GroupBy transform() throws unexpected exception when sorting each DataFrame

[bluefir]

I have the following DataFrame:

data

<class 'pandas.core.frame.DataFrame'>
MultiIndex: 410322 entries, (20111230, '00036110') to (20121019, 'Y8564W10')
Data columns:
market_cap 410117 non-null values
average_volume 410322 non-null values
return_std_daily 410322 non-null values
return_std_monthly 410322 non-null values
dtypes: float64(4)

data.index.names

['date', 'security_id']

I try to do this:

data.groupby(level='date').transform(lambda x: x.sort_index(by='average_volume'))

Traceback (most recent call last):
File "C:\Python27\lib\site-packages\IPython\core\interactiveshell.py", line 2721, in run_code
exec code_obj in self.user_global_ns, self.user_ns
File "", line 1, in
data.groupby(level='date').transform(lambda x: x.sort_index(by='average_volume'))
File "C:\Python27\lib\site-packages\pandas\core\groupby.py", line 1745, in transform
return self._transform_item_by_item(obj, wrapper)
File "C:\Python27\lib\site-packages\pandas\core\groupby.py", line 1777, in _transform_item_by_item
raise TypeError('Transform function invalid for data types')
TypeError: Transform function invalid for data types

At the same time the following works

def apply_by_group(grouped, f):
    """
    Applies a function to each Series or DataFrame in a GroupBy object, concatenates the results
    and returns the resulting Series or DataFrame.

    Parameters
    ----------
    grouped: SeriesGroupBy or DataFrameGroupBy
    f: callable
        Function to apply to each Series or DataFrame in the grouped object.

    Returns
    -------
    Series or DataFrame that results from applying the function to each Series or DataFrame in the
    GroupBy object and concatenating the results.

    """
    assert isinstance(grouped, (SeriesGroupBy, DataFrameGroupBy))
    assert hasattr(f, '__call__')

    groups = []
    for key, group in grouped:
        groups.append(f(group))
    return pd.concat(groups)

apply_by_group(data.groupby(level='date'), lambda x: x.sort_index(by='average_volume'))

<class 'pandas.core.frame.DataFrame'>
MultiIndex: 410322 entries, (20111230, '31340030') to (20121019, '03783310')
Data columns:
market_cap 410117 non-null values
average_volume 410322 non-null values
return_std_daily 410322 non-null values
return_std_monthly 410322 non-null values
dtypes: float64(4)

Is this strange or am I doing something wrong with transform()?

[jreback]

can you try with master, this should work now

[jreback]

@bluefir #3145 should have fixed this, pls report if that is accurate...thxs

[bluefir]

dev-b41dc91 was made on March 24. Does it contain the fix? I assumed it didn't.

[jreback]

ahh...you need windows....ok...well then will leave this open for a bit, pls check back periodically for the updated builds

[wesm]

I need to get the build box back up

[wesm]

Build box is back up, dev binaries should flow through to the pandas website over the next few hours. pls reopen the issue if problem not resolved