Dataset: World COVID-19 Data

About this Dataset

World COVID-19 Data

The Johns Hopkins University Center for Systems Science and Engineering (CSSE) maintains the COVID-19 Data Repository, which is updated daily (JHU). Every day at 6 AM UTC, the data is updated, which is immediately after the raw JHU data.

It is available in raw form like files with the prefix RAW and in a convenient form the files prefixed with CONVENIENT).

The data consists of:

Country-level confirmed cases and fatalities
By US county, confirmed cases and fatalities
Some metadata that is present in the unprocessed JHU data.

The RAW version is provided exactly as it was in the initial dataset.

Analyzing the CONVENIENT version should be simpler. Instead of by row, the data is grouped by column. The metadata is extracted and placed in a different file. Additionally, it switched from cumulative totals to daily change.

You can discuss any problems you notice with the data in this thread of discussion. I'll try to address the topics that received the most votes.

Please post your requests for modifying or enhancing this data in this discussion thread. I'll try once more to respond to the requests with the most votes.

I have a notebook that refreshes immediately upon each data dump update, providing a quick summary of the most recent data. If you want to see how to read the CONVENIENT data into a pandas data frame, it's also a helpful resource.

Tables

Continents2

@kaggle.abhishek14398_world_covid19_data.continents2

19.22 KB
249 rows
12 columns


CREATE TABLE continents2 (
  "unnamed_0" BIGINT,
  "name" VARCHAR,
  "alpha_2" VARCHAR,
  "alpha_3" VARCHAR,
  "country_code" BIGINT,
  "iso_3166_2" VARCHAR,
  "region" VARCHAR,
  "sub_region" VARCHAR,
  "intermediate_region" VARCHAR,
  "region_code" DOUBLE,
  "sub_region_code" DOUBLE,
  "intermediate_region_code" DOUBLE
);

Convenient Global Confirmed Cases

@kaggle.abhishek14398_world_covid19_data.convenient_global_confirmed_cases

870.68 KB
1087 rows
290 columns


CREATE TABLE convenient_global_confirmed_cases (
  "country_region" VARCHAR,
  "afghanistan" DOUBLE,
  "albania" DOUBLE,
  "algeria" DOUBLE,
  "andorra" DOUBLE,
  "angola" DOUBLE,
  "antarctica" DOUBLE,
  "antigua_and_barbuda" DOUBLE,
  "argentina" DOUBLE,
  "armenia" DOUBLE,
  "australia" VARCHAR,
  "australia_1" VARCHAR,
  "australia_2" VARCHAR,
  "australia_3" VARCHAR,
  "australia_4" VARCHAR,
  "australia_5" VARCHAR,
  "australia_6" VARCHAR,
  "australia_7" VARCHAR,
  "austria" DOUBLE,
  "azerbaijan" DOUBLE,
  "bahamas" DOUBLE,
  "bahrain" DOUBLE,
  "bangladesh" DOUBLE,
  "barbados" DOUBLE,
  "belarus" DOUBLE,
  "belgium" DOUBLE,
  "belize" DOUBLE,
  "benin" DOUBLE,
  "bhutan" DOUBLE,
  "bolivia" DOUBLE,
  "bosnia_and_herzegovina" DOUBLE,
  "botswana" DOUBLE,
  "brazil" DOUBLE,
  "brunei" DOUBLE,
  "bulgaria" DOUBLE,
  "burkina_faso" DOUBLE,
  "burma" DOUBLE,
  "burundi" DOUBLE,
  "cabo_verde" DOUBLE,
  "cambodia" DOUBLE,
  "cameroon" DOUBLE,
  "canada" VARCHAR,
  "canada_1" VARCHAR,
  "canada_2" VARCHAR,
  "canada_3" VARCHAR,
  "canada_4" VARCHAR,
  "canada_5" VARCHAR,
  "canada_6" VARCHAR,
  "canada_7" VARCHAR,
  "canada_8" VARCHAR,
  "canada_9" VARCHAR,
  "canada_10" VARCHAR,
  "canada_11" VARCHAR,
  "canada_12" VARCHAR,
  "canada_13" VARCHAR,
  "canada_14" VARCHAR,
  "canada_15" VARCHAR,
  "central_african_republic" DOUBLE,
  "chad" DOUBLE,
  "chile" DOUBLE,
  "china" VARCHAR,
  "china_1" VARCHAR,
  "china_2" VARCHAR,
  "china_3" VARCHAR,
  "china_4" VARCHAR,
  "china_5" VARCHAR,
  "china_6" VARCHAR,
  "china_7" VARCHAR,
  "china_8" VARCHAR,
  "china_9" VARCHAR,
  "china_10" VARCHAR,
  "china_11" VARCHAR,
  "china_12" VARCHAR,
  "china_13" VARCHAR,
  "china_14" VARCHAR,
  "china_15" VARCHAR,
  "china_16" VARCHAR,
  "china_17" VARCHAR,
  "china_18" VARCHAR,
  "china_19" VARCHAR,
  "china_20" VARCHAR,
  "china_21" VARCHAR,
  "china_22" VARCHAR,
  "china_23" VARCHAR,
  "china_24" VARCHAR,
  "china_25" VARCHAR,
  "china_26" VARCHAR,
  "china_27" VARCHAR,
  "china_28" VARCHAR,
  "china_29" VARCHAR,
  "china_30" VARCHAR,
  "china_31" VARCHAR,
  "china_32" VARCHAR,
  "china_33" VARCHAR,
  "colombia" DOUBLE,
  "comoros" DOUBLE,
  "congo_brazzaville" DOUBLE,
  "congo_kinshasa" DOUBLE,
  "costa_rica" DOUBLE,
  "cote_d_ivoire" DOUBLE
);

