Repository for my work on Tableau and Power BI
- Taken from Kaggle.
- Transformed the dataset removing hundreds of columns, retaining the useful ones.
- Imported and Visualized on Power BI.
- The first page shows various information regarding each state and its districts. Information such as Area, Population, Sex Ratio, Literacy Rate, etc.
- We can deduce that the greater the population is higher are the chances of the region being an urban region.
- With better Sex Ratio and higher male to female literacy rates and overall literacy rate, urban regions are better than rural parts/districts.
- The second page divides the population even further to generate even more insights.
- Dividing the population further on the basis of religion and where they live with what amenities.
- The chart below the state figures shows the electricity and internet connectivity in each region with availability of computers at home.
- The viz also shows the urban/rural households in that region.
- Developed regions have better electricity connectivity with good internet reach and higher urban households.
- Total power parity for a region is also shown.
- Taken from World Bank
https://public.tableau.com/shared/SBY9ZZF52?:display_count=n&:origin=viz_share_link
- Taken from - https://ourworldindata.org/covid-deaths
- Seperated into two datasets using Excel
https://public.tableau.com/shared/3PR3GZD56?:display_count=n&:origin=viz_share_link