We generate high, low, open, close and volume data using a simple method for a fictitious stock or crypto, plot it on a candlestick chart and use a custom font from disk to render the plot.
I step through extracting geo-data from a Wikipedia table (or any HTML source) and plotting it on an interactive canvas.
Does the capital of a country tend to be geographically close to the center? (Answer - not really.)
Exploration of basic plotting with geopandas and collating them into subplots. Formatting it and editing the colormap legends.
I show how to lay out countries in a tilemap and populate them as a heatmap using pyplot imshow.
Demonstrating that similarity of pairs of strings is uncorrelated to Jaro and Damerau-Levenshtein similarity of their md5 hashes.
Mapping a bar chart to a circular plot, with variations on circular plotting.
A quick way to generate "normally" distributed data but exclude extreme values.
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