Category: IronPython

Two Data Sources: Exchanging One for Another

Sometimes data doesn’t come in the format we wish it would. I found myself in such a situation when I was working on a data set for a template that explores Olympic history.

Specifically, I was working with data on murdered Olympians. I had the name of the athlete, their gender, their country, their sport, and the notes on their death. Frustratingly though, the country came in the form of the ioc country code. I knew that meant it would be a pain to create a relation from this data to all the other data I had brought in for my Olympic analysis. And besides, ioc codes are not intuitive to read.

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Parsing Text: Numerical Data from Historical Accounts

In a recent article on Data Shop Talk, I introduced an interesting set of analyses on Olympic data. One of the analyses focused on Olympians who had died or gone missing due to war. The data from Sports-Reference.com came in a csv file format with the following information: Athlete, Gender, Country, Sport, and Notes. This was a great start to my analysis but there was something critical missing in order to properly illustrate the timeline of deaths: the date of death.

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