Data
COVID-19-community-mobility-reports

COVID-19-community-mobility-reports

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Dustin Carrion
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  • Computer Systems Machine Learning
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The pandemic context brings new challenges to cities. This fantastic resource was created by Google with aggregated, anonymized sets of data from users who have turned on the Location History setting on Android. It captures the changes in mobility between baseline values (median value from the 5week period Jan 3 Feb 6, 2020) at weekly intervals data from February to October 2020. Data include changes in mobility related to workplace, residential, transit hubs, parks, retail and grocery. It covers 593 cities in 43 countries. See https://ourworldindata.org/covid-mobility-trends

14 features

country_region_codestring43 unique values
0 missing
country_regionstring43 unique values
0 missing
sub_region_1string593 unique values
11033 missing
sub_region_2string4465 unique values
148180 missing
metro_areastring3 unique values
1047894 missing
iso_3166_2_codestring789 unique values
864417 missing
census_fips_codenumeric0 unique values
1048575 missing
datestring242 unique values
0 missing
retail_and_recreation_percent_change_from_baselinenumeric288 unique values
426419 missing
grocery_and_pharmacy_percent_change_from_baselinenumeric320 unique values
437675 missing
parks_percent_change_from_baselinenumeric780 unique values
476386 missing
transit_stations_percent_change_from_baselinenumeric372 unique values
551496 missing
workplaces_percent_change_from_baselinenumeric191 unique values
75278 missing
residential_percent_change_from_baselinenumeric80 unique values
486336 missing

19 properties

1048575
Number of instances (rows) of the dataset.
14
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
5573689
Number of missing values in the dataset.
1048575
Number of instances with at least one value missing.
7
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
50
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
100
Percentage of instances having missing values.
Average class difference between consecutive instances.
37.97
Percentage of missing values.

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