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A simple data preprocessing library built on top of sklearn.preprocessing

Project description

A simple data preprocessing library built on top of sklearn.preprocessing

Imports

from predpytest.processing import PreDPy
obj = PreDPy()

LabelEnc and OneHotEnc()

returns a dataframe which is label encoded/one-hot encoded for a particular column

Syntax:

    obj.LabelEnc(dataframe, columns)

    obj.OneHotEnc(dataframe, columns)

transform_missing()

replaces null values by mean/median/most_frequent

Syntax:

    obj.transform_missing(dataframe, strategy)

The strategies are: mean, median or most_frequent

stdscaler()

It transforms the data in such a manner that it has mean of 0 and standard deviation of 1

Syntax:

    obj.stdscaler(dataframe)

Project details


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