module built on needy sklearn preprocessing functions
Project description
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 -
Github repo link -
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