Ggtcf

I have made my own userdefined function in Python. The input are some parameters and a dataframe. First some new variables are added to the input dataframe. Then I try to make a groupby on the dataframe and left join the result on to the dataframe.

But the dataframe don't get the groupby variables added.

 def test(df, params):

 df['b']=df['a']*params['some_parameter']
 df['c']=df['b']*df['total']

 aaa=df.groupby(['aa', 'bb']).agg('c':'sum')
 df=pd.merge(df,a,how='left',on=['aa', 'bb'])

 return 

Next try:

def test(df, params):

df['b']=df['a']*params['some_parameter']
df['d']=df['c']*df['b']

aaa=df.groupby(['y','x']).agg('d':'sum','g':'sum').add_suffix('_sum')
df=df.join(aaa, on=['y','x']) 

return 

I then call the function by:
test(df2,params)

I would expect df2 would have 4 new columns, b, d, d_sum and g_sum. But it only has 2 new columns, b and d.

You can use GroupBy.transform instaed groupby with left join by merge:

aaa=df.groupby(['aa', 'bb']).agg('c':'sum')
df=pd.merge(df,a,how='left',on=['aa', 'bb'])

to:

df['c1'] = df.groupby(['aa', 'bb'])['c'].transform('sum')

All together:

def test(df, params):

 df['b']=df['a']*params['some_parameter']
 df['c']=df['b']*df['total']

 df['new'] = df.groupby(['aa', 'bb'])['c'].transform('sum')

 return df

If need aggregate multiple columns is possible use DataFrame.join with default left join:

df = pd.DataFrame(
 'x':list('dddddd'),
 'y':list('aaabbb'),
 'a':[4,5,4,5,5,4],
 'b':[7,8,9,4,2,3],
 'c':[1,3,5,7,1,0],
 'd':[5,3,6,9,2,4],
 'g':[1,3,6,4,4,3],
)

print (df)
 x y a b c d g
0 d a 4 7 1 5 1
1 d a 5 8 3 3 3
2 d a 4 9 5 6 6
3 d b 5 4 7 9 4
4 d b 5 2 1 2 4
5 d b 4 3 0 4 3

params = 'some_parameter':100

def test(df, params):

 df['b']=df['a']*params['some_parameter']
 df['d']=df['c']*df['b']

 aaa=df.groupby(['y','x']).agg('d':'sum','g':'sum').add_suffix('_sum')
 df=df.join(aaa, on=['y','x']) 

 return df

df1 = test(df, params)
print (df1)
 x y a b c d g d_sum g_sum
0 d a 4 400 1 400 1 3900 10
1 d a 5 500 3 1500 3 3900 10
2 d a 4 400 5 2000 6 3900 10
3 d b 5 500 7 3500 4 4000 11
4 d b 5 500 1 500 4 4000 11
5 d b 4 400 0 0 3 4000 11