Pandas groupby and make set of items

Try using:

df = df.groupby('col1')['col2'].agg({'size': len, 'set': lambda x: set(x)})

Works for me.

Update

• As late as pandas version 0.22, this is an issue.
• As of pandas version 1.1.2, this is not an issue. Aggregating set, doesn't result in TypeError: 'type' object is not iterable.
  • Not certain when the functionality was updated.

Original Answer

It's because set is of type type whereas to_set is of type function:

type(set)
<class 'type'>

def to_set(x):
    return set(x)

type(to_set)

<class 'function'>

According to the docs, .agg() expects:

arg : function or dict

Function to use for aggregating groups.

• If a function, must either work when passed a DataFrame or when passed to DataFrame.apply.

• If passed a dict, the keys must be DataFrame column names.

Accepted Combinations are:

• string cythonized function name
• function

• list of functions

• dict of columns -> functions

• nested dict of names -> dicts of functions