A History of the Now: Charles Baudelaire and Virginia Woolf

In this essay I compare the use of memory and history in works by Charles Baudelaire and Virginia Woolf, mainly focusing on Le Spleen de Paris and To The Lighthouse. I argue that they use these concepts in different manners, namely Baudelaire reflects on his observations in ‘the now’, while Woolf reflects on the events that shaped us and our continuous journey of reconciling the past with the now. Continue reading A History of the Now: Charles Baudelaire and Virginia Woolf

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Data Science in Python: Energy Supply and GDP

Assignment three of Introduction to Data Science in Python (University of Michigan) involves working with multiple datasets and combining the data that they contain. Continue reading Data Science in Python: Energy Supply and GDP

Charting in Python: Misleading Visuals

The very first assignment for the University of Michigan course Applied Plotting, Charting & Data Representation in Python is to find a graphic that poorly represents the data it is meant to visualise, and is therefore misleading to the audience of whichever medium it is a part. Continue reading Charting in Python: Misleading Visuals

Stats & Game of Thrones: Episode Transcripts (Season 1)

A while ago, I set out to do a text analysis of Game of Thrones episode transcripts. Unfortunately, these scripts are not easy to find; for a text analysis to make any sense at all I need character names to go with lines in the scripts.  Continue reading Stats & Game of Thrones: Episode Transcripts (Season 1)

Data Science in Python: Olympic Gold

The first assignment for the University of Michigan course ‘Introduction to Data Science in Python’ on Coursera requires some basic data cleaning, and analysis using Pandas. Continue reading Data Science in Python: Olympic Gold

Charting in Python: Weather Data

This post explores weather data – more specifically, daily maximum and minimum temperatures – for the Netherlands between 2005 and 2015, as part of Assignment II in the Coursera course ‘Applied Plotting, Charting & Data Representation in Python’ by the University of Michigan. Continue reading Charting in Python: Weather Data

Stats & IMDb: Machine Learning and Movie Recommendations – Part I

I have been using IMDb as a tracking tool for movies. I rate movies I watched, and I use IMDb’s average member rating, and metascores (critics rating) in determining what else I’d like to see. However, these ratings often deviate from my own scores. In preparation for a machine learning course, I am using this mismatch to set up a new project; the objective is to make better predictions and give more accurate movie recommendations. Continue reading Stats & IMDb: Machine Learning and Movie Recommendations – Part I

Policy and Party Coalitions in American Government

The nature of each party’s coalition explains each party’s lawmakers’ positions on policy issues, through lawmakers’ need for voter support (party alignment) and financial donations. Therefore, they are likely to vote on policy issues in such a way that benefits from that policy are concentrated among their constituents and benefactors and costs are dispersed among a broad base. Continue reading Policy and Party Coalitions in American Government