how to groupby and aggregate dynamic columns in pandas

Question

I have following dataframe in pandas

code    tank     nozzle_1   nozzle_2    nozzle_var    nozzle_sale
123     1        1          1           10            10
123     1        2          2           12            10
123     2        1          1           10            10
123     2        2          2           12            10
123     1        1          1           10            10
123     2        2          2           12            10

Now, I want to generate cumulative sum of all the columns grouping over tank and take out the last observation. nozzle_1 and nozzle_2 columns are dynamic, it could be nozzle_3, nozzle_4....nozzle_n etc. I am doing following in pandas to get the cumsum

## Below code for calculating cumsum of dynamic columns nozzle_1 and nozzle_2
cols= df.columns[df.columns.str.contains(pat='nozzle_\d+$', regex=True)] 
df.assign(**df.groupby('tank')[cols].agg(['cumsum'])\
          .pipe(lambda x: x.set_axis(x.columns.map('_'.join), axis=1, inplace=False)))
## nozzle_sale_cumsum is static column
df[nozzle_sale_cumsum] = df.groupby('tank')['nozzle_sale'].cumsum()

From above code I will get cumsum of following columns

  tank  nozzle_1  nozzle_2  nozzle_var  nozzle_1_cumsum  nozzle_2_cumsum   nozzle_sale_cumsum
  1         1         1          10                1                1      10
  1         2         2          12                3                3      20
  2         1         1          10                1                1      10
  2         2         2          12                3                3      20
  1         1         1          10                4                4      30
  2         2         2          12                5                5      30

Now, I want to get last values of all 3 cumsum columns grouping over tank. I can do it with following code in pandas, but it is hard coded with column names.

 final_df= df.groupby('tank').agg({'nozzle_1_cumsum':'last',
                                   'nozzle_2_cumsum':'last',
                                   'nozzle_sale_cumsum':'last',
                                   }).reset_index()

Problem with above code is nozzle_1_cumsum and nozzle_2_cumsum is hard coded which is not the case. How can I do this in pandas with dynamic columns.

Answer 1

How about:

df.filter(regex='_cumsum').groupby(df['tank']).last()

Output:

      nozzle_1_cumsum  nozzle_2_cumsum  nozzle_sale_cumsum
tank                                                      
1                   4                4                  30
2                   5                5                  30

You can also replace df.filter(...) by, eg, df.iloc[:,-3:] or df[col_names] .