Convenient Global Deaths

@kaggle.abhishek14398_world_covid19_data.convenient_global_deaths

386.31 KB
1087 rows
290 columns


CREATE TABLE convenient_global_deaths (
  "country_region" VARCHAR,
  "afghanistan" DOUBLE,
  "albania" DOUBLE,
  "algeria" DOUBLE,
  "andorra" DOUBLE,
  "angola" DOUBLE,
  "antarctica" DOUBLE,
  "antigua_and_barbuda" DOUBLE,
  "argentina" DOUBLE,
  "armenia" DOUBLE,
  "australia" VARCHAR,
  "australia_1" VARCHAR,
  "australia_2" VARCHAR,
  "australia_3" VARCHAR,
  "australia_4" VARCHAR,
  "australia_5" VARCHAR,
  "australia_6" VARCHAR,
  "australia_7" VARCHAR,
  "austria" DOUBLE,
  "azerbaijan" DOUBLE,
  "bahamas" DOUBLE,
  "bahrain" DOUBLE,
  "bangladesh" DOUBLE,
  "barbados" DOUBLE,
  "belarus" DOUBLE,
  "belgium" DOUBLE,
  "belize" DOUBLE,
  "benin" DOUBLE,
  "bhutan" DOUBLE,
  "bolivia" DOUBLE,
  "bosnia_and_herzegovina" DOUBLE,
  "botswana" DOUBLE,
  "brazil" DOUBLE,
  "brunei" DOUBLE,
  "bulgaria" DOUBLE,
  "burkina_faso" DOUBLE,
  "burma" DOUBLE,
  "burundi" DOUBLE,
  "cabo_verde" DOUBLE,
  "cambodia" DOUBLE,
  "cameroon" DOUBLE,
  "canada" VARCHAR,
  "canada_1" VARCHAR,
  "canada_2" VARCHAR,
  "canada_3" VARCHAR,
  "canada_4" VARCHAR,
  "canada_5" VARCHAR,
  "canada_6" VARCHAR,
  "canada_7" VARCHAR,
  "canada_8" VARCHAR,
  "canada_9" VARCHAR,
  "canada_10" VARCHAR,
  "canada_11" VARCHAR,
  "canada_12" VARCHAR,
  "canada_13" VARCHAR,
  "canada_14" VARCHAR,
  "canada_15" VARCHAR,
  "central_african_republic" DOUBLE,
  "chad" DOUBLE,
  "chile" DOUBLE,
  "china" VARCHAR,
  "china_1" VARCHAR,
  "china_2" VARCHAR,
  "china_3" VARCHAR,
  "china_4" VARCHAR,
  "china_5" VARCHAR,
  "china_6" VARCHAR,
  "china_7" VARCHAR,
  "china_8" VARCHAR,
  "china_9" VARCHAR,
  "china_10" VARCHAR,
  "china_11" VARCHAR,
  "china_12" VARCHAR,
  "china_13" VARCHAR,
  "china_14" VARCHAR,
  "china_15" VARCHAR,
  "china_16" VARCHAR,
  "china_17" VARCHAR,
  "china_18" VARCHAR,
  "china_19" VARCHAR,
  "china_20" VARCHAR,
  "china_21" VARCHAR,
  "china_22" VARCHAR,
  "china_23" VARCHAR,
  "china_24" VARCHAR,
  "china_25" VARCHAR,
  "china_26" VARCHAR,
  "china_27" VARCHAR,
  "china_28" VARCHAR,
  "china_29" VARCHAR,
  "china_30" VARCHAR,
  "china_31" VARCHAR,
  "china_32" VARCHAR,
  "china_33" VARCHAR,
  "colombia" DOUBLE,
  "comoros" DOUBLE,
  "congo_brazzaville" DOUBLE,
  "congo_kinshasa" DOUBLE,
  "costa_rica" DOUBLE,
  "cote_d_ivoire" DOUBLE
);

