pandas .at versus .loc

Question

I\'ve been exploring how to optimize my code and ran across pandas .at method. Per the documentation

Fast label-based scalar ac

Answer 1

Update: df.get_value is deprecated as of version 0.21.0. Using df.at or df.iat is the recommended method going forward.

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df.at can only access a single value at a time.

df.loc can select multiple rows and/or columns.

Note that there is also df.get_value, which may be even quicker at accessing single values:

In [25]: %timeit df.loc[('a', 'A'), ('c', 'C')]
10000 loops, best of 3: 187 µs per loop

In [26]: %timeit df.at[('a', 'A'), ('c', 'C')]
100000 loops, best of 3: 8.33 µs per loop

In [35]: %timeit df.get_value(('a', 'A'), ('c', 'C'))
100000 loops, best of 3: 3.62 µs per loop

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Under the hood, df.at[...] calls df.get_value, but it also does some type checking on the keys.