pd.read_fwf(path, colspecs=markers, names=columns,
            converters=create_convert_dict(columns))

def create_convert_dict(columns):
    convert_dict = {}
    for col in columns:
        convert_dict[col] = null_convert
        return convert_dict

def null_convert(value):
    value = value.strip()
    if value == "":
        return None
    else:
        return value

pd.read_fwf(path, colspecs=markers, names=columns, na_values='',
            converters=create_convert_dict(columns))

def create_convert_dict(columns):
    convert_dict = {}
    for col in columns:
        convert_dict[col] = col_strip
    return convert_dict

def col_strip(value):
    return value.strip()

In [57]: data = """
A    B     C
 0    foo
3    bar     2.0
  1        3.0
"""

In [58]: df = pandas.read_fwf(StringIO(data), widths=[5, 5, 5])

In [59]: df
Out[59]:
   A    B   C
0  0  foo NaN
1  3  bar   2
2  1  NaN   3

In [60]: df.dtypes
Out[60]:
A      int64
B     object
C    float64