EDIT: Apparently, some of the prices in the .csv files I used were missing, and this caused some problems with pandas dataframe since it replaces missing values with ‘na’. Should you encounter the same problem you could check every line with an if statement or use a method to replace the na. You can check the pandas’ documentation here.
Yesterday I was really bored and had some time which could be put to good use, therefore I decided to write a quick script to plot percentage change of currencies of some countries and compare them. The code I ended up with is a bit sloppy I guess, but that’s fine since I was primarily interested in improving my (limited, as of now) use of pandas and having fun.
First of all I gathered data from Quandl, namely the prices of the selected currencies in terms of dollars, that’s to say the value per day of every selected currency with respect to the dollar:
XYZ/USD (daily)
Gathering data from Quandl is really easy and fast using the Quandl API for Python. By the way, an API for R is available too.
I then computed the percentage change for 2 years and defined some plotting functions. Here is the main result the plotting function produces given a reference currency: it plots the percentage change for every currency (with respect to the dollar) against the percentage change of the reference currency. Some of the plotted data looks definitely weird, I wonder if I did something wrong or lost some information during the process.
Here is the code I used:
Disclaimer
This article is for educational purpose only. The author is not responsible for any consequence or loss due to inappropriate use. The article may well contain mistakes and errors. The data used might not be accurate. You should never use this article for purposes different from the educational one.
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