Pandas: Creating aggregated column in DataFrame

Question

With the DataFrame below as an example,

In [83]:
df = pd.DataFrame({\'A\':[1,1,2,2],\'B\':[1,2,1,2],\'values\':np.arange(10,30,5)})
df
Out[83]:
   A  B  val         


        

Answer 1

This is not so direct but I found it very intuitive (the use of map to create new columns from another column) and can be applied to many other cases:

gb = df.groupby('A').sum()['values']

def getvalue(x):
    return gb[x]

df['sum'] = df['A'].map(getvalue)
df