How to properly use str.replace() with Pandas DataFrame

Aw man, convert to a datetime then get the year:

df_MVPs['Year'] = pd.to_datetime(df_MVPs['Year'], format='%b. %d, %Y').dt.year

You could take the last four characters of the string:

df_MVPs['Year'] = df_MVPs['Year'].str[-4:]

>>> df_MVPs
    Year        Player
46  1971  Chuck Howley
47  1970    Len Dawson
48  1969    Joe Namath
49  1968    Bart Starr
50  1967    Bart Starr

I'd use .str.extract() method instead:

In [10]: df
Out[10]:
             Year        Player
46  Jan. 17, 1971  Chuck Howley
47  Jan. 11, 1970    Len Dawson
48  Jan. 12, 1969    Joe Namath
49  Jan. 14, 1968    Bart Starr
50  Jan. 15, 1967    Bart Starr

In [11]: df.Year.str.extract('.*(\d{4})$', expand=True)
Out[11]:
       0
46  1971
47  1970
48  1969
49  1968
50  1967

but you can also use .str.replace():

In [13]: df.Year.str.replace('.*(\d{4})$', r'\1')
Out[13]:
46    1971
47    1970
48    1969
49    1968
50    1967
Name: Year, dtype: object

Here is a link which explains the .*(\d{4})$ RegEx (Regular Expresiion)