Convenient Global Metadata

@kaggle.abhishek14398_world_covid19_data.convenient_global_metadata

13.95 KB
289 rows
5 columns


CREATE TABLE convenient_global_metadata (
  "unnamed_0" BIGINT,
  "country_region" VARCHAR,
  "province_state" VARCHAR,
  "lat" DOUBLE,
  "long" DOUBLE
);

Convenient Us Confirmed Cases

@kaggle.abhishek14398_world_covid19_data.convenient_us_confirmed_cases

6.9 MB
1087 rows
3343 columns


CREATE TABLE convenient_us_confirmed_cases (
  "province_state" VARCHAR,
  "alabama" VARCHAR,
  "alabama_1" VARCHAR,
  "alabama_2" VARCHAR,
  "alabama_3" VARCHAR,
  "alabama_4" VARCHAR,
  "alabama_5" VARCHAR,
  "alabama_6" VARCHAR,
  "alabama_7" VARCHAR,
  "alabama_8" VARCHAR,
  "alabama_9" VARCHAR,
  "alabama_10" VARCHAR,
  "alabama_11" VARCHAR,
  "alabama_12" VARCHAR,
  "alabama_13" VARCHAR,
  "alabama_14" VARCHAR,
  "alabama_15" VARCHAR,
  "alabama_16" VARCHAR,
  "alabama_17" VARCHAR,
  "alabama_18" VARCHAR,
  "alabama_19" VARCHAR,
  "alabama_20" VARCHAR,
  "alabama_21" VARCHAR,
  "alabama_22" VARCHAR,
  "alabama_23" VARCHAR,
  "alabama_24" VARCHAR,
  "alabama_25" VARCHAR,
  "alabama_26" VARCHAR,
  "alabama_27" VARCHAR,
  "alabama_28" VARCHAR,
  "alabama_29" VARCHAR,
  "alabama_30" VARCHAR,
  "alabama_31" VARCHAR,
  "alabama_32" VARCHAR,
  "alabama_33" VARCHAR,
  "alabama_34" VARCHAR,
  "alabama_35" VARCHAR,
  "alabama_36" VARCHAR,
  "alabama_37" VARCHAR,
  "alabama_38" VARCHAR,
  "alabama_39" VARCHAR,
  "alabama_40" VARCHAR,
  "alabama_41" VARCHAR,
  "alabama_42" VARCHAR,
  "alabama_43" VARCHAR,
  "alabama_44" VARCHAR,
  "alabama_45" VARCHAR,
  "alabama_46" VARCHAR,
  "alabama_47" VARCHAR,
  "alabama_48" VARCHAR,
  "alabama_49" VARCHAR,
  "alabama_50" VARCHAR,
  "alabama_51" VARCHAR,
  "alabama_52" VARCHAR,
  "alabama_53" VARCHAR,
  "alabama_54" VARCHAR,
  "alabama_55" VARCHAR,
  "alabama_56" VARCHAR,
  "alabama_57" VARCHAR,
  "alabama_58" VARCHAR,
  "alabama_59" VARCHAR,
  "alabama_60" VARCHAR,
  "alabama_61" VARCHAR,
  "alabama_62" VARCHAR,
  "alabama_63" VARCHAR,
  "alabama_64" VARCHAR,
  "alabama_65" VARCHAR,
  "alabama_66" VARCHAR,
  "alabama_67" VARCHAR,
  "alabama_68" VARCHAR,
  "alaska" VARCHAR,
  "alaska_1" VARCHAR,
  "alaska_2" VARCHAR,
  "alaska_3" VARCHAR,
  "alaska_4" VARCHAR,
  "alaska_5" VARCHAR,
  "alaska_6" VARCHAR,
  "alaska_7" VARCHAR,
  "alaska_8" VARCHAR,
  "alaska_9" VARCHAR,
  "alaska_10" VARCHAR,
  "alaska_11" VARCHAR,
  "alaska_12" VARCHAR,
  "alaska_13" VARCHAR,
  "alaska_14" VARCHAR,
  "alaska_15" VARCHAR,
  "alaska_16" VARCHAR,
  "alaska_17" VARCHAR,
  "alaska_18" VARCHAR,
  "alaska_19" VARCHAR,
  "alaska_20" VARCHAR,
  "alaska_21" VARCHAR,
  "alaska_22" VARCHAR,
  "alaska_23" VARCHAR,
  "alaska_24" VARCHAR,
  "alaska_25" VARCHAR,
  "alaska_26" VARCHAR,
  "alaska_27" VARCHAR,
  "alaska_28" VARCHAR,
  "alaska_29" VARCHAR
);

