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What are the data analysis functions in Python? I believe many inexperienced people are at a loss about this. Therefore, this paper summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.

The digitization of classification variables refers to the conversion of enumerated variables into indicator vectors or dummy vectors. What is an indicator vector? take a look at the following example. The A variable is parsed as: [1], and the B is parsed as: [0].

S = pd.Series (list ('ABCA')) pd.get_dummies (s) # results AB C0 1 0 01 01 02 0 0 13 1 0 0

In addition to get_dummies, there is also an enumerated type variable annotation function: factorize, which has the following functions:

Labels, uniques = pd.factorize (['A','B','C','A']) # result labels is the ndarrays:array ([0, 1, 2, 0], dtype=int64) uniques:array (['A','B','C'], dtype=object) of NumPy. Have you mastered any data analysis functions in Python after reading the above? If you want to learn more skills or want to know more about it, you are welcome to follow the industry information channel, thank you for reading!

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