old_contents: import pandas as pd
  
  
  class Pandas_Converter(object):
      '''
      Class Converter implements parsing from original letor txt files to
      pandas data frame representation.
      '''
  
      def __init__(self, path):
          '''
          Arguments:
              path: path to letor txt file
          '''
          self._path = path
  
      @property
      def path(self):
          return self._path
  
      @path.setter
      def path(self, p):
          self._path = p
  
      def _load_file(self):
          '''
          Loads and parses raw letor txt file.
  
          Return:
              letor txt file parsed to csv in raw format
          '''
          return pd.read_csv(str(self._path), sep=" ", header=None)
  
      def _drop_col(self, df):
          '''
          Drops last column, which was added in the parsing procedure due to a
          trailing white space for each sample in the text file
  
          Arguments:
              df: pandas dataframe
          Return:
              df: original df with last column dropped
          '''
          return df.drop(df.columns[-1], axis=1)
  
      def _split_colon(self, df):
          '''
          Splits the data on the colon and transforms it into a tabular format
          where columns are features and rows samples. Cells represent feature
          values per sample.
  
          Arguments:
              df: pandas dataframe object
          Return:
              df: original df with string pattern ':' removed; columns named appropriately
          '''
          for col in range(1,len(df.columns)):
              df.loc[:,col] = df.loc[:,col].apply(lambda x: str(x).split(':')[1])
          df.columns = ['rel', 'qid'] + [str(x) for x in range(1,len(df.columns)-1)] # renaming cols
          return df
  
      def convert(self):
          '''
          Performs final conversion.
  
          Return:
              fully converted pandas dataframe
          '''
          df_raw = self._load_file(self._path)
          df_drop = self._drop_col(df_raw)
          return self._split_colon(df_drop)
  
new_contents: import pandas as pd
  
  
  class PandasLetorConverter(object):
      '''
      Class Converter implements parsing from original letor txt files to
      pandas data frame representation.
      '''
  
      def __init__(self, path):
          '''
          Arguments:
              path: path to letor txt file
          '''
          self._path = path
  
      @property
      def path(self):
          return self._path
  
      @path.setter
      def path(self, p):
          self._path = p
  
      def _load_file(self):
          '''
          Loads and parses raw letor txt file.
  
          Return:
              letor txt file parsed to csv in raw format
          '''
          return pd.read_csv(str(self._path), sep=" ", header=None)
  
      def _drop_col(self, df):
          '''
          Drops last column, which was added in the parsing procedure due to a
          trailing white space for each sample in the text file
  
          Arguments:
              df: pandas dataframe
          Return:
              df: original df with last column dropped
          '''
          return df.drop(df.columns[-1], axis=1)
  
      def _split_colon(self, df):
          '''
          Splits the data on the colon and transforms it into a tabular format
          where columns are features and rows samples. Cells represent feature
          values per sample.
  
          Arguments:
              df: pandas dataframe object
          Return:
              df: original df with string pattern ':' removed; columns named appropriately
          '''
          for col in range(1,len(df.columns)):
              df.loc[:,col] = df.loc[:,col].apply(lambda x: str(x).split(':')[1])
          df.columns = ['rel', 'qid'] + [str(x) for x in range(1,len(df.columns)-1)] # renaming cols
          return df
  
      def convert(self):
          '''
          Performs final conversion.
  
          Return:
              fully converted pandas dataframe
          '''
          df_raw = self._load_file(self._path)
          df_drop = self._drop_col(df_raw)
          return self._split_colon(df_drop)
  
subject: Change name of pandas letor converter