Understanding Covid19 Impact

Analysis has been done on the covid data which has been collected through scraping API's of this covid website which contains day-to-day information about number of Confirmed,recovered,deceased cases and all other sorts of Information related to the country India.

Scraping Data

• Scraping has been done using Scrapy library which provides tons of ways to extract the data out from the website. Data has been scraped using this link which returns a json object having everyday statistics of confirmed,recoverd, vaccinated and deceased cases for a single state. The above link belongs to Delhi.

• Fields captured:

  • Confirmed
  • recovered
  • deceased
  • tested
  • vaccinated
  • population
  • state
  • date

  This data has been scraped for every single day for every state.

• json response file has also been added for clear understanding of the response structure.

• Attached numbers.py file has comments added for better clarity of the process and can be found in the directory as follows:

  • covid
    • covid
      • spiders
        • numbers.py

Note : The above scraped data can be directly downloaded from the above mentioned Covid Website.

Running Python Script

1. Conda/pip install scrapy version listed in the requirements.txt and all the other dependencies to avoid problems while running.
2. Now, move folder covid to your local machine.
3. Activate the environment then move into covid folder from your terminal/cmd.
4. Type scrapy crawl numbers.py -o covid.csv in your terminal
5. This will generate a csv file named covid in your main folder.

Covid Data Analysis

This analysis project presents detailed analysis on the scraped covid19 data. This project project deals with missing values if any, analyses relationship between the features through plots, treats anamoly in the data when found , inspects current active cases and testing number by states and much more. Extra fields have been calculated for eg .fatality ratio, percentage population affected etc to see at what extent the lives of people from every state has been impacted by corona virus. Recovery rate of the country and impact of vaccination on active cases has also been studied. Pandas has been used for data manipulation where Seaborn and matplotlib is used for plots. Please see covid.ipynb for more details and plots on the covid data.