Regarding getting the rowsum of a python data frame

Question

I have following python data frame

data={'1':[1,1,1,1],'2':[1,1,1,1],'3':[1,1,1,1]}
df=pd.DataFrame(data)

I need to get the sum of the rows in a such away that my final output should be like this,

So in this desired output, the second column should contain the row sum up to second column of the original data frame. So on.

To get this output, I wrote the following code,

sum_mat=np.zeros(shape=(3,3))

numOfIteration=3
itr=list(range(0,numOfIteration))

for i in range(0,3):
    for j in range(0,3):
        while i <= itr[i]:
            sum_mat[i,j]+= df.iloc[i,j]

print (sum_mat)

I am not getting an output here because the code is running forever (may be an infinite loop).

Can anyone suggest anything to get the desired output ?

May be there is more effective and easier way to do the same thing.

Thank you

UPDATE: i update the for loop as follows,

for i in range(0,3):
   for j in range(0,3):
        while i <= itr[i]:
           sum_mat[i,j] = df.iloc[:,0:i].sum(axis=1)

but it gives following error,

sum_mat[i,j] = df.iloc[:,0:i].sum(axis=1)
ValueError: setting an array element with a sequence.

Answer 1

this could work also

for i,row in df.iterrows(): #go through each row
    df.loc[i]=df.loc[i].cumsum() #assign each row as the cumulative sum of the row

output:

>>> df
   1  2  3
0  1  2  3
1  1  2  3
2  1  2  3
3  1  2  3

EDIT

can just do :

df=df.cumsum(axis=1)