Name: South African COVID-19 Provincial Data
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

South African COVID-19 Provincial Data

Timeline of Confirmed Cases, Deaths, Recoveries and Testing Rates

By [source]

About this dataset

This dataset provides a detailed look into the ongoing COVID-19 pandemic in South Africa. It contains data on the number of confirmed cases, deaths, recoveries, and testing rates at both a provincial and national level. With this data set, users are able to gain insight into the current state and trends of the pandemic in South Africa. This provides essential information necessary to help fight the epidemic and make informed decisions surrounding its prevention. Using this set as a resource will allow users to monitor how this devastating virus has impacted communities, plans for containment and treatment strategies all while taking into account cultural, socioeconomic factors that can influence these metrics. This dataset is an invaluable tool for understanding not only South Africa’s specific current challenge with COVID-19 but is relevant on a global scale whenit comes to fighting back against this virus that continues to wreak havoc aroundthe worldl

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How to use the dataset

How to use This Dataset

This Kaggle dataset provides an overview of the South African COVID-19 pandemic situation. It contains data regarding the number of confirmed cases, deaths, recoveries, and testing rates for each province at both the provincial and national level. In order to understand this dataset effectively, it is important to know what each column represents in this dataset. The following is a description of all column names that are included:

Column Names

EC: Number of confirmed cases in Eastern Cape province

FS: Number of confirmed cases in Free State province

GP: Number of confirmed cases in Gauteng province

KZN: Number of confirmed cases in KwaZulu Natal province

LP: Number of confirmed cases in Limpopo province

MP: Number of confirmed cases in Mpumalanga Province

NC: Number total number orconfirmed casews in Northern Cape Province

NW :Number total numberurceof confirmes ed cacasesin North WestProvince

WC :Number totaconsfirme dcasescinWestern CapProvincee

UNKNOWN :Number totalnumberorconfirmesdacsesinsUnknown locations

Total :Totalnumberofconfrmecase sacrosseSouthAfrica

Source :Sourecodataset fedzile_Dbi ejweleputswaMangaungXharie thabo_MofutsanyanaRecoveriesDeathsYYMMDD

Research Ideas

Creating an interactive map to show the spread of COVID-19 over time, with up date information about confirmed cases, deaths, recoveries and testing rates for each province or district.

Constructing a machine learning model to predict the likely number of future cases in each province based on previous data activities.

Comparing different districts and provinces within South Africa and drawing out trends among them with comparative graphical representations or independent analyses

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: covid19za_provincial_cumulative_timeline_recoveries.csv

Column name	Description
date	Date of the data entry. (Date)
YYYYMMDD	Date in YYYYMMDD format. (String)
EC	Number of confirmed cases in Eastern Cape Province. (Integer)
FS	Number of confirmed cases in Free State Province. (Integer)
GP	Number of confirmed cases in Gauteng Province. (Integer)
KZN	Number of confirmed cases in Kwazulu Natal Province. (Integer)
LP	Number of confirmed cases in Limpopo Province. (Integer)
MP	Number of confirmed cases in Mpumalanga Province. (Integer)
NC	Number of confirmed cases in Northern Cape Province. (Integer)
NW	Number of confirmed cases in North West Province. (Integer)
WC	Number of confirmed cases in Western Cape Province. (Integer)
UNKNOWN	Number of confirmed cases in unknown locations. (Integer)
total	Total number of confirmed cases in South Africa. (Integer)
source	Source of the data. (String)

File: provincial_fs_cumulative.csv

Column name	Description
date	Date of the data entry. (Date)
YYYYMMDD	Date in YYYYMMDD format. (String)
total	Total number of confirmed cases in South Africa. (Integer)
source	Source of the data. (String)
fezile_dabi	Number of confirmed cases in the Fezile Dabi district. (Integer)
lejweleputswa	Number of confirmed cases in the Lejweleputswa district. (Integer)
mangaung	Number of confirmed cases in the Mangaung district. (Integer)
xhariep	Number of confirmed cases in the Xhariep district. (Integer)
thabo_mofutsanyana	Number of confirmed cases in the Thabo Mofutsanyana district. (Integer)
Recoveries	Number of recoveries in South Africa. (Integer)
Deaths	Number of deaths in South Africa. (Integer)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Covid19za Provincial Cumulative Timeline Confirmed

@kaggle.thedevastator_south_african_covid_19_provincial_data.covid19za_provincial_cumulative_timeline_confirmed

18.87 kB
125 rows
14 columns

CREATE TABLE covid19za_provincial_cumulative_timeline_confirmed (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "ec" DOUBLE,
  "fs" DOUBLE,
  "gp" DOUBLE,
  "kzn" DOUBLE,
  "lp" DOUBLE,
  "mp" DOUBLE,
  "nc" DOUBLE,
  "nw" DOUBLE,
  "wc" DOUBLE,
  "unknown" DOUBLE,
  "total" BIGINT,
  "source" VARCHAR
);

