pandas How to add values in multiple rows based on value in one column

Question

I was just wondering if I could perform summation over multiple rows if they have same value for one column. For example, let's say I have a dataframe A:

A:
col1, col2, col3, col4
A     0.1    0.2  0.3
B     0.4   0.5   0.6
A     0.7   0.8   0.9
C     1.0    1.1   1.2

The end result should be:

col1, col2, col3, col4
A      0.8   1.0   1.2
B      0.4   0.5    0.6
C       1.0   1.1   1.2

This is because the first and third rows of the dataframe have the same value (A) for col1... How am I supposed to implement this?

Answer 1

In [83]: A.set_index('col1').sum(level=0)
Out[83]:
      col2  col3  col4
col1
A      0.8   1.0   1.2
B      0.4   0.5   0.6
C      1.0   1.1   1.2

or

In [152]: A.set_index('col1').sum(level=0).reset_index()
Out[152]:
  col1  col2  col3  col4
0    A   0.8   1.0   1.2
1    B   0.4   0.5   0.6
2    C   1.0   1.1   1.2

Answer 2

Use groupby with aggregation sum:

df1 = df.groupby('col1', as_index=False).sum()
print (df1)
  col1  col2  col3  col4
0    A   0.8   1.0   1.2
1    B   0.4   0.5   0.6
2    C   1.0   1.1   1.2

---

df1 = df.groupby('col1').sum().reset_index()
print (df1)
  col1  col2  col3  col4
0    A   0.8   1.0   1.2
1    B   0.4   0.5   0.6
2    C   1.0   1.1   1.2