October 2017
Intermediate to advanced
532 pages
16h 10m
English
Content preview from Pandas Cookbook
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Tidying variable values as column names with stack
To help understand the differences between tidy and messy data, let's take a look at a simple table that may or may not be in tidy form:
>>> state_fruit = pd.read_csv('data/state_fruit.csv', index_col=0)>>> state_fruit
There does not appear to be anything messy about this table, and the information is easily consumable. However, according to the tidy principles, it isn't actually tidy. Each column name is actually the value of a variable. In fact, none of the variable names are even present in the DataFrame. One of the first steps to transform a messy dataset into tidy data is to identify ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.