pandas .diff() but use first cell as difference between last cell in prior column

say that i have a df in the following format:

year        2016  2017  2018  2019  2020  min  max    avg
month                                                    
2021-01-01   284   288   311   383   476  284  476  357.4
2021-02-01   301   315   330   388   441  301  441  359.6
2021-03-01   303   331   341   400   475  303  475  375.4
2021-04-01   283   300   339   419   492  283  492  372.6
2021-05-01   287   288   346   420   445  287  445  359.7
2021-06-01   283   292   340   424   446  283  446  359.1
2021-07-01   294   296   360   444   452  294  452  370.3
2021-08-01   294   315   381   445   451  294  451  375.9
2021-09-01   288   331   405   464   459  288  464  385.6
2021-10-01   327   349   424   457   453  327  457  399.1
2021-11-01   316   351   413   469   471  316  471  401.0
2021-12-01   259   329   384   467   465  259  467  375.7

and i would like to get the difference of the 2020 column by using df['delta'] = df['2020'].diff()

this will obviously return NaN for the first value in the column. how can i make it so that it automatically interprets that diff as the difference between the FIRST value of 2020 and the LAST value of 2019?

Answer

If you want only for 2020:

df["delta"] = pd.concat([df["2019"], df["2020"]]).diff().tail(len(df))

Prints:

          year  2016  2017  2018  2019  2020  min  max    avg  delta
0   2021-01-01   284   288   311   383   476  284  476  357.4    9.0
1   2021-02-01   301   315   330   388   441  301  441  359.6  -35.0
2   2021-03-01   303   331   341   400   475  303  475  375.4   34.0
3   2021-04-01   283   300   339   419   492  283  492  372.6   17.0
4   2021-05-01   287   288   346   420   445  287  445  359.7  -47.0
5   2021-06-01   283   292   340   424   446  283  446  359.1    1.0
6   2021-07-01   294   296   360   444   452  294  452  370.3    6.0
7   2021-08-01   294   315   381   445   451  294  451  375.9   -1.0
8   2021-09-01   288   331   405   464   459  288  464  385.6    8.0
9   2021-10-01   327   349   424   457   453  327  457  399.1   -6.0
10  2021-11-01   316   351   413   469   471  316  471  401.0   18.0
11  2021-12-01   259   329   384   467   465  259  467  375.7   -6.0