Mixing
How to add a new column based on an aggregate function in pandas
0
I have a pandas dataframe as follows
A, B
----
a, 2
a, 5
a, 6
b, 1
b, 2
I'd like to groupby column A and sum up the values in column B and append it as another column and create the following dataframe
A, B, SUM
--------
a, 2, 13
a, 5, 13
a, 6, 13
b, 1, 3
b, 2, 3
How can I do that in pandas?
pandas group-by
asked Nov 22 '18 at 1:37
H.Z.H.Z.
1,80354392
add a comment |
0
I have a pandas dataframe as follows
A, B
----
a, 2
a, 5
a, 6
b, 1
b, 2
I'd like to groupby column A and sum up the values in column B and append it as another column and create the following dataframe
A, B, SUM
--------
a, 2, 13
a, 5, 13
a, 6, 13
b, 1, 3
b, 2, 3
How can I do that in pandas?
pandas group-by
asked Nov 22 '18 at 1:37
H.Z.H.Z.
1,80354392
add a comment |
0
0
0
I have a pandas dataframe as follows
A, B
----
a, 2
a, 5
a, 6
b, 1
b, 2
I'd like to groupby column A and sum up the values in column B and append it as another column and create the following dataframe
A, B, SUM
--------
a, 2, 13
a, 5, 13
a, 6, 13
b, 1, 3
b, 2, 3
How can I do that in pandas?
pandas group-by
asked Nov 22 '18 at 1:37
H.Z.H.Z.
1,80354392
I have a pandas dataframe as follows
A, B
----
a, 2
a, 5
a, 6
b, 1
b, 2
I'd like to groupby column A and sum up the values in column B and append it as another column and create the following dataframe
A, B, SUM
--------
a, 2, 13
a, 5, 13
a, 6, 13
b, 1, 3
b, 2, 3
How can I do that in pandas?
pandas group-by
pandas group-by
asked Nov 22 '18 at 1:37
H.Z.H.Z.
1,80354392
asked Nov 22 '18 at 1:37
H.Z.H.Z.
1,80354392
asked Nov 22 '18 at 1:37
H.Z.H.Z.
1,80354392
asked Nov 22 '18 at 1:37
H.Z.H.Z.
1,80354392
asked Nov 22 '18 at 1:37
H.Z.H.Z.
1,80354392
1,80354392
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
3
Using transform
df.assign(SUM=df.groupby('A').B.transform('sum'))
Out[15]:
A B SUM
0 a 2 13
1 a 5 13
2 a 6 13
3 b 1 3
4 b 2 3
answered Nov 22 '18 at 1:39
Wen-BenWen-Ben
112k83367
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
3
Using transform
df.assign(SUM=df.groupby('A').B.transform('sum'))
Out[15]:
A B SUM
0 a 2 13
1 a 5 13
2 a 6 13
3 b 1 3
4 b 2 3
answered Nov 22 '18 at 1:39
Wen-BenWen-Ben
112k83367
add a comment |
3
Using transform
df.assign(SUM=df.groupby('A').B.transform('sum'))
Out[15]:
A B SUM
0 a 2 13
1 a 5 13
2 a 6 13
3 b 1 3
4 b 2 3
answered Nov 22 '18 at 1:39
Wen-BenWen-Ben
112k83367
add a comment |
3
3
3
Using transform
df.assign(SUM=df.groupby('A').B.transform('sum'))
Out[15]:
A B SUM
0 a 2 13
1 a 5 13
2 a 6 13
3 b 1 3
4 b 2 3
answered Nov 22 '18 at 1:39
Wen-BenWen-Ben
112k83367
Using transform
df.assign(SUM=df.groupby('A').B.transform('sum'))
Out[15]:
A B SUM
0 a 2 13
1 a 5 13
2 a 6 13
3 b 1 3
4 b 2 3
answered Nov 22 '18 at 1:39
Wen-BenWen-Ben
112k83367
answered Nov 22 '18 at 1:39
Wen-BenWen-Ben
112k83367
answered Nov 22 '18 at 1:39
Wen-BenWen-Ben
112k83367
answered Nov 22 '18 at 1:39
Wen-BenWen-Ben
112k83367
112k83367
add a comment |
add a comment |
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