Python Pandas: Is Order Preserved When Using groupby() and agg()?

See this enhancement issue

The short answer is yes, the groupby will preserve the orderings as passed in. You can prove this by using your example like this:

In [20]: df.sort_index(ascending=False).groupby('A').agg([np.mean, lambda x: x.iloc[1] ])Out[20]:            B             C                 mean <lambda> mean <lambda>A                                  group1  11.0       10  101      100group2  17.5       10  175      100group3  11.0       10  101      100

This is NOT true for resample however as it requires a monotonic index (it WILL work with a non-monotonic index, but will sort it first).

Their is a sort= flag to groupby, but this relates to the sorting of the groups themselves and not the observations within a group.

FYI: df.groupby('A').nth(1) is a safe way to get the 2nd value of a group (as your method above will fail if a group has < 2 elements)

Panda's 0.19.1 doc says "groupby preserves the order of rows within each group", so this is guaranteed behavior.

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html

In order to preserve order, you'll need to pass .groupby(..., sort=False). In your case the grouping column is already sorted, so it does not make difference, but generally one must use the sort=False flag:

 df.groupby('A', sort=False).agg([np.mean, lambda x: x.iloc[1] ])