Question
Suppose I have a dataframe with columns a, b and c, I want to sort the
dataframe by column b in ascending order, and by column c in descending
order, how do I do this?
Answer
As of the 0.17.0 release, the [sort](http://pandas.pydata.org/pandas-
docs/version/0.17.0/generated/pandas.DataFrame.sort.html) method was
deprecated in favor of [sort_values](http://pandas.pydata.org/pandas-
docs/stable/generated/pandas.DataFrame.sort_values.html). 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](http://pandas.pydata.org/pandas-
docs/stable/generated/pandas.DataFrame.sort.html):
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
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)
