Exploratory Data Analysis in R: US presidential campaign donations 2016
The 2016 election victory of Donald Trump shook many people’s beliefs about US democracy. The media commonly portrayed this upset as a popular revolt by disadvantaged voters against a liberal political elite. But is this narrative backed up by data such as election campaign finance donations? Who financed this popular revolt?
I used a data set of campaign donations published by the US Federal Election Commission
to explore and visualise trends of the primary as well as general election compaign donations.
Exploratory data analysis in Python: Missed hospital appointments
Health care systems are both expensive to run and extremely valuable for patients. So why do so many patients miss their medical appointments?
I tried to gain some preliminary insights into factors associated with no-shows using a dataset of 110k hospital appointments in Brazil. It collects information about both appointments and patient characteristics in 14 variables.
Data visualisation: P2P lending and the credit crunch
Peer-to-peer lending is an alternative finance facility that developed from the mid-noughties. How is it used by lenders, and does it help them deal with financial issues they face?
To look into this topic, I used visualisation in Tableau of large data set of loans from the P2P lending company Prosper.
My particular interest was how the period of the 2008 financial crisis shaped P2P lending, and how lenders used this banking alternative.
The credit crunch posed additional economic hurdles for lenders shut out from the traditional financial institutions - was there evidence that it enabled them to successfully overcome these?
How did the changing regulatory framework affect how P2P lending worked?
Wrangling and analysis of social media data in Python: can dogs pics be engaging too?
WeRateDogs is a Twitter account that rates people’s dogs with a humorous comment about the dog. This project is all about wrangling and analysing data related to WeRateDogs.
