Ok, this was more complex than I thought. I hope I got it right and this gives you some pointers how I investigated. :) Use type() to see what you are getting:

Ok, this was more complex than I thought. I hope I got it right and this gives you some pointers how I investigated. :) Use type() to see what you are getting: >>> type(df.describe().mean()) <class 'pandas.core.series.Series'> >>> type(df.describe().mean) <class 'method'> Something without parenthesis cannot be a method call, at least not from a normal viewpoint. Instead you are trying to access the attribute "mean" of the result of describe() if you run df.groupby(df.var1).describe().mean. This attribute might very well be a method itself (a method object). Last in that chain was describe(), so let's look at that: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.describe.html https://pandas.pydata.org/pandas-docs/stable/generated/panda... It returns a "summary: Series/DataFrame of summary statistics", so calling .mean() on that, will call https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.mean.html#pandas.DataFrame.mean https://pandas.pydata.org/pandas-docs/stable/generated/panda... Accessing .mean will instead return that method object itself. By default pandas will return a string describing the data itself when printing a method: >>> df.describe() numeric n2 count 3.0 3.0 mean 2.0 3.0 std 1.0 1.0 min 1.0 2.0 25% 1.5 2.5 50% 2.0 3.0 75% 2.5 3.5 max 3.0 4.0 >>> df.describe().mean <bound method DataFrame.mean of numeric n2 count 3.0 3.0 mean 2.0 3.0 std 1.0 1.0 min 1.0 2.0 25% 1.5 2.5 50% 2.0 3.0 75% 2.5 3.5 max 3.0 4.0> >>> df.describe().mean() numeric 2.00 n2 2.75 dtype: float64 I assume this is what threw you off? You are not using the "results" of .mean in further code but were just looking at them, right?