Python scripts for graphing historical real GDP data from the Maddison Project

Continuing on this, over the past couple weeks I’ve worked on two Python scripts: one to graph both the Maddison GDP series for each country one desires, and one to graph one GDP series for each country one desires as best reconciled by my judgment in the manner described (“first attempt”) at the bottom of the previous post re: the Maddison data. The latter is probably more useful, as there are fewer lines to pay attention to, but I cannot deny that both are highly useful. If you don’t trust my judgment, edit my second script to something you’d trust.

First script (graphs both Maddison GDP per capita series for each country of your choice).

Second script (graphs one GDP per capita series for each country of your choice, as reconciled by my judgment).

Try them out; see what you think. An example of the sort of thing you can do with the second script (trivially edited to graph total GDP rather than GDP per capita):

Yes; the USSR and some other countries are under “arbitrary revisions” in the second script; there is no real reason to believe the USSR’s per capita GDP was ever over half that of the U.S., or Russia’s ever approached 2/3 of that of the U.S. Even now, after the arbitrary revision, Russia peaks as over 48% of the U.S. in 1975, which is probably too much. My arbitrary revisions are for illustrative purposes and by their nature arbitrary (but probably necessary); make them whatever you wish.

How to use the scripts:

You naturally have to have Python installed on your system (as well as the Pandas, xlrd, and MatPlotLib Python libraries, which take up about a couple hundred megabytes combined). Then do the following:

Before this, go to the current directory, where you keep both the mpd2018.xlsx and files
Do you want a log or a linear scale?
Enter your start year, hit Enter, enter your end year, hit Enter
Your result. Whether you believe India’s real GDP per capita actually declined during the License Raj period is up to you, of course.

It’s as easy to use as that!