Data
COVID-19-Indonesia-Dataset

COVID-19-Indonesia-Dataset

active ARFF CC BY-NC-SA 4.0 Visibility: public Uploaded 23-03-2022 by Onur Yildirim
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Context The COVID-19 dataset in Indonesia was created to find out various factors that could be taken into consideration in decision making related to the level of stringency in each province in Indonesia. Content Data compiled based on time series, both on a country level (Indonesia), and on a province level. If needed in certain provinces, it might also be provided at the city / regency level. Demographic data is also available, as well as calculations between demographic data and COVID-19 pandemic data. Acknowledgements Thank you to those who have provided data openly so that we can compile it into a dataset here, which is as follows: covid19.go.id, kemendagri.go.id, bps.go.id, and bnpb-inacovid19.hub.arcgis.com

38 features

Datestring643 unique values
0 missing
Location_ISO_Codestring35 unique values
0 missing
Locationstring35 unique values
0 missing
New_Casesnumeric2082 unique values
0 missing
New_Deathsnumeric393 unique values
0 missing
New_Recoverednumeric2035 unique values
0 missing
New_Active_Casesnumeric1958 unique values
0 missing
Total_Casesnumeric15265 unique values
0 missing
Total_Deathsnumeric4526 unique values
0 missing
Total_Recoverednumeric14152 unique values
0 missing
Total_Active_Casesnumeric7089 unique values
0 missing
Location_Levelstring2 unique values
0 missing
City_or_Regencynumeric0 unique values
21759 missing
Provincestring34 unique values
642 missing
Countrystring1 unique values
0 missing
Continentstring1 unique values
0 missing
Islandstring7 unique values
642 missing
Time_Zonestring3 unique values
642 missing
Special_Statusstring3 unique values
18636 missing
Total_Regenciesnumeric18 unique values
0 missing
Total_Citiesnumeric10 unique values
614 missing
Total_Districtsnumeric35 unique values
0 missing
Total_Urban_Villagesnumeric33 unique values
617 missing
Total_Rural_Villagesnumeric34 unique values
642 missing
Area_(km2)numeric35 unique values
0 missing
Populationnumeric35 unique values
0 missing
Population_Densitynumeric35 unique values
0 missing
Longitudenumeric35 unique values
0 missing
Latitudenumeric35 unique values
0 missing
New_Cases_per_Millionnumeric5712 unique values
0 missing
Total_Cases_per_Millionnumeric19157 unique values
0 missing
New_Deaths_per_Millionnumeric806 unique values
0 missing
Total_Deaths_per_Millionnumeric10361 unique values
0 missing
Total_Deaths_per_100rbnumeric4754 unique values
0 missing
Case_Fatality_Ratestring1316 unique values
0 missing
Case_Recovered_Ratestring6067 unique values
0 missing
Growth_Factor_of_New_Casesnumeric658 unique values
1187 missing
Growth_Factor_of_New_Deathsnumeric375 unique values
2467 missing

19 properties

21759
Number of instances (rows) of the dataset.
38
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
47848
Number of missing values in the dataset.
21759
Number of instances with at least one value missing.
26
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
68.42
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.
5.79
Percentage of missing values.

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