docstr: A default pre-processing and information gathering from training input dataframe
docstr_tok: ["A","default","pre-processing","and","information","gathering","from","training","input","dataframe"]
code: def _set_training_meta(self, df):
      """A default pre-processing and information gathering from training input dataframe"""
      training_meta = dict()
      response = df[self.response_col].values
      training_meta[TrainingMetaKeys.RESPONSE.value] = response
      training_meta[TrainingMetaKeys.DATE_ARRAY.value] = pd.to_datetime(
          df[self.date_col]
      ).reset_index(drop=True)
      training_meta[TrainingMetaKeys.NUM_OF_OBS.value] = len(response)
      training_meta[TrainingMetaKeys.RESPONSE_SD.value] = np.nanstd(
          response
      )
      training_meta[TrainingMetaKeys.RESPONSE_MEAN.value] = np.nanmean(
          response
      )
      training_meta[TrainingMetaKeys.START.value] = df[
          self.date_col
      ].iloc[0]
      training_meta[TrainingMetaKeys.END.value] = df[
          self.date_col
      ].iloc[-1]
      training_meta[TrainingMetaKeys.DATE_COL.value] = self.date_col
      training_meta[
          TrainingMetaKeys.RESPONSE_COL.value
      ] = self.response_col
      self._training_meta = training_meta
  
imports: from copy import deepcopy
  import numpy
  import pandas
  import warnings
  from enum import Enum
  from typing import Dict, Any
  from ..exceptions import ForecasterException, AbstractMethodException, IllegalArgument
  from ..utils.general import is_ordered_datetime, is_even_gap_datetime
  from ..template.model_template import ModelTemplate
  from ..estimators.stan_estimator import StanEstimatorMCMC
  from ..constants.constants import TrainingMetaKeys, PredictionMetaKeys
label_desc: Use image node_id 4 for calling the Forecaster obj's underlying member method code with example usage: obj._set_training_meta(df) without return types