For each row, how to sum values for columns start with same string

Question

Edit: the column names indeed start with more than 1 character, but with a sep='_', it's more like AAA_BBB, AAA_DDD, BBB_EEE, BBB_FFF, ...

Thanks for the groupby solutions!

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I have a pandas dataframe like this (borrowed from another question):

df =

C1    C2    T3  T5
28    34    11  22
45    100   33  66

How can I get a new dataframe, with sum of columns that have the same "starting string", e.g. "C", "T" ? Thanks!

df =

C     T  
62    33    
145   99

Unfortunately I have to deal with this structure of dataframe, and there are about 1000 columns in the dataframe, looks like A1,A2,A3,B1,B2,B3, ...

Answer 1

Use,

 df.groupby(df.columns.str[0], axis=1).sum()

Output:

     C   T
0   62  33
1  145  99