Applied Plotting, Charting & Data Representation in Python

Part of an assignment for a Coursera introductory data science course

Scraped the data from the Irish Census Archives: http://www.census.nationalarchives.ie/pages/1911/ (happy with myself for that, wasn't able to code anything a few months ago)

Used Python, Pandas, Matplotlib

Different Protestant denominations were bundled together.

I thought it was really interesting that in spite of these factors varying hugely from county to county, the comparison locally of Catholic to Protestant was very consistent.

Also interesting was that while Dublin had the lowest illiteracy rates, it had among the highest child mortality rate! This trend was also reflected in other counties with higher urban populations such as Antrim and Cork.

It reminds of this course. They have taken a chart from there. I’m guessing OP recently completed the course and liked it

It was the final assignment in this course.

https://www.coursera.org/learn/python-plotting

After spending the first 3 weeks learning how to use matplotlib, we were directed to come up with our own research question and answer it using publicly available datasets.

We spent a lot of time talking about normal distributions. I thought I'd show some examples where distribution is very skewed.

Inequality in many domains, most notably in the distribution of wealth and resources, is a frequent subject of discussion around the world. Most often, inequality is attributed to social, political and economic systems that are not set up to distribute resources and rewards in an equitable manner. Based on, what appears to me, a superficial understanding of the phenomenon, various social and economic strategies are proposed to redistribute resources and rewards equitably. Generally it is attributed to western society and capitalism.

I wanted to show how the problem of 'inequality' is deeper than we tend to think.