Sort pandas dataframe both on values of a column and index?

Question

Is it feasible to sort pandas dataframe by values of a column, but also by index?

If you sort a pandas dataframe by values of a column, you can get the resultant dataframe sorted by the column, but unfortunately, you see the order of your dataframe's index messy within the same value of a sorted column.

So, can I sort a dataframe by a column, such as the column named count but also sort it by the value of index? And is it also feasible to sort a column by descending order, but whereas sort a index by ascending order?

I know how to sort multiple columns in dataframe, and also know I can achieve what I'm asking here by first reset_index() the index and sort it, and then create the index again. But is it more intuitive and efficient way to do it?

Answer 1

Pandas 0.23 finally gets you there :-D

You can now pass index names (and not only column names) as parameters to sort_values. So, this one-liner works:

df = df.sort_values(by = ['MyCol', 'MyIdx'], ascending = [False, True])

And if your index is currently unnamed:

df = df.rename_axis('MyIdx').sort_values(by = ['MyCol', 'MyIdx'], ascending = [False, True])

Answer 2

In pandas 0.23+ you can do it directly - see OmerB's answer. If you don't yet have 0.23+, read on.

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I'd venture that the simplest way is to just copy your index over to a column, and then sort by both.

df['colFromIndex'] = df.index
df = df.sort(['count', 'colFromIndex'])

I'd also prefer to be able to just do something like df.sort(['count', 'index']), but of course that doesn't work.