Metadata-Version: 2.1
Name: featureColByTorch
Version: 1.0
Summary: this is a feature column and transformer tools in pytorch, which is like the featureColumn class in Tensorflow
Home-page: https://blog.csdn.net/qq_40742298
Author: Braylon
Author-email: S.Braylon1002@gmail.com
Maintainer: Braylon
Maintainer-email: S.Braylon1002@gmail.com
License: BSD License
Description: ## Feature Column in Pytorch
        
        ### Description
        
        this is a feature column tool implemented by pytorch, which has the same function compared to featurecol class in Tensorflow.
        
        And it's also a tool for me to paricipate in some data science competition.
        
        ### Usage
        
        ```python
        from features import Features
        from number_feat import Number
        from category_feat import Category
        
        from transformers.NumberTransformer import NumberTransformer
        from transformers.CategoryTransformer import CategoryTransformer
        import pandas as pd
        import numpy as np
        ```
        
        - Example
        ```python
        def make_data():
            data = pd.DataFrame(np.random.randint(1, 20, size=(3,4)), columns=['col1', 'col2', 'col3', 'col4'])
            return data
        
        if __name__ == "__main__":
            data = make_data()
            Number_1 = Number('col1', NumberTransformer())
            Category_1 = Category('col2', CategoryTransformer())
            Category_2 = Category('col3', CategoryTransformer())
            Features_1 = Features(number_feat=[Number_1], category_feat=[Category_2], sequence_feat=[])
            print(Features_1.number_feat)
            Features_1.fit(data)
            res = Features_1.transform(data)
            print(res)
        ```
        
        ### Returned Data
        
        ```python
        # [<number_feat.Number object at 0x0000018903E64748>]
        # OrderedDict([('col1', array([-1.4048787 ,  0.8429272 ,  0.56195146], dtype=float32)), ('col3', array([1, 1, 1], dtype=int64))])
        ```
Platform: all
Description-Content-Type: text/markdown
