In [1]: from string import ascii_lowercase
In [2]: np.random.seed(2718281)
In [3]: n = 1 << 21
In [4]: dr = date_range('2015-08-30', periods=n // 10, freq='T')
In [5]: df = DataFrame({
...: '1st':np.random.choice(list(ascii_lowercase), n),
...: '2nd':np.random.randint(0, 5, n),
...: '3rd':np.random.choice(dr, n)})
In [6]: df.loc[np.random.choice(n, n // 10), '3rd'] = np.nan
In [7]: gr = df.groupby(['1st', '2nd'])
In [8]: %timeit gr.count()
The slowest run took 21.22 times longer than the fastest. This could mean that an intermediate result is being cached
1 loops, best of 3: 13.3 ms per loop
In [9]: %timeit gr.count()
100 loops, best of 3: 13.8 ms per loop
In [10]: pd.__version__
Out[10]: '0.16.2+521.g207efc2'
In [8]: %timeit gr.count()
1 loops, best of 3: 144 ms per loop
In [9]: %timeit gr.count()
10 loops, best of 3: 149 ms per loop
In [10]: pd.__version__
Out[10]: '0.16.2+522.g9c2d1a6'
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