sklearnFunctions 0.0.9

module built on needy sklearn preprocessing functions

sklearnFunctions - eleka12

This package is built on top of functions which are mostly required in a Data processing lifecycle.

As of now This package contains a function which can remove outliers present in the Dataset

More number of functions will be added...

How to use sklearnFunctions

• install the latest package

• in jupyter notebook -

    !pip install sklearnFunctions

• in command prompt -

    pip install sklearnFunctions

• Now run below snippets of code in your jupyter-notebooks / python project

Importing sklearnFunctions

from sklearnFunctions.preprocessing import outliers

The input for the outlier function must be in DataFrame

old_df = pd.DataFrame({"X":xvals,"Y":yvals})

Checking for outliers | .is_present() function will return a percentage of outlier present in each column

outliers().is_present(old_df)

Removing outliers from DataFrame | .outliers_removal() function will remove all the outliers present in DataFrame

new_df = outliers().outliers_removal(old_df)

pypi repo link -

mongoops - PYPI

Github repo link -

mongoops - Github