class_docstr: The dataset is from Max Planck Institute for Biogeochemistry, Keras examples.
  
  The dataset consists of 14 variables (temperature, humidity, wind direction,
  pressure etc.) measured every 10 minutes. The data is aggregated for an hour for analysis.
  The data is aggregated for an hour (6 samples) and selected 7 features for training.
  Further, 120 hours is used as past window and 12 hours as forecast horizon.
  
  References:
      .. [#1] Max Planck Institute for Biogeochemistry. https://www.bgc-jena.mpg.de/wetter/.
      .. [#2] https://github.com/keras-team/keras-io/blob/master/examples/timeseries/timeseries_weather_forecasting.py
      .. [#3] https://www.kaggle.com/stytch16/jena-climate-2009-2016
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code: def _normalize(self, data, train_split):
      data_mean = data[:train_split].mean(axis=0)
      data_std = data[:train_split].std(axis=0)
      return (data - data_mean) / data_std
  
file_path: AIX360/aix360/datasets/climate_dataset.py
imports: import os
  import requests
  import numpy
  import pandas
  from zipfile import ZipFile
  from io import BytesIO
  from tensorflow import keras
label_desc: Use image node_id 2 for calling the ClimateDataset obj's underlying member method code with example usage: obj._normalize(data, train_split) and returns: unknown