000e+03 | 3.055200e+04 | 3.414200e+04 | 2.825200e+04 | 2.121400e+04 | 3.055200e+04 | 4.197000e+03 | 5.211000e+03 | 1.950000e+03 | 9.127000e+03 | 2.853000e+03 | 1.141000e+03 | 3.993000e+03 | 1.175000e+03 | 1.816000e+03 | 2.808000e+03 | 5.115000e+03 | 1.465000e+03 | 1.294000e+03 | 1.909700e+04 | 3.973000e+03 | 2.495000e+03 | 6.162000e+03 | 3.948000e+03 | 1.909700e+04 | 6.162000e+03 | 5.927000e+03 | 5.674000e+03 | 4.965000e+03 | 2.398900e+04 | 1.298500e+04 | None | None | None |
stdev | 2.228937e+03 | 7.936172e+02 | 1.120561e+03 | 1.146240e+03 | 7.750633e+00 | 1.104914e+02 | 1.121643e+02 | 1.132003e+02 | 7.188730e+01 | 1.075927e+02 | 5.489900e+01 | 5.251894e+01 | 9.475956e+01 | 1.251577e+02 | 1.155036e+02 | 1.057082e+02 | 1.034058e+02 | 9.913924e+01 | 9.575753e+01 | 8.738622e+01 | 3.685899e+01 | 4.708550e+01 | 5.993755e+01 | 4.641712e+01 | 3.390149e+01 | 3.303075e+01 | 1.062496e+02 | 1.096859e+02 | 1.100421e+02 | 6.923133e+01 | 1.222020e+02 | 5.400368e+01 | 5.017502e+01 | 7.957206e+01 | 1.181003e+02 | 1.097178e+02 | 1.040098e+02 | 1.022617e+02 | 9.984035e+01 | 9.595609e+01 | 9.064753e+01 | 4.279481e+01 | 5.533706e+01 | 4.018353e+01 | 5.125616e+01 | 6.700952e+01 | 5.231319e+01 | 4.266777e+01 | 5.793785e+01 | 1.907504e+03 | 2.201732e+03 | 2.139467e+03 | None | None | 1.719905e+03 | 1.474748e+03 | 1.216138e+03 | None | None | None | None | None | 4.535513e+02 | 9.093226e+02 | 5.036082e+02 | 1.282778e+03 | 1.789563e+02 | 34.687847 | 1.270444e+02 | 1.282778e+03 | 2.056417e+03 | 3.975201e+01 | 31.827724 | 6.303262e+01 | 5.395722e+01 | 8.368872e+01 | 5.878341e+01 | 1.523871e+02 | 1.455158e+02 | 3.090106e+04 | 1.612694e+04 | 1.063003e+02 | 6.984943e+01 | 6.359047e+01 | 6.205942e+01 | 5.829994e+01 | 5.862582e+01 | 5.505314e+01 | 5.498863e+01 | 4.950700e+01 | 8.417410e+01 | 1.059809e+02 | 1.372959e+02 | 1.147172e+02 | 8.513799e+01 | 1.078177e+02 | 1.647825e+02 | 2.216522e+03 | 5.618142e+02 | 0.063577 | 8.958362e+02 | 4.642559e+02 | 1.648026e+05 | 2.189567e+05 | 2.866141e+05 | 7.936172e+02 | 4.791495e+02 | 3.131224e+02 | 6.702031e+01 | 2.830720e+01 | 7.543086e+02 | 1.952911e+02 | 1.133588e+02 | 1.165817e+02 | 1.324159e+02 | 1.511113e+02 | 1.440865e+02 | 2.991683e+02 | 2.250775e+02 | 4.732752e+01 | 1.038676e+02 | 1.166008e+02 | 1.755339e+01 | 5.050110e+02 | 3.637558e+02 | 5.859720e+02 | 1.966127e+02 | 8.899265 | 7.652833 | 6.760134e+02 | 2.402736e+02 | 4.587204e+02 | 7.795312e+00 | 4.974370e+01 | 1.432986e+02 | 5.574670e+01 | 4.303120e+01 | 5.598719e+01 | 6.694950e+01 | 7.252401e+01 | 7.206055e+01 | 5.312190e+01 | 3.129274e+01 | 6.543429e+02 | 5.537075e+01 | 4.790928e+02 | 3.932843e+02 | 2.492432e+02 | 2.316744e+02 | 1.829281e+02 | 1.148169e+02 | 9.050640e+01 | 18.145011 | 11.523613 | 1.141550e+02 | 3.774419e+01 | 3.534531e+01 | 2.257531e+02 | 1.967251e+02 | 2.132096e+02 | 2.089584e+02 | 1.102167e+02 | 2.155892e+02 | 1.292811e+02 | 1.602168e+02 | 1.904055e+02 | 1.072317e+03 | 1.404476e+02 | 1.047340e+02 | 2.315210e+02 | 2.298423e+02 | 3.314566e+02 | 3.799984e+02 | 1.711299e+02 | 9.448405e+01 | 3.422968e+04 | 2.647627e+02 | 1.086306e+02 | 1.041140e+03 | 1.447731e+02 | 1.967409e+02 | 9.474669e+02 | 4.446641e+02 | 1.694405e+02 | 4.828823e+02 | 4.093667e+02 | 1.267778e+02 | 2.557686e+02 | 2.629695e+02 | 3.540041e+02 | 4.791437e+02 | 4.842803e+02 | 7.062823e+02 | 3.801689e+02 | 5.062105e+02 | 4.047851e+01 | 1.009911e+02 | 8.698075e+01 | 4.965424e+01 | 4.571015e+01 | 1.159105e+02 | 8.115282e+01 | 3.033556e+02 | 1.138865e+03 | 1.092197e+02 | 1.203354e+03 | 7.150048e+02 | 1.129133e+03 | 1.616169e+02 | 1.192208e+03 | 8.874869e+01 | 1.600300e+02 | 1.116914e+02 | 3.015791e+02 | 1.305728e+02 | 5.400275e+01 | 1.826280e+02 | 7.619403e+01 | 9.987631e+01 | 1.551951e+02 | 2.015002e+02 | 9.018655e+01 | 5.451432e+01 | 6.156759e+02 | 1.512020e+02 | 1.862018e+02 | 2.988008e+02 | 2.366780e+02 | 6.156759e+02 | 2.988008e+02 | 1.687454e+02 | 1.692225e+02 | 1.687234e+02 | 7.662855e+02 | 4.083119e+02 | None | None | None |
q1 | 2.627000e+03 | 9.980000e+02 | 1.276000e+03 | 1.318000e+03 | 3.280000e+01 | 5.600000e+01 | 5.700000e+01 | 5.900000e+01 | 3.200000e+01 | 1.400000e+01 | 0.000000e+00 | 0.000000e+00 | 3.100000e+01 | 6.100000e+01 | 6.100000e+01 | 6.000000e+01 | 6.000000e+01 | 6.600000e+01 | 7.200000e+01 | 7.100000e+01 | 1.500000e+01 | 2.200000e+01 | 2.800000e+01 | 1.600000e+01 | 8.000000e+00 | 4.000000e+00 | 5.300000e+01 | 5.400000e+01 | 5.500000e+01 | 3.000000e+01 | 1.200000e+01 | 0.000000e+00 | 0.000000e+00 | 3.000000e+01 | 6.000000e+01 | 6.400000e+01 | 6.200000e+01 | 6.200000e+01 | 6.800000e+01 | 7.700000e+01 | 7.700000e+01 | 2.300000e+01 | 3.500000e+01 | 1.800000e+01 | 2.600000e+01 | 3.600000e+01 | 2.200000e+01 | 1.400000e+01 | 1.400000e+01 | 9.510000e+02 | 2.604000e+03 | 2.519000e+03 | None | None | 2.125000e+03 | 1.782000e+03 | 1.328000e+03 | None | None | None | None | None | 2.200000e+01 | 1.600000e+01 | 0.000000e+00 | 6.600000e+01 | 0.000000e+00 | 0.000000 | 1.600000e+01 | 6.600000e+01 | 1.943000e+03 | 0.000000e+00 | 0.000000 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 5.300000e+01 | 6.000000e+01 | 