October 2017
Intermediate to advanced
532 pages
16h 10m
English
Content preview from Pandas Cookbook
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Understanding data types
In very broad terms, data may be classified as either continuous or categorical. Continuous data is always numeric and represents some kind of measurement, such as height, wage, or salary. Continuous data can take on an infinite number of possibilities. Categorical data, on the other hand, represents discrete, finite amounts of values such as car color, type of poker hand, or brand of cereal.
Pandas does not broadly classify data as either continuous or categorical. Instead, it has precise technical definitions for many distinct data types. The following table contains all pandas data types, with their string equivalents, and some notes on each type:
| Common data type name | NumPy/pandas object | Pandas string name ... |
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