Convenient Us Deaths

@kaggle.abhishek14398_world_covid19_data.convenient_us_deaths

3.62 MB
1087 rows
3343 columns


CREATE TABLE convenient_us_deaths (
  "province_state" VARCHAR,
  "alabama" VARCHAR,
  "alabama_1" VARCHAR,
  "alabama_2" VARCHAR,
  "alabama_3" VARCHAR,
  "alabama_4" VARCHAR,
  "alabama_5" VARCHAR,
  "alabama_6" VARCHAR,
  "alabama_7" VARCHAR,
  "alabama_8" VARCHAR,
  "alabama_9" VARCHAR,
  "alabama_10" VARCHAR,
  "alabama_11" VARCHAR,
  "alabama_12" VARCHAR,
  "alabama_13" VARCHAR,
  "alabama_14" VARCHAR,
  "alabama_15" VARCHAR,
  "alabama_16" VARCHAR,
  "alabama_17" VARCHAR,
  "alabama_18" VARCHAR,
  "alabama_19" VARCHAR,
  "alabama_20" VARCHAR,
  "alabama_21" VARCHAR,
  "alabama_22" VARCHAR,
  "alabama_23" VARCHAR,
  "alabama_24" VARCHAR,
  "alabama_25" VARCHAR,
  "alabama_26" VARCHAR,
  "alabama_27" VARCHAR,
  "alabama_28" VARCHAR,
  "alabama_29" VARCHAR,
  "alabama_30" VARCHAR,
  "alabama_31" VARCHAR,
  "alabama_32" VARCHAR,
  "alabama_33" VARCHAR,
  "alabama_34" VARCHAR,
  "alabama_35" VARCHAR,
  "alabama_36" VARCHAR,
  "alabama_37" VARCHAR,
  "alabama_38" VARCHAR,
  "alabama_39" VARCHAR,
  "alabama_40" VARCHAR,
  "alabama_41" VARCHAR,
  "alabama_42" VARCHAR,
  "alabama_43" VARCHAR,
  "alabama_44" VARCHAR,
  "alabama_45" VARCHAR,
  "alabama_46" VARCHAR,
  "alabama_47" VARCHAR,
  "alabama_48" VARCHAR,
  "alabama_49" VARCHAR,
  "alabama_50" VARCHAR,
  "alabama_51" VARCHAR,
  "alabama_52" VARCHAR,
  "alabama_53" VARCHAR,
  "alabama_54" VARCHAR,
  "alabama_55" VARCHAR,
  "alabama_56" VARCHAR,
  "alabama_57" VARCHAR,
  "alabama_58" VARCHAR,
  "alabama_59" VARCHAR,
  "alabama_60" VARCHAR,
  "alabama_61" VARCHAR,
  "alabama_62" VARCHAR,
  "alabama_63" VARCHAR,
  "alabama_64" VARCHAR,
  "alabama_65" VARCHAR,
  "alabama_66" VARCHAR,
  "alabama_67" VARCHAR,
  "alabama_68" VARCHAR,
  "alaska" VARCHAR,
  "alaska_1" VARCHAR,
  "alaska_2" VARCHAR,
  "alaska_3" VARCHAR,
  "alaska_4" VARCHAR,
  "alaska_5" VARCHAR,
  "alaska_6" VARCHAR,
  "alaska_7" VARCHAR,
  "alaska_8" VARCHAR,
  "alaska_9" VARCHAR,
  "alaska_10" VARCHAR,
  "alaska_11" VARCHAR,
  "alaska_12" VARCHAR,
  "alaska_13" VARCHAR,
  "alaska_14" VARCHAR,
  "alaska_15" VARCHAR,
  "alaska_16" VARCHAR,
  "alaska_17" VARCHAR,
  "alaska_18" VARCHAR,
  "alaska_19" VARCHAR,
  "alaska_20" VARCHAR,
  "alaska_21" VARCHAR,
  "alaska_22" VARCHAR,
  "alaska_23" VARCHAR,
  "alaska_24" VARCHAR,
  "alaska_25" VARCHAR,
  "alaska_26" VARCHAR,
  "alaska_27" VARCHAR,
  "alaska_28" VARCHAR,
  "alaska_29" VARCHAR
);