3.697400e+04 | 1.902300e+04 | 3.400000e+01 | 2.300000e+01 | 2.600000e+01 | 3.000000e+01 | 2.900000e+01 | 3.000000e+01 | 2.800000e+01 | 2.900000e+01 | 2.400000e+01 | 5.800000e+01 | 7.600000e+01 | 8.600000e+01 | 4.700000e+01 | 1.900000e+01 | 1.400000e+01 | 8.000000e+00 | 2.559000e+03 | 2.120000e+02 | 0.373800 | 1.153000e+03 | 6.920000e+02 | 6.570000e+04 | 9.880000e+04 | 1.491000e+05 | 9.980000e+02 | 2.090000e+02 | 6.400000e+01 | 0.000000e+00 | 0.000000e+00 | 5.220000e+02 | 7.000000e+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 | 9.000000e+00 | 1.956000e+03 | 3.810000e+02 | 2.730000e+02 | 6.120000e+02 | 6.200000e+01 | 0.000000 | 0.000000 | 5.080000e+02 | 7.300000e+01 | 5.290000e+02 | 2.420000e+01 | 9.000000e+00 | 2.900000e+01 | 7.000000e+00 | 0.000000e+00 | 7.000000e+00 | 1.100000e+01 | 1.400000e+01 | 1.500000e+01 | 8.000000e+00 | 0.000000e+00 | 4.960000e+02 | 0.000000e+00 | 2.740000e+02 | 1.400000e+02 | 6.000000e+00 | 1.410000e+02 | 7.000000e+01 | 3.400000e+01 | 1.200000e+01 | 0.000000 | 0.000000 | 2.300000e+01 | 0.000000e+00 | 0.000000e+00 | 8.400000e+01 | 1.040000e+02 | 1.260000e+02 | 1.100000e+02 | 3.600000e+01 | 9.500000e+01 | 3.300000e+01 | 3.800000e+01 | 4.200000e+01 | 1.072000e+03 | 0.000000e+00 | 2.300000e+01 | 7.000000e+00 | 2.900000e+01 | 2.780000e+02 | 3.010000e+02 | 8.500000e+01 | 2.400000e+01 | 3.315000e+04 | 0.000000e+00 | 0.000000e+00 | 8.940000e+02 | 7.400000e+01 | 0.000000e+00 | 7.800000e+02 | 0.000000e+00 | 1.090000e+02 | 1.910000e+02 | 3.420000e+02 | 8.000000e+01 | 6.200000e+01 | 2.220000e+02 | 1.150000e+02 | 4.000000e+02 | 1.920000e+02 | 2.200000e+02 | 8.100000e+01 | 4.570000e+02 | 1.100000e+01 | 2.400000e+01 | 8.000000e+00 | 0.000000e+00 | 7.000000e+00 | 6.700000e+01 | 4.700000e+01 | 3.160000e+02 | 1.143000e+03 | 6.000000e+01 | 1.245000e+03 | 7.460000e+02 | 1.115000e+03 | 0.000000e+00 | 1.235000e+03 | 0.000000e+00 | 8.200000e+01 | 4.500000e+01 | 2.340000e+02 | 4.100000e+01 | 7.000000e+00 | 6.500000e+01 | 4.000000e+01 | 2.900000e+01 | 1.110000e+02 | 8.100000e+01 | 3.700000e+01 | 1.300000e+01 | 2.900000e+02 | 6.300000e+01 | 9.600000e+01 | 2.430000e+02 | 1.860000e+02 | 2.900000e+02 | 2.430000e+02 | 9.700000e+01 | 9.700000e+01 | 1.020000e+02 | 5.600000e+02 | 8.400000e+01 | None | None | None |
