During this lockdown, Data Scientists jumped into visualising the COVID19 situation from various datasets uploaded on Kaggle, so I decided to follow the bandwagon. Rather than taking data from around the world, I specified my analysis to India, as I would be able to relate the results to what I see around me.

Using the COVID-19 dataset from Kaggle and plotly, here is my visualisation.

The dataset contains 7 files, of which I used the following:

• Age Group Details
• COVID-19 in Details

Apart from that, I used the most recent data uploaded on Ministry of Health and Family Welfare (23.06.2020) for the State-wise count.

ag= pd.read_csv('AgeGroupDetails.csv')
sw = pd.read_csv("23.csv")
sw_date = pd.read_csv("covid_19_india.csv")

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Confirmed, Recovered and Deceased Cases Recorded Over Time

The first positive case of the virus in India was recorded on January 30th 2020, almost a month after the news broke out on the spread of the pandemic in China. The patient had a history of travel from Wuhan, which can be noticed in the screenshot below.

sw_date = pd.read_csv("covid_19_india.csv")
sw_date.head()

Using the same csv file, I dropped the unwanted columns and combined the results for each diagnosed date.

#data-science #covid19 #python #data-visualization #india