Convenient Us Metadata

@kaggle.abhishek14398_world_covid19_data.convenient_us_metadata

123.41 KB
3342 rows
6 columns


CREATE TABLE convenient_us_metadata (
  "unnamed_0" BIGINT,
  "province_state" VARCHAR,
  "admin2" VARCHAR,
  "population" BIGINT,
  "lat" DOUBLE,
  "long" DOUBLE
);

Raw Global Confirmed Cases

@kaggle.abhishek14398_world_covid19_data.raw_global_confirmed_cases

2.36 MB
289 rows
1091 columns


CREATE TABLE raw_global_confirmed_cases (
  "country_region" VARCHAR,
  "province_state" VARCHAR,
  "lat" DOUBLE,
  "long" DOUBLE,
  "n_1_22_20" BIGINT,
  "n_1_23_20" BIGINT,
  "n_1_24_20" BIGINT,
  "n_1_25_20" BIGINT,
  "n_1_26_20" BIGINT,
  "n_1_27_20" BIGINT,
  "n_1_28_20" BIGINT,
  "n_1_29_20" BIGINT,
  "n_1_30_20" BIGINT,
  "n_1_31_20" BIGINT,
  "n_2_1_20" BIGINT,
  "n_2_2_20" BIGINT,
  "n_2_3_20" BIGINT,
  "n_2_4_20" BIGINT,
  "n_2_5_20" BIGINT,
  "n_2_6_20" BIGINT,
  "n_2_7_20" BIGINT,
  "n_2_8_20" BIGINT,
  "n_2_9_20" BIGINT,
  "n_2_10_20" BIGINT,
  "n_2_11_20" BIGINT,
  "n_2_12_20" BIGINT,
  "n_2_13_20" BIGINT,
  "n_2_14_20" BIGINT,
  "n_2_15_20" BIGINT,
  "n_2_16_20" BIGINT,
  "n_2_17_20" BIGINT,
  "n_2_18_20" BIGINT,
  "n_2_19_20" BIGINT,
  "n_2_20_20" BIGINT,
  "n_2_21_20" BIGINT,
  "n_2_22_20" BIGINT,
  "n_2_23_20" BIGINT,
  "n_2_24_20" BIGINT,
  "n_2_25_20" BIGINT,
  "n_2_26_20" BIGINT,
  "n_2_27_20" BIGINT,
  "n_2_28_20" BIGINT,
  "n_2_29_20" BIGINT,
  "n_3_1_20" BIGINT,
  "n_3_2_20" BIGINT,
  "n_3_3_20" BIGINT,
  "n_3_4_20" BIGINT,
  "n_3_5_20" BIGINT,
  "n_3_6_20" BIGINT,
  "n_3_7_20" BIGINT,
  "n_3_8_20" BIGINT,
  "n_3_9_20" BIGINT,
  "n_3_10_20" BIGINT,
  "n_3_11_20" BIGINT,
  "n_3_12_20" BIGINT,
  "n_3_13_20" BIGINT,
  "n_3_14_20" BIGINT,
  "n_3_15_20" BIGINT,
  "n_3_16_20" BIGINT,
  "n_3_17_20" BIGINT,
  "n_3_18_20" BIGINT,
  "n_3_19_20" BIGINT,
  "n_3_20_20" BIGINT,
  "n_3_21_20" BIGINT,
  "n_3_22_20" BIGINT,
  "n_3_23_20" BIGINT,
  "n_3_24_20" BIGINT,
  "n_3_25_20" BIGINT,
  "n_3_26_20" BIGINT,
  "n_3_27_20" BIGINT,
  "n_3_28_20" BIGINT,
  "n_3_29_20" BIGINT,
  "n_3_30_20" BIGINT,
  "n_3_31_20" BIGINT,
  "n_4_1_20" BIGINT,
  "n_4_2_20" BIGINT,
  "n_4_3_20" BIGINT,
  "n_4_4_20" BIGINT,
  "n_4_5_20" BIGINT,
  "n_4_6_20" BIGINT,
  "n_4_7_20" BIGINT,
  "n_4_8_20" BIGINT,
  "n_4_9_20" BIGINT,
  "n_4_10_20" BIGINT,
  "n_4_11_20" BIGINT,
  "n_4_12_20" BIGINT,
  "n_4_13_20" BIGINT,
  "n_4_14_20" BIGINT,
  "n_4_15_20" BIGINT,
  "n_4_16_20" BIGINT,
  "n_4_17_20" BIGINT,
  "n_4_18_20" BIGINT,
  "n_4_19_20" BIGINT,
  "n_4_20_20" BIGINT,
  "n_4_21_20" BIGINT,
  "n_4_22_20" BIGINT,
  "n_4_23_20" BIGINT,
  "n_4_24_20" BIGINT,
  "n_4_25_20" BIGINT,
  "n_4_26_20" BIGINT
);