q3 | 4.606000e+03 | 1.714000e+03 | 2.254000e+03 | 2.334000e+03 | 4.110000e+01 | 1.380000e+02 | 1.420000e+02 | 1.450000e+02 | 8.800000e+01 | 5.200000e+01 | 2.600000e+01 | 2.600000e+01 | 8.700000e+01 | 1.510000e+02 | 1.460000e+02 | 1.380000e+02 | 1.380000e+02 | 1.440000e+02 | 1.520000e+02 | 1.480000e+02 | 4.500000e+01 | 5.900000e+01 | 7.400000e+01 | 5.000000e+01 | 3.300000e+01 | 2.700000e+01 | 1.320000e+02 | 1.370000e+02 | 1.390000e+02 | 8.500000e+01 | 4.600000e+01 | 2.300000e+01 | 2.400000e+01 | 8.400000e+01 | 1.490000e+02 | 1.460000e+02 | 1.400000e+02 | 1.410000e+02 | 1.480000e+02 | 1.590000e+02 | 1.590000e+02 | 5.800000e+01 | 8.100000e+01 | 5.000000e+01 | 6.600000e+01 | 8.700000e+01 | 6.300000e+01 | 4.600000e+01 | 5.100000e+01 | 2.942000e+03 | 4.525000e+03 | 4.421000e+03 | None | None | 3.666000e+03 | 3.115000e+03 | 2.398000e+03 | None | None | None | None | None | 1.980000e+02 | 2.690000e+02 | 9.700000e+01 | 4.480000e+02 | 2.000000e+00 | 0.000000 | 8.800000e+01 | 4.480000e+02 | 3.809000e+03 | 0.000000e+00 | 0.000000 | 1.600000e+01 | 1.300000e+01 | 2.300000e+01 | 1.300000e+01 | 2.000000e+02 | 2.100000e+02 | 6.082500e+04 | 3.022100e+04 | 1.040000e+02 | 7.900000e+01 | 8.000000e+01 | 8.200000e+01 | 7.800000e+01 | 8.000000e+01 | 7.400000e+01 | 7.400000e+01 | 6.500000e+01 | 1.280000e+02 | 1.670000e+02 | 2.070000e+02 | 1.410000e+02 | 8.300000e+01 | 8.100000e+01 | 6.000000e+01 | 4.496000e+03 | 6.050000e+02 | 0.434700 | 1.949000e+03 | 1.055000e+03 | 1.533000e+05 | 2.108000e+05 | 2.867000e+05 | 1.714000e+03 | 5.700000e+02 | 1.880000e+02 | 3.100000e+01 | 1.500000e+01 | 1.248000e+03 | 6.200000e+01 | 4.100000e+01 | 5.900000e+01 | 6.000000e+01 | 4.300000e+01 | 2.700000e+01 | 2.000000e+01 | 2.700000e+01 | 0.000000e+00 | 2.100000e+01 | 8.100000e+01 | 1.978000e+03 | 8.130000e+02 | 5.550000e+02 | 1.126000e+03 | 2.100000e+02 | 0.000000 | 0.000000 | 1.019000e+03 | 2.330000e+02 | 8.890000e+02 | 3.140000e+01 | 4.100000e+01 | 1.260000e+02 | 4.500000e+01 | 3.200000e+01 | 4.400000e+01 | 5.700000e+01 | 6.300000e+01 | 6.200000e+01 | 4.200000e+01 | 1.700000e+01 | 1.105000e+03 | 0.000000e+00 | 6.790000e+02 | 3.830000e+02 | 1.660000e+02 | 3.130000e+02 | 1.970000e+02 | 1.130000e+02 | 6.600000e+01 | 0.000000 | 0.000000 | 1.000000e+02 | 1.900000e+01 | 1.700000e+01 | 2.310000e+02 | 2.610000e+02 | 2.970000e+02 | 2.830000e+02 | 1.210000e+02 | 2.610000e+02 | 1.240000e+02 | 1.450000e+02 | 1.450000e+02 | 2.014000e+03 | 3.400000e+01 | 8.700000e+01 | 4.800000e+01 | 1.090000e+02 | 5.560000e+02 | 6.360000e+02 | 2.400000e+02 | 1.020000e+02 | 6.035000e+04 | 3.400000e+01 | 2.000000e+01 | 1.824000e+03 | 1.830000e+02 | 0.000000e+00 | 1.637000e+03 | 2.000000e+01 | 2.520000e+02 | 5.500000e+02 | 7.280000e+02 | 1.890000e+02 | 2.160000e+02 | 4.380000e+02 | 3.390000e+02 | 8.500000e+02 | 5.470000e+02 | 6.830000e+02 | 