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
1 maintainer
Metadata
1 maintainer
Release files for PreProcessingNinja 0.0.1
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Source distribution (sdist)
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| PreProcessingNinja-0.0.1-py3-none-any.whl | Python 3 | none | any | Details for PreProcessingNinja-0.0.1-py3-none-any.whl |
Total release size: 6.8 kB
Release files / PreProcessingNinja-0.0.1.tar.gz
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Release files / PreProcessingNinja-0.0.1-py3-none-any.whl
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