Covid19za Provincial Cumulative Timeline Deaths

@kaggle.thedevastator_south_african_covid_19_provincial_data.covid19za_provincial_cumulative_timeline_deaths

14.81 kB
101 rows
14 columns

CREATE TABLE covid19za_provincial_cumulative_timeline_deaths (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "ec" BIGINT,
  "fs" BIGINT,
  "gp" BIGINT,
  "kzn" BIGINT,
  "lp" BIGINT,
  "mp" BIGINT,
  "nc" BIGINT,
  "nw" BIGINT,
  "wc" BIGINT,
  "unknown" BIGINT,
  "total" BIGINT,
  "source" VARCHAR
);

Covid19za Provincial Cumulative Timeline Recoveries

@kaggle.thedevastator_south_african_covid_19_provincial_data.covid19za_provincial_cumulative_timeline_recoveries

14.87 kB
78 rows
14 columns

CREATE TABLE covid19za_provincial_cumulative_timeline_recoveries (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "ec" BIGINT,
  "fs" BIGINT,
  "gp" BIGINT,
  "kzn" BIGINT,
  "lp" BIGINT,
  "mp" BIGINT,
  "nc" BIGINT,
  "nw" BIGINT,
  "wc" BIGINT,
  "unknown" BIGINT,
  "total" BIGINT,
  "source" VARCHAR
);

Covid19za Provincial Cumulative Timeline Testing

@kaggle.thedevastator_south_african_covid_19_provincial_data.covid19za_provincial_cumulative_timeline_testing

10.38 kB
6 rows
14 columns

CREATE TABLE covid19za_provincial_cumulative_timeline_testing (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "ec" BIGINT,
  "fs" BIGINT,
  "gp" BIGINT,
  "kzn" BIGINT,
  "lp" BIGINT,
  "mp" BIGINT,
  "nc" BIGINT,
  "nw" BIGINT,
  "wc" BIGINT,
  "unknown" BIGINT,
  "total" BIGINT,
  "source" VARCHAR
);

Covid19za Timeline Confirmed

@kaggle.thedevastator_south_african_covid_19_provincial_data.covid19za_timeline_confirmed

13.6 kB
709 rows
10 columns

CREATE TABLE covid19za_timeline_confirmed (
  "case_id" BIGINT,
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "country" VARCHAR,
  "province" VARCHAR,
  "geo_subdivision" VARCHAR,
  "age" DOUBLE,
  "gender" VARCHAR,
  "transmission_type" VARCHAR,
  "type" VARCHAR
);

Covid19za Timeline Deaths

@kaggle.thedevastator_south_african_covid_19_provincial_data.covid19za_timeline_deaths

11.59 kB
103 rows
11 columns

CREATE TABLE covid19za_timeline_deaths (
  "report_id" BIGINT,
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "province" VARCHAR,
  "geo" VARCHAR,
  "gender" VARCHAR,
  "age" DOUBLE,
  "confirmed_date" VARCHAR,
  "transmission_type" VARCHAR,
  "notes_comorbidity" VARCHAR,
  "source" VARCHAR
);

Covid19za Timeline Testing

@kaggle.thedevastator_south_african_covid_19_provincial_data.covid19za_timeline_testing

15.91 kB
132 rows
14 columns

CREATE TABLE covid19za_timeline_testing (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "cumulative_tests" DOUBLE,
  "recovered" BIGINT,
  "hospitalisation" DOUBLE,
  "critical_icu" DOUBLE,
  "ventilation" DOUBLE,
  "deaths" BIGINT,
  "contacts_identified" DOUBLE,
  "contacts_traced" DOUBLE,
  "scanned_travellers" DOUBLE,
  "passengers_elevated_temperature" DOUBLE,
  "covid_suspected_criteria" DOUBLE,
  "source" VARCHAR
);

Covid19za Timeline Transmission Type

@kaggle.thedevastator_south_african_covid_19_provincial_data.covid19za_timeline_transmission_type

9.86 kB
709 rows
5 columns

CREATE TABLE covid19za_timeline_transmission_type (
  "case_id" BIGINT,
  "transmission_type" VARCHAR,
  "type" VARCHAR,
  "countries" VARCHAR,
  "unnamed_4" VARCHAR  -- Unnamed: 4
);

Nicd Daily National Report

@kaggle.thedevastator_south_african_covid_19_provincial_data.nicd_daily_national_report