2.950000e+02 | 9.020000e+02 | 4.200000e+01 | 9.200000e+01 | 4.900000e+01 | 1.900000e+01 | 3.900000e+01 | 1.720000e+02 | 1.150000e+02 | 5.820000e+02 | 2.156000e+03 | 1.450000e+02 | 2.319000e+03 | 1.325000e+03 | 2.115000e+03 | 0.000000e+00 | 2.300000e+03 | 1.700000e+01 | 1.940000e+02 | 1.260000e+02 | 4.870000e+02 | 1.250000e+02 | 3.700000e+01 | 2.040000e+02 | 1.010000e+02 | 8.700000e+01 | 2.380000e+02 | 2.200000e+02 | 1.010000e+02 | 5.300000e+01 | 7.470000e+02 | 1.810000e+02 | 2.530000e+02 | 5.010000e+02 | 3.740000e+02 | 7.470000e+02 | 5.010000e+02 | 2.240000e+02 | 2.260000e+02 | 2.360000e+02 | 1.120000e+03 | 2.120000e+02 | None | None | None |
median | 3.627000e+03 | 1.357000e+03 | 1.773000e+03 | 1.842000e+03 | 3.710000e+01 | 9.400000e+01 | 9.800000e+01 | 9.900000e+01 | 5.900000e+01 | 3.100000e+01 | 1.300000e+01 | 1.300000e+01 | 5.600000e+01 | 1.030000e+02 | 1.010000e+02 | 9.600000e+01 | 9.700000e+01 | 1.030000e+02 | 1.110000e+02 | 1.080000e+02 | 2.900000e+01 | 3.900000e+01 | 5.000000e+01 | 3.200000e+01 | 1.900000e+01 | 1.500000e+01 | 9.000000e+01 | 9.400000e+01 | 9.400000e+01 | 5.600000e+01 | 2.700000e+01 | 1.100000e+01 | 1.100000e+01 | 5.600000e+01 | 1.020000e+02 | 1.020000e+02 | 1.000000e+02 | 9.900000e+01 | 1.060000e+02 | 1.180000e+02 | 1.170000e+02 | 4.000000e+01 | 5.800000e+01 | 3.400000e+01 | 4.500000e+01 | 6.000000e+01 | 4.100000e+01 | 2.900000e+01 | 3.000000e+01 | 1.989000e+03 | 3.590000e+03 | 3.499000e+03 | None | None | 2.921000e+03 | 2.453000e+03 | 1.880000e+03 | None | None | None | None | None | 8.200000e+01 | 8.200000e+01 | 2.800000e+01 | 1.870000e+02 | 0.000000e+00 | 0.000000 | 4.700000e+01 | 1.870000e+02 | 2.906000e+03 | 0.000000e+00 | 0.000000 | 0.000000e+00 | 0.000000e+00 | 5.000000e+00 | 0.000000e+00 | 1.270000e+02 | 1.350000e+02 | 4.881100e+04 | 2.455200e+04 | 6.400000e+01 | 4.800000e+01 | 5.100000e+01 | 5.500000e+01 | 5.200000e+01 | 5.300000e+01 | 4.900000e+01 | 5.000000e+01 | 4.400000e+01 | 9.200000e+01 | 1.200000e+02 | 1.450000e+02 | 9.200000e+01 | 4.800000e+01 | 4.000000e+01 | 2.600000e+01 | 3.523000e+03 | 3.830000e+02 | 0.405000 | 1.547000e+03 | 8.510000e+02 | 1.011000e+05 | 1.479000e+05 | 2.031000e+05 | 1.357000e+03 | 3.740000e+02 | 1.200000e+02 | 1.000000e+01 | 0.000000e+00 | 9.150000e+02 | 2.600000e+01 | 1.500000e+01 | 2.300000e+01 | 1.900000e+01 | 9.