Pythonic to randomly assign pandas dataframe entries

Suppose we have a data frame

In [1]: df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))

In [2]: df
Out[3]:
     A   B   C   D
0   45  88  44  92
1   62  34   2  86
2   85  65  11  31
3   74  43  42  56
4   90  38  34  93
5    0  94  45  10
..  ..  ..  ..  ..

How can I randomly replace x% of all entries with a value, such as None?

In [4]: something(df, percent=25)
Out[5]:
     A   B   C   D
0   45  88  None  92
1   62  34   2  86
2   None  None  11  31
3   74  43  None  56
4   90  38  34  None
5    None  94  45  10
..  ..  ..  ..  ..

I've found information about sampling particular axes, and I can imagine a way of randomly generating integers within the dimensions of my data frame and setting those equal to None, but that doesn't feel very Pythonic.