Adding multiple row values into one row keeping the index interval as same as the number of row adde-CodePudding

I have a data frame with multiple columns (30/40) in a time series continuously from 1 to 1440 minutes.

df

time   colA  colB   colC.....
1        5    4      3
2        1    2      3
3        5    4      3
4        6    7      3
5        9    0      3
6        4    4      0
..

Now I want to add two row values into one but I want to keep the interval of index 'time' same as the row number I am adding. The resulted data frame is:

df

time  colA  colB  colC.......
1       6    6     6
3       11   11    6
5       13    4    3
..

Here I added two row values into one but the time index interval is also same as 2 rows. 1,3,5... Is it possible to achieve that?

CodePudding user response：

one way is to do the addition for all and then fix time:

df_new = df[1::2].reset_index(drop=True)   df[::2].reset_index(drop=True)
df_new['time'] = df[::2]['time'].values

CodePudding user response：

Another way would be to group your data set every two rows and aggregate with using sum on your 'colX' columns and mean on your time column. Chaining astype(int) will round the resulting values:

d = {col: 'sum' for col in [c for c in df.columns if c.startswith('col')]}
df.groupby(df.index // 2).agg({**d,'time': 'mean'}).astype(int)

prints back:

   colA  colB  colC  time
0     6     6     6     1
1    11    11     6     3
2    13     4     3     5