code: def DEFAULT_TYPEINFERER(column):
      
      try:
          return np.array([int(x) for x in column], 'int')
      except:
          try:
              return np.array([float(x) if x != '' else np.nan for x in column],
                              'float')
          except:
              return np.array(column, 'str')
docs: Infer the data type (int, float, str) of a list of strings.
  
      Take a list of strings, and attempts to infer a numeric data type that fits
      them all.
  
      If the strings are all integers, returns a NumPy array of integers.
  
      If the strings are all floats, returns a NumPy array of floats.
  
      Otherwise, returns a NumPy array of the original list of strings.
  
      Used to determine the datatype of a column read from a separated-variable
      (CSV) text file (e.g. ``.tsv``, ``.csv``) of data where columns are
      expected to be of uniform Python type.
  
      This function is used by tabular load functions for SV files, e.g. by
      :func`tabular.io.loadSV` when type information is not provided in the
      header, and by :func:`tabular.io.loadSVsafe`.
  
      **Parameters**
  
              **column** :  list of strings
  
                      List of strings corresponding to a column of data.
  
      **Returns**
  
              **out** :  numpy array
  
                      Numpy array of data from `column`, with data type
                      int, float or str.