What's the alternative to pandas chain indexing?

Question

I'm taking an online class to learn python and the instructor taught us that chain indexing was not a good idea. However, he failed to tell is the appropriate alternative to use.

Suppose I have a Pandas data frame with rows indexed as ['1', '2', '3'] and columns with names ['a', 'b', 'c'].

What's the appropriate alternative to using the command df['1']['a'] to extract the value found in the first row and first column?

Answer 1

Use multi-axis indexing, e.g.

df.loc['a', '1']

When you use df['1']['a'], you are first accessing the series object s = df['1'], and then accessing the series element s['a'], resulting in two __getitem__ calls, both of which are heavily overloaded (handle a lot of scenarios, like slicing, boolean mask indexing, and so on).

It's much more efficient to use the df.loc indexer.