Is there any faster way than pandas fillna()?

I try to test:

np.random.seed(123)
N = 60000
df = pd.DataFrame(np.random.choice(['a', None], size=(N, 20), p=(.7, .3)))

In [333]: %timeit df.fillna('b')
93.5 ms ± 1.28 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

In [337]: %timeit df[df.isna()] = 'b'
122 ms ± 2.75 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

Changed solution (but I find it a bit hacky):

#pandas below
In [335]: %timeit df.values[df.isna()] = 'b'
56.7 ms ± 799 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

#pandas 0.24+
In [339]: %timeit df.to_numpy()[df.isna()] = 'b'
56.5 ms ± 951 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)