11.59 kB
48 rows
10 columns

CREATE TABLE nicd_daily_national_report (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "male_total_cases" BIGINT,
  "female_total_cases" BIGINT,
  "unknown_sex_total_cases" BIGINT,
  "testing_passive" BIGINT,
  "testing_community_screening" BIGINT,
  "testing_public" BIGINT,
  "testing_private" BIGINT,
  "source" VARCHAR
);

Nicd Hospital Surveillance Data

@kaggle.thedevastator_south_african_covid_19_provincial_data.nicd_hospital_surveillance_data

12.82 kB
39 rows
12 columns

CREATE TABLE nicd_hospital_surveillance_data (
  "date" VARCHAR,
  "n__yyyymmdd" BIGINT  -- YYYYMMDD,
  "n__total_admissions" BIGINT  -- Total Admissions,
  "n__current_num_in_hospital" BIGINT  -- Current Num In Hospital,
  "n__general" BIGINT  -- General,
  "n__high_care" BIGINT  -- High Care,
  "n__icu" BIGINT  -- ICU,
  "n__isolation" BIGINT  -- Isolation,
  "n__total_healthcare_workers_admitted" BIGINT  -- Total Healthcare Workers Admitted,
  "n__num_discharged_alive" BIGINT  -- Num Discharged Alive,
  "n__hospital_deaths" BIGINT  -- Hospital Deaths,
  "n__source" VARCHAR  -- Source
);

Provincial Ec Cumulative

@kaggle.thedevastator_south_african_covid_19_provincial_data.provincial_ec_cumulative

10.74 kB
12 rows
13 columns

CREATE TABLE provincial_ec_cumulative (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "alfred_nzo" BIGINT,
  "amathole" BIGINT,
  "buffalo_city_metro" BIGINT,
  "chris_hani" BIGINT,
  "joe_gqabi" BIGINT,
  "nelson_mandele_metro" BIGINT,
  "or_tambo" BIGINT,
  "sarah_baartman_district" BIGINT,
  "unknown" BIGINT,
  "total" BIGINT,
  "source" VARCHAR
);

Provincial Fs Cumulative

@kaggle.thedevastator_south_african_covid_19_provincial_data.provincial_fs_cumulative

9.45 kB
22 rows
11 columns

CREATE TABLE provincial_fs_cumulative (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "fezile_dabi" BIGINT,
  "lejweleputswa" BIGINT,
  "mangaung" BIGINT,
  "xhariep" BIGINT,
  "thabo_mofutsanyana" BIGINT,
  "total" BIGINT,
  "recoveries" BIGINT,
  "deaths" BIGINT,
  "source" VARCHAR
);

Provincial Gp Cumulative

@kaggle.thedevastator_south_african_covid_19_provincial_data.provincial_gp_cumulative

16.41 kB
89 rows
12 columns

CREATE TABLE provincial_gp_cumulative (
  "date" VARCHAR,
  "yyyymmdd" DOUBLE,
  "ekurhuleni_cases" DOUBLE,
  "johannesburg_cases" DOUBLE,
  "sedibeng_cases" DOUBLE,
  "tshwane_cases" DOUBLE,
  "west_rand_cases" DOUBLE,
  "gp_unallocated_cases" DOUBLE,
  "gp_cases" BIGINT,
  "gp_recoveries" DOUBLE,
  "gp_hospitalisations" DOUBLE,
  "source" VARCHAR
);

Provincial Lp Cumulative

@kaggle.thedevastator_south_african_covid_19_provincial_data.provincial_lp_cumulative

32.82 kB
69 rows
36 columns

CREATE TABLE provincial_lp_cumulative (
  "date" TIMESTAMP,
  "yyyymmdd" BIGINT,
  "dc35" BIGINT,
  "lim354" DOUBLE,
  "lim351" DOUBLE,
  "lim353" DOUBLE,
  "lim355" DOUBLE,
  "dc34" BIGINT,
  "lim341" DOUBLE,
  "lim344" DOUBLE,
  "lim343" DOUBLE,
  "lim345" DOUBLE,
  "dc33" BIGINT,
  "lim334" DOUBLE,
  "lim331" DOUBLE,
  "lim332" DOUBLE,
  "lim333" DOUBLE,
  "lim335" DOUBLE,
  "dc47" DOUBLE,
  "lim472" DOUBLE,
  "lim471" DOUBLE,
  "lim476" DOUBLE,
  "lim473" DOUBLE,
  "dc36" BIGINT,
  "lim366" DOUBLE,
  "lim362" DOUBLE,
  "lim368" DOUBLE,
  "lim367" DOUBLE,
  "lim361" DOUBLE,
  "unknown" DOUBLE,
  "total" BIGINT,
  "recoveries" DOUBLE,
  "deaths" DOUBLE,
  "active" DOUBLE,
  "tests" DOUBLE,
  "source" VARCHAR
);

