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standardscaler pyspark

notPlancha answered on March 25, 2023 Popularity 5/10 Helpfulness 10/10

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  • standardscaler pyspark

    2

    transform one (or more) column(s) into Vector

    Now you scan scale the data using StandardScaler

    Add everything to a `Pipeline` to make it easier

    Popularity 5/10 Helpfulness 10/10 Language python
    Source: Grepper
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    Contributed on Apr 08 2023
    notPlancha
    0 Answers  Avg Quality 2/10

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    0

    #transform one column into Vector that is required input data type for Scalers. 

    from pyspark.ml.feature import StandardScaler

    from pyspark.ml.feature import VectorAssembler

    vector_assembler = VectorAssembler(inputCols=["avg_price"],

    outputCol="avg_price_vector")

    data = vector_assembler.transform(data)


    # Now you scan scale the data using StandardScaler

    standard_scaler = StandardScaler(withMean=True, withStd=True,

    inputCol="avg_price_vector",

    outputCol="avg_price_scaled")

    final_data_prepared = standard_scaler.fit(data).transform(data) 

    Popularity 6/10 Helpfulness 3/10 Language whatever
    Source: Grepper
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    Contributed on Mar 25 2023
    Terrible Toucan
    0 Answers  Avg Quality 2/10


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