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https://github.com/reachsumit/population-density-india

The goal of this project is to calculate population weighted mean of geospatial coordinates of each Indian state and compare data from different decennial censuses.
https://github.com/reachsumit/population-density-india

jupyter-notebook map pandas python-3-6 scraping-websites shapely tableau-desktop

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The goal of this project is to calculate population weighted mean of geospatial coordinates of each Indian state and compare data from different decennial censuses.

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README

        

# Weighted Population density for Indian states

### Why this project ?
A few days ago, a reddit user posted a beautiful visualization for Mean Centers of U.S. population by state on /r/MapPorn subreddit.
![reddit /r/MapPorn post](https://cdn-images-1.medium.com/max/1000/1*hU3J73baFXc_ogL-rjhCTA.png)

Pretty neat, right ? This map conveys the point across and also maintains an appeasing simplicity. This inspired me to create a similar population map for my motherland, India.

But what I imagined to be a straightforward task, turned into something really complicated. While the original creator of the above reddit post was able to get the desired data in neatly arranged format from the US Census Bureau website, similar information wasn’t readily available for India. So, I set out to create my map from scratch.

### What does the code include ?
Python code that useds Pandas to manipulate web-scraped population data. Along with code to manipulate geospatial data to generate the desired results.

Read the complete project details here:
https://medium.com/@sam.sumitkumar/plotting-weighted-mean-population-centroids-on-a-country-map-22da408c1397

### Screenshots
Indian districts mapped as polygons
![Indian districts mapped as polygons](https://cdn-images-1.medium.com/max/1000/1*AtdiA7yDWs6a_yYk4ZcZlQ.png)

Mapping centroids for each district
![Indian districts mapped as polygons](https://cdn-images-1.medium.com/max/1000/1*viLwWvgk0PWIafUQSzLBqQ.png)

Mean centers of population by state, 2001 vs. 2011
![Output](https://cdn-images-1.medium.com/max/1000/1*f50rwoMlTzi7MlXqumvfGg.png)