So here’s the problem in a nutshell:
The Asian Development Bank put out a dataset of ‘key indicators’ for sustainable development covering their 86 member countries. I would like to have a look at how countries are performing relative to one another.
In my normal way of things, I would go about a long and tedious process of pulling out each table of interest as its own CSV file, but this practice is time intensive, prone to errors, and not reproducible. As the data for all 86 countries is relatively uniform, I figured this might be a great occasion to learn more JS and set up a notebook that extracts all these tables for me once, and then set up a selection input (like a dropdown), and then toggle between countries.
This line of questioning I’ve been asking is me trying to learn how this sort of thing is done. Here’s the first page of one country:
At the top is a header row, with values for years the each data point is collected. I’ll need to join this as a header across all tables.
After the header row is the name of the table. I’ll also need to pull this out and return in back somewhere.
Then come the table data. It’s unfortunately not all that well organized and there appear to be some conversion errors when I saved from Excel to CSV, but overall things are looking pretty well aligned using
So now I am at the point where I am starting to extract and rebuild each table.
I think so - yes? The CSV files render pretty poorly, so I need to select out specific columns and rows (for instance, starting with column 2 rather than column one)
Yes also? I would like to create arrays that contain the specific table information, in such a way to eventually pipe 'em through Tom’s Table’s tool (or similar) to basically re-create ADB’s publication, but in a manner more amenable to comparing and visualising the data.
Maybe… if what I am describing above turns out to be completely different that what you were asking about under the first two points above
By the way, ADB is nice as they do allow manipulation and re-presentation of their data, with appropriate attribution (under CC BY 3.0 IGO).