class_docstr: Class to build a Prophet Model
      
class_docstr_tok: ["Class","to","build","a","Prophet","Model"]
docstr: Renames the columns of the input dataframe to the right format needed by Prophet
  Target is renamed to 'y' and the time column is renamed to 'ds'
  # TODO: Complete docstring
docstr_tok: ["Renames","the","columns","of","the","input","dataframe","to","the","right","format","needed","by","Prophet","Target","is","renamed","to","'","y","'","and","the","time","column","is","renamed","to","'ds'","#","TODO",":","Complete","docstring"]
code: def prep_col_names_for_prophet(
      self, ts_df: pd.DataFrame, test: bool = False
  ) -> pd.DataFrame:
      """
      Renames the columns of the input dataframe to the right format needed by Prophet
      Target is renamed to 'y' and the time column is renamed to 'ds'
      # TODO: Complete docstring
      """
  
      if self.time_col not in ts_df.columns:
          #### This happens when time_col is not found but it's actually the index. In that case, reset index
          data = ts_df.reset_index()
      else:
          data = ts_df.copy(deep=True)
  
      if self.time_col not in data.columns:
          print(
              "(Error): You have not provided the time_column values. This will result in an error"
          )
  
      if test is False:
          data = data.rename(
              columns={
                  self.time_col: "ds",
                  self.original_target_col: "y",
              }
          )
      else:
          data = data.rename(columns={self.time_col: "ds"})
  
      return data
  
imports: from typing import Optional
  import logging
  import copy
  import time
  import numpy
  from sklearn.model_selection import TimeSeriesSplit
  import pandas
  from pandas.core.generic import NDFrame
  import pdb
  import dask
  import dask.dataframe
  import matplotlib.pyplot
  from prophet import Prophet
  from prophet.diagnostics import cross_validation
  from prophet.diagnostics import performance_metrics
  from prophet.plot import plot_cross_validation_metric
  from .build_base import BuildBase
  from ..utils import print_dynamic_rmse, quick_ts_plot, print_ts_model_stats
  from ..utils.logging import SuppressStdoutStderr
  from sklearn.metrics import mean_squared_error
  from prophet import Prophet
  import time
  import pdb
  import copy
  import matplotlib.pyplot
label_desc: Use image node_id 6 for calling the BuildProphet obj's underlying member method code with example usage: obj.prep_col_names_for_prophet(ts_df, test) and returns: data