Global Trends Deserve Global Charts and a Note on Chart Infrastructure
In the next few series of posts I plan to do something I've largely shied away from in my career: cross-sectional data. This data is important because it helps to remind us that the mean is just that - the mean. It hides import variation in the data. Just look at the graph below for an example!
So in the next few posts I will focus on the world, at fixed points in time, to delve in and help describe whats happening globally. For this exercise, I will rely on Treasury TIC data, the BIS for short-term rates and Inflation, and the IMF and OECD for a smorgasbord of other data. I hope you come to enjoy what follows.Historical #dataviz: Fluctuations in wholesale prices, 1891 to 1918 https://t.co/ZfUC9ZmAT0 pic.twitter.com/baE8w7VCPv— FRASER (@FedFRASER) September 18, 2019
Building a chart infrastructure
What is chart infrastructure? It is a set of charts that can be easily transferred to new problems. It's all about efficiency and "reproduce ability" - that's what statistical programming is all about (in my view). A proper chart infrastructure requires proper data, for geographical data it's all about making sure the names of locations in your data-set match-up with your coordinate 'crosswalk' files. This files has things like state abbreviations and states spelled out in full - in order to cover the bases and making merging in new data-sets easier.
Chart Infrastructure as geographical or otherwise, also means setting up a data process that allows for the easy and swift update of charts. Therefore, having a proper chart infrastructure requires having a proper data infrastructure. For example, take the charts below.
A. I save each chart as a 6 x 11 so that each chart takes up the exact same area in my work across all platforms.
B. For each area I have a set of fixed latitudes and longitudes, so that in future plots involving Europe or South America will be comparable to the eye.
C. Each plot is made easily update-able by the data flow infrastructure.
These points are recommended for those building chart-packs.
Chart Infrastructure as geographical or otherwise, also means setting up a data process that allows for the easy and swift update of charts. Therefore, having a proper chart infrastructure requires having a proper data infrastructure. For example, take the charts below.
A. I save each chart as a 6 x 11 so that each chart takes up the exact same area in my work across all platforms.
B. For each area I have a set of fixed latitudes and longitudes, so that in future plots involving Europe or South America will be comparable to the eye.
C. Each plot is made easily update-able by the data flow infrastructure.
These points are recommended for those building chart-packs.