Data
Coronavirus-Disease-(COVID-19)

Coronavirus-Disease-(COVID-19)

active ARFF Database: Open Database, Contents: Original Authors Visibility: public Uploaded 23-03-2022 by Dustin Carrion
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Context Since awareness on COVID-19 began growing across the world, more health datasets have been published as open for (re-)users to utilise in creating platforms and interactive maps, for example, to support citizens in taking steps to stay healthy, like avoiding risk areas . This dataset is intended to mobilize researchers to apply recent advances in natural language processing to generate new insights in support of the fight against this infectious disease. Acknowledgements Source of data: ourworldindata

32 features

iso_codestring211 unique values
64 missing
locationstring212 unique values
0 missing
datestring153 unique values
0 missing
total_casesnumeric5785 unique values
0 missing
new_casesnumeric1891 unique values
0 missing
total_deathsnumeric1979 unique values
0 missing
new_deathsnumeric596 unique values
0 missing
total_cases_per_millionnumeric11580 unique values
385 missing
new_cases_per_millionnumeric6689 unique values
385 missing
total_deaths_per_millionnumeric5282 unique values
385 missing
new_deaths_per_millionnumeric1717 unique values
385 missing
total_testsnumeric5388 unique values
15345 missing
new_testsnumeric3612 unique values
15940 missing
total_tests_per_thousandnumeric4130 unique values
15345 missing
new_tests_per_thousandnumeric1339 unique values
15940 missing
new_tests_smoothednumeric4153 unique values
14838 missing
new_tests_smoothed_per_thousandnumeric1399 unique values
14838 missing
tests_unitsstring5 unique values
14240 missing
stringency_indexnumeric157 unique values
4543 missing
populationnumeric211 unique values
64 missing
population_densitynumeric199 unique values
934 missing
median_agenumeric133 unique values
1911 missing
aged_65_oldernumeric183 unique values
2169 missing
aged_70_oldernumeric182 unique values
2007 missing
gdp_per_capitanumeric183 unique values
2178 missing
extreme_povertynumeric73 unique values
8509 missing
cvd_death_ratenumeric186 unique values
1992 missing
diabetes_prevalencenumeric141 unique values
1293 missing
female_smokersnumeric107 unique values
5543 missing
male_smokersnumeric122 unique values
5711 missing
handwashing_facilitiesnumeric92 unique values
12657 missing
hospital_beds_per_100knumeric100 unique values
3482 missing

19 properties

20976
Number of instances (rows) of the dataset.
32
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
161083
Number of missing values in the dataset.
19860
Number of instances with at least one value missing.
28
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
87.5
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.
94.68
Percentage of instances having missing values.
Average class difference between consecutive instances.
24
Percentage of missing values.

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