How to sort a dataFrame in python pandas by two or more columns?

As of pandas 0.17.0, DataFrame.sort() is deprecated, and set to be removed in a future version of pandas. The way to sort a dataframe by its values is now is DataFrame.sort_values

As such, the answer to your question would now be

df.sort_values(['b', 'c'], ascending=[True, False], inplace=True)

As of the 0.17.0 release, the sort method was deprecated in favor of sort_values. sort was completely removed in the 0.20.0 release. The arguments (and results) remain the same:

df.sort_values(['a', 'b'], ascending=[True, False])

---

You can use the ascending argument of sort:

df.sort(['a', 'b'], ascending=[True, False])

For example:

In [11]: df1 = pd.DataFrame(np.random.randint(1, 5, (10,2)), columns=['a','b'])

In [12]: df1.sort(['a', 'b'], ascending=[True, False])
Out[12]:
   a  b
2  1  4
7  1  3
1  1  2
3  1  2
4  3  2
6  4  4
0  4  3
9  4  3
5  4  1
8  4  1

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As commented by @renadeen

Sort isn't in place by default! So you should assign result of the sort method to a variable or add inplace=True to method call.

that is, if you want to reuse df1 as a sorted DataFrame:

df1 = df1.sort(['a', 'b'], ascending=[True, False])

or

df1.sort(['a', 'b'], ascending=[True, False], inplace=True)