Reputation: 1465
Using the following example:
arrays = [['one','one','one','two','two','two'],[1,2,3,1,2,3]]
df = pd.DataFrame(np.random.randn(6,2),index=pd.MultiIndex.from_tuples(zip(*arrays)),columns=['A','B'])
As expected this apply works over the groupby object:
df.groupby(level=0).apply(lambda x: pd.rolling_mean(x, window=3, center=True))
However, when specifying options for apply it throws up an error:
df.groupby(level=0).apply(lambda x: pd.rolling_mean(x, window=3, center=True), raw=True)
TypeError: <lambda>() got an unexpected keyword argument 'raw'
I can't figure out where I have gone wrong.
Note: It seems to work fine for non MultiIndex objects
Pandas: Timing difference between Function and Apply to Series
Upvotes: 4
Views: 2019
Reputation: 60230
There are different apply
methods for DataFrame
s and GroupBy
objects. Only DataFrame.apply
has a raw
argument:
help(df.apply)
# Output:
Help on method apply in module pandas.core.frame:
apply(self, func, axis=0, broadcast=False, raw=False, reduce=None, args=(), **kwds) method of pandas.core.frame.DataFrame instance
Applies function along input axis of DataFrame.
...
Whereas for the groupby:
grouped = df.groupby(level=0)
help(grouped.apply)
# Output:
Help on method apply in module pandas.core.groupby:
apply(self, func, *args, **kwargs) method of pandas.core.groupby.DataFrameGroupBy instance
Upvotes: 4