code: def column_of_data(path, start, column, end="-1", units=""):
      
      if not isinstance(start, int):
          start = int(start)
      if not isinstance(end, int):
          end = int(end)
  
      df = pd.read_csv(path, delimiter='\t')
      if units == "":
          if isinstance(column, int):
              data = np.array(pd.to_numeric(df.iloc[start:end, column]))
          else:
              df[column][0:len(df)]
      else:
          if isinstance(column, int):
              data = np.array(pd.to_numeric(df.iloc[start:end, column]))*u(units)
          else:
              df[column][0:len(df)]*u(units)
      return data
docs: This function extracts a column of data from a ProCoDA data file.
  
      Note: Column 0 is time. The first data column is column 1.
  
      :param path: The file path of the ProCoDA data file. If the file is in the working directory, then the file name is sufficient.
      :type path: string
      :param start: Index of first row of data to extract from the data file
      :type start: int
      :param end: Index of last row of data to extract from the data. Defaults to last row
      :type end: int, optional
      :param column: Index of the column that you want to extract OR name of the column header that you want to extract
      :type column: int or string
      :param units: The units you want to apply to the data, e.g. 'mg/L'. Defaults to "" (dimensionless)
      :type units: string, optional
  
      :return: Experimental data with the units applied.
      :rtype: numpy.array
  
      :Examples:
  
      .. code-block:: python
  
          data = column_of_data("Reactor_data.txt", 0, 1, -1, "mg/L")