Data
Coronavirus-News-(COVID-19)

Coronavirus-News-(COVID-19)

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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Context The World Health Organization (WHO) declared the 201920 coronavirus outbreak a pandemic and a Public Health Emergency of International Concern (PHEIC). Evidence of local transmission of the disease has been found in many countries across all six WHO regions. Content Coronaviruses are a large family of viruses that are known to cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). A novel coronavirus (COVID-19) was identified in 2019 in Wuhan, China. This is a new coronavirus that has not been previously identified in humans, and has since spread globally, resulting in the 201920 coronavirus pandemic. Acknowledgements I'd like to express my gratitude to my instructional team (Essra Madi, Markus Lim, Fahad Alsharekh and Bilal Yousef) for all of there efforts. Inspiration I hope this data will help the data scientist to get an insight about spreading the (COVID-19) around the world.

7 features

Unnamed:_0numeric1010 unique values
0 missing
Unnamed:_0.1numeric1010 unique values
0 missing
datestring41 unique values
0 missing
titlestring954 unique values
0 missing
categorystring52 unique values
0 missing
bodystring941 unique values
1 missing
sourcestring149 unique values
7 missing

19 properties

1010
Number of instances (rows) of the dataset.
7
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
8
Number of missing values in the dataset.
7
Number of instances with at least one value missing.
2
Number of numeric attributes.
0
Number of nominal attributes.
0.01
Number of attributes divided by the number of instances.
28.57
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.
0.69
Percentage of instances having missing values.
Average class difference between consecutive instances.
0.11
Percentage of missing values.

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