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 4.000000e+00 | 4.000000e+01 | 1.969000e+03 | 5.990000e+02 | 4.090000e+02 | 8.700000e+02 | 1.290000e+02 | 0.000000 | 0.000000 | 7.650000e+02 | 1.440000e+02 | 6.910000e+02 | 2.810000e+01 | 2.400000e+01 | 7.000000e+01 | 2.200000e+01 | 1.500000e+01 | 2.200000e+01 | 3.000000e+01 | 3.500000e+01 | 3.500000e+01 | 2.300000e+01 | 7.000000e+00 | 8.120000e+02 | 0.000000e+00 | 4.720000e+02 | 2.510000e+02 | 6.700000e+01 | 2.230000e+02 | 1.300000e+02 | 7.100000e+01 | 3.500000e+01 | 0.000000 | 0.000000 | 5.700000e+01 | 5.000000e+00 | 0.000000e+00 | 1.500000e+02 | 1.800000e+02 | 2.070000e+02 | 1.930000e+02 | 7.400000e+01 | 1.740000e+02 | 7.300000e+01 | 8.200000e+01 | 8.400000e+01 | 1.548000e+03 | 1.600000e+01 | 5.200000e+01 | 2.300000e+01 | 6.200000e+01 | 4.110000e+02 | 4.710000e+02 | 1.620000e+02 | 6.000000e+01 | 4.599500e+04 | 8.000000e+00 | 2.000000e+00 | 1.362000e+03 | 1.240000e+02 | 0.000000e+00 | 1.211000e+03 | 5.000000e+00 | 1.780000e+02 | 3.420000e+02 | 5.340000e+02 | 1.320000e+02 | 1.260000e+02 | 3.250000e+02 | 2.140000e+02 | 6.300000e+02 | 3.450000e+02 | 4.080000e+02 | 1.650000e+02 | 6.720000e+02 | 2.500000e+01 | 5.200000e+01 | 2.400000e+01 | 6.000000e+00 | 2.100000e+01 | 1.180000e+02 | 7.900000e+01 | 4.500000e+02 | 1.651000e+03 | 1.000000e+02 | 1.793000e+03 | 1.026000e+03 | 1.622000e+03 | 0.000000e+00 | 1.780000e+03 | 0.000000e+00 | 1.330000e+02 | 8.200000e+01 | 3.580000e+02 | 7.800000e+01 | 1.900000e+01 | 1.290000e+02 | 6.900000e+01 | 5.500000e+01 | 1.720000e+02 | 1.410000e+02 | 6.600000e+01 | 3.100000e+01 | 4.950000e+02 | 1.200000e+02 | 1.680000e+02 | 3.690000e+02 | 2.740000e+02 | 4.950000e+02 | 3.690000e+02 | 1.580000e+02 | 1.610000e+02 | 1.650000e+02 | 8.330000e+02 | 1.420000e+02 | None | None | None |
interquartile_range | 1.979000e+03 | 7.160000e+02 | 9.780000e+02 | 1.016000e+03 | 8.300000e+00 | 8.200000e+01 | 8.500000e+01 | 8.600000e+01 | 5.600000e+01 | 3.800000e+01 | 2.600000e+01 | 2.600000e+01 | 5.600000e+01 | 9.000000e+01 | 8.500000e+01 | 7.800000e+01 | 7.800000e+01 | 7.800000e+01 | 8.000000e+01 | 7.700000e+01 | 3.000000e+01 | 3.700000e+01 | 4.600000e+01 | 3.400000e+01 | 2.500000e+01 | 2.300000e+01 | 7.900000e+01 | 8.300000e+01 | 8.400000e+01 | 5.500000e+01 | 3.400000e+01 | 2.300000e+01 | 2.400000e+01 | 5.400000e+01 | 8.900000e+01 | 8.200000e+01 | 7.800000e+01 | 7.900000e+01 | 8.000000e+01 | 8.200000e+01 | 8.200000e+01 | 3.500000e+01 | 4.600000e+01 | 3.200000e+01 | 4.000000e+01 | 5.100000e+01 | 4.100000e+01 | 3.200000e+01 | 3.700000e+01 | 1.991000e+03 | 1.921000e+03 | 1.902000e+03 | None | None | 1.541000e+03 | 1.333000e+03 | 1.070000e+03 | None | None | None | None | None | 1.760000e+02 | 2.530000e+02 | 9.700000e+01 | 3.820000e+02 | 2.000000e+00 | 