Provincial Mp Cumulative

@kaggle.thedevastator_south_african_covid_19_provincial_data.provincial_mp_cumulative

22.29 kB
124 rows
24 columns

CREATE TABLE provincial_mp_cumulative (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "bushbuckridge" DOUBLE,
  "mbombela" DOUBLE,
  "nkomazi" DOUBLE,
  "thaba_chweu" DOUBLE,
  "albert_luthuli" DOUBLE,
  "dipaliseng" DOUBLE,
  "pixley_ka_seme" DOUBLE,
  "govan_mbeki" DOUBLE,
  "lekwa" DOUBLE,
  "mkhondo" DOUBLE,
  "msukaligwa" DOUBLE,
  "js_moroka" DOUBLE,
  "emakhazeni" DOUBLE,
  "emalahleni" DOUBLE,
  "steve_tshwete" DOUBLE,
  "thembisile_hani" DOUBLE,
  "victor_khanye" DOUBLE,
  "unknown" DOUBLE,
  "total" DOUBLE,
  "recoveries" DOUBLE,
  "deaths" DOUBLE,
  "sources" VARCHAR
);

Provincial Nc Cumulative

@kaggle.thedevastator_south_african_covid_19_provincial_data.provincial_nc_cumulative

14.22 kB
30 rows
17 columns

CREATE TABLE provincial_nc_cumulative (
  "date" TIMESTAMP,
  "francis_baard_cases" BIGINT,
  "namakwa_cases" BIGINT,
  "pixley_ka_seme_cases" BIGINT,
  "zf_mgcawu_cases" BIGINT,
  "john_taolo_gaetswe_cases" BIGINT,
  "francis_baard_deaths" BIGINT,
  "namakwa_deaths" BIGINT,
  "pixley_ka_seme_deaths" BIGINT,
  "zf_mgcawu_deaths" BIGINT,
  "john_taolo_gaetswe_deaths" BIGINT,
  "francis_baard_recoveries" DOUBLE,
  "namakwa_recoveries" BIGINT,
  "pixley_ka_seme_recoveries" DOUBLE,
  "zf_mgcawu_recoveries" DOUBLE,
  "john_taolo_gaetswe_recoveries" BIGINT,
  "source" VARCHAR
);

Provincial Nw Cumulative

@kaggle.thedevastator_south_african_covid_19_provincial_data.provincial_nw_cumulative

13.73 kB
84 rows
12 columns

CREATE TABLE provincial_nw_cumulative (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "dr_ruth_segomotsi_mompati" DOUBLE,
  "ngaka_modiri_molema" DOUBLE,
  "bojanala_platinum" DOUBLE,
  "dr_kenneth_kaunda" DOUBLE,
  "unallocated" DOUBLE,
  "total" BIGINT,
  "recovered" DOUBLE,
  "deaths" DOUBLE,
  "tested" DOUBLE,
  "source" VARCHAR
);

Provincial Wc Cumulative

@kaggle.thedevastator_south_african_covid_19_provincial_data.provincial_wc_cumulative

39 kB
93 rows
41 columns

CREATE TABLE provincial_wc_cumulative (
  "date" VARCHAR,
  "yyyymmdd" BIGINT,
  "ct" BIGINT,
  "ct_we" BIGINT,
  "ct_so" BIGINT,
  "ct_no" BIGINT,
  "ct_tb" BIGINT,
  "ct_ea" BIGINT,
  "ct_kf" BIGINT,
  "ct_mp" BIGINT,
  "ct_kl" BIGINT,
  "cw" BIGINT,
  "cw_bv" BIGINT,
  "cw_ds" BIGINT,
  "cw_lb" BIGINT,
  "cw_sb" BIGINT,
  "cw_wb" BIGINT,
  "ck" BIGINT,
  "ck_bw" BIGINT,
  "ck_lb" BIGINT,
  "ck_pa" BIGINT,
  "gr" BIGINT,
  "gr_bt" BIGINT,
  "gr_ge" BIGINT,
  "gr_hq" BIGINT,
  "gr_kl" BIGINT,
  "gr_kn" BIGINT,
  "gr_mb" BIGINT,
  "gr_os" BIGINT,
  "ob" BIGINT,
  "ob_ca" BIGINT,
  "ob_os" BIGINT,
  "ob_sd" BIGINT,
  "ob_tk" BIGINT,
  "wc" BIGINT,
  "wc_br" BIGINT,
  "wc_cb" BIGINT,
  "wc_mz" BIGINT,
  "wc_sb" BIGINT,
  "wc_sl" BIGINT,
  "unknown" BIGINT
);