A data preprocessing helper consists of your basic preprocessing needs
Project description
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.
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