Raw Global Deaths

@kaggle.abhishek14398_world_covid19_data.raw_global_deaths

1.87 MB
289 rows
1091 columns


CREATE TABLE raw_global_deaths (
  "country_region" VARCHAR,
  "province_state" VARCHAR,
  "lat" DOUBLE,
  "long" DOUBLE,
  "n_1_22_20" BIGINT,
  "n_1_23_20" BIGINT,
  "n_1_24_20" BIGINT,
  "n_1_25_20" BIGINT,
  "n_1_26_20" BIGINT,
  "n_1_27_20" BIGINT,
  "n_1_28_20" BIGINT,
  "n_1_29_20" BIGINT,
  "n_1_30_20" BIGINT,
  "n_1_31_20" BIGINT,
  "n_2_1_20" BIGINT,
  "n_2_2_20" BIGINT,
  "n_2_3_20" BIGINT,
  "n_2_4_20" BIGINT,
  "n_2_5_20" BIGINT,
  "n_2_6_20" BIGINT,
  "n_2_7_20" BIGINT,
  "n_2_8_20" BIGINT,
  "n_2_9_20" BIGINT,
  "n_2_10_20" BIGINT,
  "n_2_11_20" BIGINT,
  "n_2_12_20" BIGINT,
  "n_2_13_20" BIGINT,
  "n_2_14_20" BIGINT,
  "n_2_15_20" BIGINT,
  "n_2_16_20" BIGINT,
  "n_2_17_20" BIGINT,
  "n_2_18_20" BIGINT,
  "n_2_19_20" BIGINT,
  "n_2_20_20" BIGINT,
  "n_2_21_20" BIGINT,
  "n_2_22_20" BIGINT,
  "n_2_23_20" BIGINT,
  "n_2_24_20" BIGINT,
  "n_2_25_20" BIGINT,
  "n_2_26_20" BIGINT,
  "n_2_27_20" BIGINT,
  "n_2_28_20" BIGINT,
  "n_2_29_20" BIGINT,
  "n_3_1_20" BIGINT,
  "n_3_2_20" BIGINT,
  "n_3_3_20" BIGINT,
  "n_3_4_20" BIGINT,
  "n_3_5_20" BIGINT,
  "n_3_6_20" BIGINT,
  "n_3_7_20" BIGINT,
  "n_3_8_20" BIGINT,
  "n_3_9_20" BIGINT,
  "n_3_10_20" BIGINT,
  "n_3_11_20" BIGINT,
  "n_3_12_20" BIGINT,
  "n_3_13_20" BIGINT,
  "n_3_14_20" BIGINT,
  "n_3_15_20" BIGINT,
  "n_3_16_20" BIGINT,
  "n_3_17_20" BIGINT,
  "n_3_18_20" BIGINT,
  "n_3_19_20" BIGINT,
  "n_3_20_20" BIGINT,
  "n_3_21_20" BIGINT,
  "n_3_22_20" BIGINT,
  "n_3_23_20" BIGINT,
  "n_3_24_20" BIGINT,
  "n_3_25_20" BIGINT,
  "n_3_26_20" BIGINT,
  "n_3_27_20" BIGINT,
  "n_3_28_20" BIGINT,
  "n_3_29_20" BIGINT,
  "n_3_30_20" BIGINT,
  "n_3_31_20" BIGINT,
  "n_4_1_20" BIGINT,
  "n_4_2_20" BIGINT,
  "n_4_3_20" BIGINT,
  "n_4_4_20" BIGINT,
  "n_4_5_20" BIGINT,
  "n_4_6_20" BIGINT,
  "n_4_7_20" BIGINT,
  "n_4_8_20" BIGINT,
  "n_4_9_20" BIGINT,
  "n_4_10_20" BIGINT,
  "n_4_11_20" BIGINT,
  "n_4_12_20" BIGINT,
  "n_4_13_20" BIGINT,
  "n_4_14_20" BIGINT,
  "n_4_15_20" BIGINT,
  "n_4_16_20" BIGINT,
  "n_4_17_20" BIGINT,
  "n_4_18_20" BIGINT,
  "n_4_19_20" BIGINT,
  "n_4_20_20" BIGINT,
  "n_4_21_20" BIGINT,
  "n_4_22_20" BIGINT,
  "n_4_23_20" BIGINT,
  "n_4_24_20" BIGINT,
  "n_4_25_20" BIGINT,
  "n_4_26_20" BIGINT
);

