[FIXED] Python pandas create new dataframe out of column entries

Issue

In the pandas package of python, how would one do the following the most easily?

df = pd.DataFrame({'Animal': ['Falcon', 'Falcon',
                              'Parrot', 'Parrot'],
                   'Max Speed': [380., 370., 24., 26.]})

Resulting in:

    Animal  Max Speed
0   Falcon  380.0
1   Falcon  370.0
2   Parrot  24.0
3   Parrot  26.0

Converting this into:

    Falcon  Parrot
0   380     24
1   370     26

I would have expected to able to use the groupby method, but I cannot seem to figure out how to create a new dataframe out of that.

df.groupby('Animal').to_frame() or something along those lines

edit: okay after some messing about I managed to find a solution in the form of:

df.groupby('Animal')['Max Speed'].apply(pd.DataFrame).apply(lambda x: pd.Series(x.dropna().to_numpy()))

But that seems to be quite clumsy, there is bound to be a better way right?

Solution

You can aggregate the values in lists during the groupby, convert to a dictionary, and then back to a DataFrame:

pd.DataFrame(dict(df.groupby('Animal')['Max Speed'].apply(list)))

Answered By - Arne