code: def make_seasonal_dummies(
      df, date_col, freq, sparse=True, drop_first=True
  ):
      """Based on the frequency input (in pandas.DataFrame style), provide dummies indicator for regression type of
      purpose.
  
      Parameters
      ----------
      df : pd.DataFrame
          Input dataframe to supply datetime array for generating series of indicators
      date_col : str
          Label of the date column supply for generating series
      freq : str ['weekday', 'month', 'week']
          Options to pick the right frequency for generating dummies
      sparse : bool
          argument passed into `pd.get_dummies`
      drop_first : bool
          argument passed into `pd.get_dummies`
      Returns
      -------
      out : pd.DataFrame
          data with computed fourier series attached
      fs_cols : list
          list of labels derived from fourier series
      Notes
      -----
          This is calling :func:`pd.get_dummies`
      """
      if freq == "weekday":
          dummies = pd.get_dummies(
              df[date_col].dt.weekday,
              prefix="wd",
              sparse=sparse,
              drop_first=drop_first,
          )
      elif freq == "month":
          dummies = pd.get_dummies(
              df[date_col].dt.month,
              prefix="m",
              sparse=sparse,
              drop_first=drop_first,
          )
      elif freq == "week":
          dummies = pd.get_dummies(
              df[date_col].dt.week,
              prefix="w",
              sparse=sparse,
              drop_first=drop_first,
          )
      else:
          raise IllegalArgument("Invalid argument of freq.")
  
      cols = dummies.columns.tolist()
      out = pd.concat([df, dummies], axis=1)
      return out, cols
  
file_path: orbit/orbit/utils/features.py
imports: import numpy
  import pandas
  from orbit.exceptions import IllegalArgument
label_desc: Use image node_id 3 for calling a global function with example usage: make_seasonal_dummies(df, date_col, freq, sparse, drop_first) and returns: out,  cols