Raw Us Confirmed Cases

@kaggle.abhishek14398_world_covid19_data.raw_us_confirmed_cases

15.81 MB
3342 rows
1098 columns


CREATE TABLE raw_us_confirmed_cases (
  "province_state" VARCHAR,
  "admin2" VARCHAR,
  "uid" BIGINT,
  "iso2" VARCHAR,
  "iso3" VARCHAR,
  "code3" BIGINT,
  "fips" DOUBLE,
  "country_region" VARCHAR,
  "lat" DOUBLE,
  "long" DOUBLE,
  "combined_key" VARCHAR,
  "n_1_22_20" BIGINT,
  "n_1_23_20" BIGINT,
  "n_1_24_20" BIGINT,
  "n_1_25_20" BIGINT,
  "n_1_26_20" BIGINT,
  "n_1_27_20" BIGINT,
  "n_1_28_20" BIGINT,
  "n_1_29_20" BIGINT,
  "n_1_30_20" BIGINT,
  "n_1_31_20" BIGINT,
  "n_2_1_20" BIGINT,
  "n_2_2_20" BIGINT,
  "n_2_3_20" BIGINT,
  "n_2_4_20" BIGINT,
  "n_2_5_20" BIGINT,
  "n_2_6_20" BIGINT,
  "n_2_7_20" BIGINT,
  "n_2_8_20" BIGINT,
  "n_2_9_20" BIGINT,
  "n_2_10_20" BIGINT,
  "n_2_11_20" BIGINT,
  "n_2_12_20" BIGINT,
  "n_2_13_20" BIGINT,
  "n_2_14_20" BIGINT,
  "n_2_15_20" BIGINT,
  "n_2_16_20" BIGINT,
  "n_2_17_20" BIGINT,
  "n_2_18_20" BIGINT,
  "n_2_19_20" BIGINT,
  "n_2_20_20" BIGINT,
  "n_2_21_20" BIGINT,
  "n_2_22_20" BIGINT,
  "n_2_23_20" BIGINT,
  "n_2_24_20" BIGINT,
  "n_2_25_20" BIGINT,
  "n_2_26_20" BIGINT,
  "n_2_27_20" BIGINT,
  "n_2_28_20" BIGINT,
  "n_2_29_20" BIGINT,
  "n_3_1_20" BIGINT,
  "n_3_2_20" BIGINT,
  "n_3_3_20" BIGINT,
  "n_3_4_20" BIGINT,
  "n_3_5_20" BIGINT,
  "n_3_6_20" BIGINT,
  "n_3_7_20" BIGINT,
  "n_3_8_20" BIGINT,
  "n_3_9_20" BIGINT,
  "n_3_10_20" BIGINT,
  "n_3_11_20" BIGINT,
  "n_3_12_20" BIGINT,
  "n_3_13_20" BIGINT,
  "n_3_14_20" BIGINT,
  "n_3_15_20" BIGINT,
  "n_3_16_20" BIGINT,
  "n_3_17_20" BIGINT,
  "n_3_18_20" BIGINT,
  "n_3_19_20" BIGINT,
  "n_3_20_20" BIGINT,
  "n_3_21_20" BIGINT,
  "n_3_22_20" BIGINT,
  "n_3_23_20" BIGINT,
  "n_3_24_20" BIGINT,
  "n_3_25_20" BIGINT,
  "n_3_26_20" BIGINT,
  "n_3_27_20" BIGINT,
  "n_3_28_20" BIGINT,
  "n_3_29_20" BIGINT,
  "n_3_30_20" BIGINT,
  "n_3_31_20" BIGINT,
  "n_4_1_20" BIGINT,
  "n_4_2_20" BIGINT,
  "n_4_3_20" BIGINT,
  "n_4_4_20" BIGINT,
  "n_4_5_20" BIGINT,
  "n_4_6_20" BIGINT,
  "n_4_7_20" BIGINT,
  "n_4_8_20" BIGINT,
  "n_4_9_20" BIGINT,
  "n_4_10_20" BIGINT,
  "n_4_11_20" BIGINT,
  "n_4_12_20" BIGINT,
  "n_4_13_20" BIGINT,
  "n_4_14_20" BIGINT,
  "n_4_15_20" BIGINT,
  "n_4_16_20" BIGINT,
  "n_4_17_20" BIGINT,
  "n_4_18_20" BIGINT,
  "n_4_19_20" BIGINT
);

