docs: def summarize(df,preview_rows = 8,
              display_max_cols = None,display_width = None,
              output_path = None, output_safe = True,to_folder = False): 
      """ Prints information about the DataFrame to a file or to the prompt.
  
      Parameters
      ----------
      df - DataFrame
          The DataFrame to summarize
      preview_rows - int, default 5
          Amount of rows to preview from the head and tail of the DataFrame
      display_max_cols - int, default None
          Maximum amount of columns to display. If set to None, all columns will be displayed.
          If set to 0, only as many as fit in the screen's width will be displayed
      display_width - int, default None
          Width of output. Can be width of file or width of console for printing.
          Set to None for pandas to detect it from console.
      output_path - path-like, default None
          If not None, this will be used as the path of the output file, and this
          function will print to a file instead of to the prompt
      output_safe - boolean, default True
          If True and output_file is not None, this function will not overwrite any
          existing files.
      output_csv: boolean, default False
          If True, will output to a directory with name of output_path with all data in 
          csv format. WARNING: If set to true, this function will overwrite existing files
          in the directory with the following names: 
              ['Preview.csv','Describe.csv','Info.csv','Percentile Details.csv',
               'Missing Values Summary.csv','Potential Outliers.csv','Correlation Matrix.csv']
      """
      assert type(df) is pd.DataFrame
      
      # Reformat displays
      initial_settings = pd_settings(display_max_cols, None, display_width)
  
      # --------Values of data-----------
      df_preview = _io.preview(df,preview_rows)
      df_desc_num, df_desc_cat = detailed_desc(df)
      percent_values = stats.percentiles(df)
      potential_outliers = stats.df_outliers(df).dropna(axis = 1,how = 'all')
      potential_outliers = potential_outliers if _utils.rows(potential_outliers) else None
      corr_values = regstats.corr_matrix(df)
  
      # ----------Build lists------------
      
      title_list = \
      ['Preview','Describe (Numerical)','Describe (Categorical)','Percentile Details',
       'Potential Outliers','Correlation Matrix']
      info_list = \
      [df_preview,df_desc_num, df_desc_cat,percent_values,
       potential_outliers,corr_values]
      error_list = [None,'No numerical data.','All numerical data.','No numerical data.',
                    'No potential outliers.','No categorical, bool, or numerical data.']
      
      # ----------Build output------------
      
      output = ''
      for title, value,error_text in zip(title_list,info_list,error_list):
          if value is None:
              value = "{} skipped: {}".format(title,error_text)
          if str(value).endswith('\n'):
              value = value[:-1]
          output+='{}\n{}\n\n'.format(_io.title_line(title),value)
  
      # ----------Send to file/print to console------------
      if output_path is None: 
          # Potentially could change this to allow for output_safe to work with directories
           print(output)
      else:
          if not to_folder:
              print('Outputting to file...')
              _io.output_to_file(output,output_path,output_safe)
          else:
              print('Outputting to folder...')
              if not os.path.exists(output_path):
                  os.mkdir(output_path)
              for title, value,error_text in zip(title_list,info_list,error_list):
                  if value is None:
                      print("{} skipped: {}".format(title,error_text))
                  else:
                      file_dir = os.path.join(output_path,"{}.csv".format(title))
                      if type(value) is pd.DataFrame:
                          # Eventually add a check to see if file exists
                          value.to_csv(file_dir)
                      else:
                          _io.output_to_file(value,file_dir,False) 
                          # Change to output_safe when directory output_safe is implemented
          print('Done!')
  
      # Reset display settings
      pd_settings(*initial_settings)