code: def transform(self, shard: "SparkXShards") -> "SparkXShards":
      invalidInputError(
          self.scalerModel, "Please call fit_transform first"
      )
      df = shard.to_spark_df()
      scaledData = self.scalerModel.transform(df)  # type: ignore
      scaledData = scaledData.drop(self.vecOutputCol)
      data_shards = spark_df_to_pd_sparkxshards(scaledData)
      return data_shards
  
imports: import pyspark.sql.functions
  from pyspark.sql import Row
  from pyspark.sql.types import IntegerType, StructType, StringType, StructField
  from bigdl.dllib.utils.log4Error import invalidInputError
  from bigdl.orca.data import SparkXShards
  from bigdl.orca import OrcaContext
  from pyspark.ml.feature import MinMaxScaler
  from pyspark.ml.feature import StandardScaler
  from pyspark.ml.feature import VectorAssembler
  from pyspark.ml import Pipeline
  from bigdl.orca.data.utils import *
  import uuid
  from typing import TYPE_CHECKING, Tuple, Union, List
label_desc: Use image node_id 5 for calling the MinMaxScaler obj's underlying member method code with example usage: obj.transform(shard) and returns: data_shards