pandas groupby sort descending order

Question

pandas groupby will by default sort. But I'd like to change the sort order. How can I do this?

I'm guessing that I can't apply a sort method to the returned groupby object.

Answer 1

Do your groupby, and use reset_index() to make it back into a DataFrame. Then sort.

grouped = df.groupby('mygroups').sum().reset_index()
grouped.sort_values('mygroups', ascending=False)

Answer 2

As of Pandas 0.18 one way to do this is to use the sort_index method of the grouped data.

Here's an example:

np.random.seed(1)
n=10
df = pd.DataFrame({'mygroups' : np.random.choice(['dogs','cats','cows','chickens'], size=n), 
                   'data' : np.random.randint(1000, size=n)})

grouped = df.groupby('mygroups', sort=False).sum()
grouped.sort_index(ascending=False)
print grouped

data
mygroups      
dogs      1831
chickens  1446
cats       933

As you can see, the groupby column is sorted descending now, indstead of the default which is ascending.

Answer 3

Similar to one of the answers above, but try adding .sort_values() to your .groupby() will allow you to change the sort order. If you need to sort on a single column, it would look like this:

df.groupby('group')['id'].count().sort_values(ascending=False)

ascending=False will sort from high to low, the default is to sort from low to high.

*Careful with some of these aggregations. For example .size() and .count() return different values since .size() counts NaNs.

What is the difference between size and count in pandas?