Raw Us Deaths

@kaggle.abhishek14398_world_covid19_data.raw_us_deaths

6.87 MB
3342 rows
1099 columns


CREATE TABLE raw_us_deaths (
  "province_state" VARCHAR,
  "admin2" VARCHAR,
  "uid" BIGINT,
  "iso2" VARCHAR,
  "iso3" VARCHAR,
  "code3" BIGINT,
  "fips" DOUBLE,
  "country_region" VARCHAR,
  "lat" DOUBLE,
  "long" DOUBLE,
  "combined_key" VARCHAR,
  "population" BIGINT,
  "n_1_22_20" BIGINT,
  "n_1_23_20" BIGINT,
  "n_1_24_20" BIGINT,
  "n_1_25_20" BIGINT,
  "n_1_26_20" BIGINT,
  "n_1_27_20" BIGINT,
  "n_1_28_20" BIGINT,
  "n_1_29_20" BIGINT,
  "n_1_30_20" BIGINT,
  "n_1_31_20" BIGINT,
  "n_2_1_20" BIGINT,
  "n_2_2_20" BIGINT,
  "n_2_3_20" BIGINT,
  "n_2_4_20" BIGINT,
  "n_2_5_20" BIGINT,
  "n_2_6_20" BIGINT,
  "n_2_7_20" BIGINT,
  "n_2_8_20" BIGINT,
  "n_2_9_20" BIGINT,
  "n_2_10_20" BIGINT,
  "n_2_11_20" BIGINT,
  "n_2_12_20" BIGINT,
  "n_2_13_20" BIGINT,
  "n_2_14_20" BIGINT,
  "n_2_15_20" BIGINT,
  "n_2_16_20" BIGINT,
  "n_2_17_20" BIGINT,
  "n_2_18_20" BIGINT,
  "n_2_19_20" BIGINT,
  "n_2_20_20" BIGINT,
  "n_2_21_20" BIGINT,
  "n_2_22_20" BIGINT,
  "n_2_23_20" BIGINT,
  "n_2_24_20" BIGINT,
  "n_2_25_20" BIGINT,
  "n_2_26_20" BIGINT,
  "n_2_27_20" BIGINT,
  "n_2_28_20" BIGINT,
  "n_2_29_20" BIGINT,
  "n_3_1_20" BIGINT,
  "n_3_2_20" BIGINT,
  "n_3_3_20" BIGINT,
  "n_3_4_20" BIGINT,
  "n_3_5_20" BIGINT,
  "n_3_6_20" BIGINT,
  "n_3_7_20" BIGINT,
  "n_3_8_20" BIGINT,
  "n_3_9_20" BIGINT,
  "n_3_10_20" BIGINT,
  "n_3_11_20" BIGINT,
  "n_3_12_20" BIGINT,
  "n_3_13_20" BIGINT,
  "n_3_14_20" BIGINT,
  "n_3_15_20" BIGINT,
  "n_3_16_20" BIGINT,
  "n_3_17_20" BIGINT,
  "n_3_18_20" BIGINT,
  "n_3_19_20" BIGINT,
  "n_3_20_20" BIGINT,
  "n_3_21_20" BIGINT,
  "n_3_22_20" BIGINT,
  "n_3_23_20" BIGINT,
  "n_3_24_20" BIGINT,
  "n_3_25_20" BIGINT,
  "n_3_26_20" BIGINT,
  "n_3_27_20" BIGINT,
  "n_3_28_20" BIGINT,
  "n_3_29_20" BIGINT,
  "n_3_30_20" BIGINT,
  "n_3_31_20" BIGINT,
  "n_4_1_20" BIGINT,
  "n_4_2_20" BIGINT,
  "n_4_3_20" BIGINT,
  "n_4_4_20" BIGINT,
  "n_4_5_20" BIGINT,
  "n_4_6_20" BIGINT,
  "n_4_7_20" BIGINT,
  "n_4_8_20" BIGINT,
  "n_4_9_20" BIGINT,
  "n_4_10_20" BIGINT,
  "n_4_11_20" BIGINT,
  "n_4_12_20" BIGINT,
  "n_4_13_20" BIGINT,
  "n_4_14_20" BIGINT,
  "n_4_15_20" BIGINT,
  "n_4_16_20" BIGINT,
  "n_4_17_20" BIGINT,
  "n_4_18_20" BIGINT
);