Year to date vs Year to date last year | Pandas - python-2.7

Question

I would like to calculate the Year to date (YTD) value for this year and compare it to the same period last year in Pandas. My df looks like this:
Month Product A Product B
2015-01-01 24 62
2015-02-01 46 24
2015-03-01 30 70
2015-04-01 26 51
2015-05-01 34 42
2015-06-01 45 35
2015-07-01 25 13
2015-08-01 98 95
2015-09-01 6 81
2015-10-01 93 38
2015-11-01 98 59
2015-12-01 98 1
2016-01-01 67 42
2016-02-01 72 34
2016-03-01 7 6
2016-04-01 19 24
2016-05-01 82 38
2016-06-01 15 79
2016-07-01 49 83
2016-08-01 97 56
The two values i am after for product A are
YTD = 408 and YTD SPLY = 328 (Sum Jan-Aug 2016, Sum Jan-Aug 2015).
When a new month is added to the df, i would like the formula to calculate Jan-Sep and so on.
Any ideas how to proceed?

Answer 1

Not exactly sure what you want but it looks like you want to take the cumulative sum for each year.
df[['A_cumsum', 'B_cumsum']] = df.resample('A', on='Month').transform('cumsum')
Month Product A Product B A_cumsum B_cumsum
0 2015-01-01 24 62 24 62
1 2015-02-01 46 24 70 86
2 2015-03-01 30 70 100 156
3 2015-04-01 26 51 126 207
4 2015-05-01 34 42 160 249
5 2015-06-01 45 35 205 284
6 2015-07-01 25 13 230 297
7 2015-08-01 98 95 328 392
8 2015-09-01 6 81 334 473
9 2015-10-01 93 38 427 511
10 2015-11-01 98 59 525 570
11 2015-12-01 98 1 623 571
12 2016-01-01 67 42 67 42
13 2016-02-01 72 34 139 76
14 2016-03-01 7 6 146 82
15 2016-04-01 19 24 165 106
16 2016-05-01 82 38 247 144
17 2016-06-01 15 79 262 223
18 2016-07-01 49 83 311 306
19 2016-08-01 97 56 408 362