original_docstring: 
      This function allows to add the int experience column to the files. It can be useful if you need to sort the data
      by the users' experience. Int experience values can be found in the const file (the INT_EXPERIENCE Enum class).
  
      Note: It may be necessary for files with old data format
  
      For more details see
      https://github.com/JetBrains-Research/task-tracker-post-processing/wiki/Data-processing:-add-int-experience-column
      
docstring: This function allows to add the int experience column to the files. It can be useful if you need to sort the data
  by the users' experience. Int experience values can be found in the const file (the INT_EXPERIENCE Enum class).
  
  It may be necessary for files with old data format
  
  
docstring_tokens: This function allows to add the int experience column to the files . It can be useful if you need to sort the data by the users ' experience . Int experience values can be found in the const file ( the INT_EXPERIENCE Enum class ) . It may be necessary for files with old data format
code: def add_int_experience(path: str, output_directory_prefix: str = 'int_exp') -> str:
      """
      This function allows to add the int experience column to the files. It can be useful if you need to sort the data
      by the users' experience. Int experience values can be found in the const file (the INT_EXPERIENCE Enum class).
  
      Note: It may be necessary for files with old data format
  
      For more details see
      https://github.com/JetBrains-Research/task-tracker-post-processing/wiki/Data-processing:-add-int-experience-column
      """
      output_directory = get_output_directory(path, output_directory_prefix)
      files = get_all_file_system_items(path)
      for file in files:
          df = pd.read_csv(file, encoding=ISO_ENCODING)
          if TASK_TRACKER_COLUMN.EXPERIENCE.value in df.columns:
              # It is old file structure
              df[TASK_TRACKER_COLUMN.INT_EXPERIENCE.value] = \
                  df[TASK_TRACKER_COLUMN.EXPERIENCE.value].apply(convert_to_int_experience)
          write_result(output_directory, path, file, df)
      return output_directory
code_tokens: def add_int_experience ( path : str , output_directory_prefix : str = 'int_exp' ) -> str : output_directory = get_output_directory ( path , output_directory_prefix ) files = get_all_file_system_items ( path ) for file in files : df = pd . read_csv ( file , encoding = ISO_ENCODING ) if TASK_TRACKER_COLUMN . EXPERIENCE . value in df . columns : df [ TASK_TRACKER_COLUMN . INT_EXPERIENCE . value ] = df [ TASK_TRACKER_COLUMN . EXPERIENCE . value ] . apply ( convert_to_int_experience ) write_result ( output_directory , path , file , df ) return output_directory
short_docstring: This function allows to add the int experience column to the files.
short_docstring_tokens: This function allows to add the int experience column to the files .
comment: """
      This function allows to add the int experience column to the files. It can be useful if you need to sort the data
      by the users' experience. Int experience values can be found in the const file (the INT_EXPERIENCE Enum class).
  
      Note: It may be necessary for files with old data format
  
      For more details see
      https://github.com/JetBrains-Research/task-tracker-post-processing/wiki/Data-processing:-add-int-experience-column
      """$SEP$# It is old file structure