code: def normalize(df, style = 'mean'):
      
      if style == 'mean':
          df_mean,df_std = df.mean(),df.std()
          return (df-df_mean)/df_std
      elif style == 'minmax':
          col_min,col_max = df.min(),df.max()
          return (df-col_min)/(col_max-col_min)
      else:
          return style(df)
docs: Returns a normalized version of a DataFrame or Series
      Parameters:
      df - DataFrame or Series
          The data to normalize
      style - function or string, default 'mean'
          The style to use when computing the norms. Takes 'mean' or 'minmax' to
          do mean or min-max normalization respectively. User-defined functions that take
          a pandas Series as input and return a normalized pandas Series are also accepted