PreProcessing Ninja

A PreProcessing library for your basic PreProcessing needs

Features of the package

• impute_missing_value: Helps to impute missing values
• scale_data: Scales the data
• encode_categorical_data: Helps in encoding categorical variables
• remove_outliers: Helps in removing outliers

Use

pip install PreProcessingNinja

Example

from preprocessing_ninja import PreProcessingNinja
ninja = PreProcessingNinja()

#creating column dictionary
d = {
    'column1':'mean',
    'column2':'mean',
    'column3':'most_frequent'
}

#calling method
df = ninja.impute_missing_value(datafra,e, d)

Note

There might be bugs.

Authors

• @BijoyKumarRoy