0.000000 | 7.200000e+01 | 3.820000e+02 | 1.866000e+03 | 0.000000e+00 | 0.000000 | 1.600000e+01 | 1.300000e+01 | 2.300000e+01 | 1.300000e+01 | 1.470000e+02 | 1.500000e+02 | 2.385100e+04 | 1.119800e+04 | 7.000000e+01 | 5.600000e+01 | 5.400000e+01 | 5.200000e+01 | 4.900000e+01 | 5.000000e+01 | 4.600000e+01 | 4.500000e+01 | 4.100000e+01 | 7.000000e+01 | 9.100000e+01 | 1.210000e+02 | 9.400000e+01 | 6.400000e+01 | 6.700000e+01 | 5.200000e+01 | 1.937000e+03 | 3.930000e+02 | 0.060900 | 7.960000e+02 | 3.630000e+02 | 8.760000e+04 | 1.120000e+05 | 1.376000e+05 | 7.160000e+02 | 3.610000e+02 | 1.240000e+02 | 3.100000e+01 | 1.500000e+01 | 7.260000e+02 | 5.500000e+01 | 4.100000e+01 | 5.900000e+01 | 6.000000e+01 | 4.300000e+01 | 2.700000e+01 | 2.000000e+01 | 2.700000e+01 | 0.000000e+00 | 2.100000e+01 | 7.200000e+01 | 2.200000e+01 | 4.320000e+02 | 2.820000e+02 | 5.140000e+02 | 1.480000e+02 | 0.000000 | 0.000000 | 5.110000e+02 | 1.600000e+02 | 3.600000e+02 | 7.200000e+00 | 3.200000e+01 | 9.700000e+01 | 3.800000e+01 | 3.200000e+01 | 3.700000e+01 | 4.600000e+01 | 4.900000e+01 | 4.700000e+01 | 3.400000e+01 | 1.700000e+01 | 6.090000e+02 | 0.000000e+00 | 4.050000e+02 | 2.430000e+02 | 1.600000e+02 | 1.720000e+02 | 1.270000e+02 | 7.900000e+01 | 5.400000e+01 | 0.000000 | 0.000000 | 7.700000e+01 | 1.900000e+01 | 1.700000e+01 | 1.470000e+02 | 1.570000e+02 | 1.710000e+02 | 1.730000e+02 | 8.500000e+01 | 1.660000e+02 | 9.100000e+01 | 1.070000e+02 | 1.030000e+02 | 9.420000e+02 | 3.400000e+01 | 6.400000e+01 | 4.100000e+01 | 8.000000e+01 | 2.780000e+02 | 3.350000e+02 | 1.550000e+02 | 7.800000e+01 | 2.720000e+04 | 3.400000e+01 | 2.000000e+01 | 9.300000e+02 | 1.090000e+02 | 0.000000e+00 | 8.570000e+02 | 2.000000e+01 | 1.430000e+02 | 3.590000e+02 | 3.860000e+02 | 1.090000e+02 | 1.540000e+02 | 2.160000e+02 | 2.240000e+02 | 4.500000e+02 | 3.550000e+02 | 4.630000e+02 | 2.140000e+02 | 4.450000e+02 | 3.100000e+01 | 6.800000e+01 | 4.100000e+01 | 1.900000e+01 | 3.200000e+01 | 1.050000e+02 | 6.800000e+01 | 2.660000e+02 | 1.013000e+03 | 8.500000e+01 | 1.074000e+03 | 5.790000e+02 | 1.000000e+03 | 0.000000e+00 | 1.065000e+03 | 1.700000e+01 | 1.120000e+02 | 8.100000e+01 | 2.530000e+02 | 8.400000e+01 | 3.000000e+01 | 1.390000e+02 | 6.100000e+01 | 5.800000e+01 | 1.270000e+02 | 1.390000e+02 | 6.400000e+01 | 4.000000e+01 | 4.570000e+02 | 1.180000e+02 | 1.570000e+02 | 2.580000e+02 | 1.880000e+02 | 4.570000e+02 | 2.580000e+02 | 1.270000e+02 | 1.290000e+02 | 1.340000e+02 | 5.600000e+02 | 1.280000e+02 | None | None | None |
sample_ds.geom_coverage()