41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
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import pandas as pd
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from EncoderManager import EncoderManager
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def main():
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# Define example data
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data = {
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'Color': ['Red', 'Blue', 'Green', 'Red', 'Green', 'Blue'],
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'Gender': ['Male', 'Female', 'Male', 'Female', 'Male', 'Male'],
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'Size': ['M', 'S', 'L', 'M', 'XL', 'M'],
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'Species': ['Dog', 'Cat', 'Bird', 'Dog', 'Bird', 'Cat'],
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'Count': [2, 1, 3, 4, 1, 2]
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}
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df = pd.DataFrame(data)
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# Define encoding parameters
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label_cols = ('Gender','Species')
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ordinal_cols = ('Size',)
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onehot_cols = ('Color',)
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# Create encoder manager
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encoder = EncoderManager(df, label_cols, ordinal_cols, onehot_cols)
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# Test encoding
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encoded_df = encoder.encode(inplace=False)
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print("Encoded DataFrame:")
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print(encoded_df)
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# Test decoding
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decoded_df = encoder.decode(inplace=False)
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print("Decoded DataFrame:")
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print(decoded_df)
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df_normalized = encoder.normalize('min-max', inplace=True).get_df()
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print("Normalized DataFrame:")
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print(df_normalized)
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if __name__ == "__main__":
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main()
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