Normalize numerical attributes
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				@ -1,4 +1,5 @@
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from pandas import DataFrame, read_csv
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from sklearn.preprocessing import normalize
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def replace_values(df) -> DataFrame:
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@ -37,7 +38,21 @@ def filter_dataframe(df) -> DataFrame:
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    return filtered_df
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def normalize_numerical_values(df) -> DataFrame:
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    cols = [
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        "TOT_HERIDOS_LEVES",
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        "TOT_HERIDOS_GRAVES",
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        "TOT_VEHICULOS_IMPLICADOS",
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        "TOT_MUERTOS",
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    ]
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    filtered_df = df.filter(items=cols)
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    normalized_df = normalize(X=filtered_df)
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    updated_df = df.update(normalized_df)
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    return updated_df
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def parse_data(source, action) -> DataFrame:
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    df = read_csv(filepath_or_buffer=source, na_values="?")
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    processed_df = process_na(df=df, action=action)
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    return processed_df
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    normalized_df = normalize_numerical_values(df=processed_df)
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    return normalized_df
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