About this Dataset

COVID-19 Community Mobility Dataset

The Dataset has been extracted from google https://www.google.com/covid19/mobility/ for 120+ countries and have been tried to look into deep inside the mobility data. This data may help to understand community mobility inpacts on infection rate both countrywise as well as worldwide. File:

community_dataset_with_infection_count.csv

Description of fields :

1.COUNTRY_REGION_CODE->ISO2 country code
2.COUNTRY_REGION->Country Name
3.DATE_VAL->Date
4.DAY_CT-> Day number starting from 15-Feb-2020
5.RETAIL_AND_RECREATION_PCT->Mobility trends for places like restaurants,
cafes, shopping centers, theme parks,
museums, libraries, and movie theaters.

6.INC_RETAIL_AND_RECREATION_PCT-Increase Mobility trends for places like restaurants,
cafes, shopping centers, theme parks,
museums, libraries, and movie theaters.

7.GROCERY_AND_PHARMACY_PCT->Mobility trends for places like grocery
markets, food warehouses, farmers
markets, specialty food shops, drug stores,
and pharmacies.

8.INC_GROCERY_AND_PHARMACY_PCT-> Increase Mobility trends for places like grocery
markets, food warehouses, farmers
markets, specialty food shops, drug stores,
and pharmacies.

9.PARKS_PCT->Mobility trends for places like national parks,
public beaches, marinas, dog parks, plazas,
and public gardens.

10.INC_PARKS_PCT-> Increase Mobility trends for places like national parks,
public beaches, marinas, dog parks, plazas,
and public gardens.

11.TRANSIT_STATIONS_PCT-> Mobility trends for places like public transport
hubs such as subway, bus, and train stations.

12.INC_TRANSIT_STATIONS_PCT-> Increase Mobility trends for places like public transport
hubs such as subway, bus, and train stations.

13.WORKPLACES_PCT-> Mobility trends for places of work
14.INC_WORKPLACES_PCT -> Increase Mobility trends for places of work
15.RESIDENTIAL_PCT -> Mobility trends for places of residence
16.INC_RESIDENTIAL_PCT -> Increase Mobility trends for places of residence
17.COVID_CONFIRMED -> Confirm Covid cases for that country.
18.COVID_RECOVERED -> Confirm Recover cases for that country.
19.COVID_DEATHS -> Confirm Death cases for that country.
20.COVID_CNTY_NEW_CASES -> New Covid cases for that country.
21.COVID_COUNTRY_INC_RATE -> Increase New Covid cases for that country.
22.COVID_WORLD_CONFIRMED --> Confirm Covid cases for that World.
23.COVID_WORLD_RECOVERED -> Confirm Recover cases for that World.
24.COVID_WORLD_DEATHS -> Confirm Death cases for that World.
25.COVID_WORLD_INC_RATE ->Confirm Increase cases for that world.

Tables

World Mobility With Covid Infection Count

@kaggle.arghadeep_covid19_community_mobility_dataset.world_mobility_with_covid_infection_count

163.19 KB
7068 rows
29 columns


CREATE TABLE world_mobility_with_covid_infection_count (
  "country_region_code" VARCHAR,
  "country_region" VARCHAR,
  "date_val" VARCHAR,
  "day_ct" BIGINT,
  "retail_and_recreation_pct" BIGINT,
  "inc_retail_and_recreation_pct" BIGINT,
  "grocery_and_pharmacy_pct" BIGINT,
  "inc_grocery_and_pharmacy_pct" BIGINT,
  "parks_pct" BIGINT,
  "inc_parks_pct" BIGINT,
  "transit_stations_pct" BIGINT,
  "inc_transit_stations_pct" BIGINT,
  "workplaces_pct" BIGINT,
  "inc_workplaces_pct" BIGINT,
  "residential_pct" BIGINT,
  "inc_residential_pct" BIGINT,
  "covid_confirmed" BIGINT,
  "covid_recovered" BIGINT,
  "covid_deaths" BIGINT,
  "covid_cnty_new_cases" DOUBLE,
  "covid_country_inc_rate" DOUBLE,
  "covid_country_recovr_inc_rate" DOUBLE,
  "covid_country_death_inc_rate" DOUBLE,
  "covid_world_confirmed" BIGINT,
  "covid_world_recovered" BIGINT,
  "covid_world_deaths" BIGINT,
  "covid_world_inc_rate" DOUBLE,
  "covid_world_recvr_inc_rate" DOUBLE,
  "covid_world_death_inc_rate" DOUBLE
);

Community Mobility Raw Dataset Google

@kaggle.arghadeep_covid19_community_mobility_dataset.community_mobility_raw_dataset_google

157.04 KB
10956 rows
5 columns


CREATE TABLE community_mobility_raw_dataset_google (
  "days" DOUBLE,
  "valus" DOUBLE,
  "params" VARCHAR,
  "countrycode" VARCHAR,
  "src" VARCHAR
);

Community Dataset With Infection Count

@kaggle.arghadeep_covid19_community_mobility_dataset.community_dataset_with_infection_count

149.31 KB
7068 rows
25 columns


CREATE TABLE community_dataset_with_infection_count (
  "country_region_code" VARCHAR,
  "country_region" VARCHAR,
  "date_val" VARCHAR,
  "day_ct" BIGINT,
  "retail_and_recreation_pct" BIGINT,
  "inc_retail_and_recreation_pct" BIGINT,
  "grocery_and_pharmacy_pct" BIGINT,
  "inc_grocery_and_pharmacy_pct" BIGINT,
  "parks_pct" BIGINT,
  "inc_parks_pct" BIGINT,
  "transit_stations_pct" BIGINT,
  "inc_transit_stations_pct" BIGINT,
  "workplaces_pct" BIGINT,
  "inc_workplaces_pct" BIGINT,
  "residential_pct" BIGINT,
  "inc_residential_pct" BIGINT,
  "covid_confirmed" BIGINT,
  "covid_recovered" BIGINT,
  "covid_deaths" BIGINT,
  "covid_cnty_new_cases" DOUBLE,
  "covid_country_inc_rate" DOUBLE,
  "covid_world_confirmed" BIGINT,
  "covid_world_recovered" BIGINT,
  "covid_world_deaths" BIGINT,
  "covid_world_inc_rate" DOUBLE
);