code: def _maxabs_scaler_scale_timeseries_numpy(data, scaler):
      data_scale = np.zeros(data.shape)
      for i in range(data.shape[1]):
          value_max_abs = scaler.scale_[i]
          data_scale[:, i] = data[:, i] / value_max_abs
      return data_scale
  
file_path: BigDL/python/chronos/src/bigdl/chronos/data/utils/scale.py
imports: import numpy
  import pandas
  from sklearn.preprocessing import StandardScaler, MaxAbsScaler, MinMaxScaler, RobustScaler
label_desc: Use image node_id 7 for calling a global function with example usage: _maxabs_scaler_scale_timeseries_numpy(data, scaler) and returns: data_scale