calculating the contribution of a variable to the growth of a total in R-CodePudding

I am currently trying to compute the contribution of a variable to the growth of a total. The formula is the following : On the period T - T' : the contribution of variable X to the growth of the total variable Y is defined like follows :

(Xt/Yt)*((Xt'-Xt)/Xt)*100

Here is my dataset :

 structure(list(regroupement = c("Autres", "Ortho (  rhumato et rachis)", 
"Rachis", "Chirurgie digestive", "Ophtalmo", "Uro-néphro", "Gynéco", 
"ORL Stomato sf bouche et dent", "bouche et dents", "Tissus mou et chir plastique", 
"Chir thoracique et vasculaire", "Chir thoracique", "Chir esth et hors sécu", 
"Divers chir", "Gastro", "Endoscopies digestives", "Cardio Vasc (médecine)", 
"Pneumologie", "Neurologie", "Soins palliatifs", "Vasculaire interventionnel", 
"Divers médecine", "Accouchements", "Obstétrique autre (hors IVG)", 
"IVG", "Néo nat", "Séances autres", "Total"), actes_2019 = c(10, 
29520, 395, 14618, 5589, 6515, 4150, 866, 3458, 2137, 449, 0, 
575, 2180, 9179, 36079, 311, 388, 714, 4, 0, 6024, 4028, 294, 
292, 1, 1842, 129618), actes_2020 = c(8, 25451, 308, 12845, 4167, 
7376, 2994, 337, 2206, 2107, 437, 4, 575, 1477, 7933, 30192, 
218, 897, 267, 0, 11, 3740, 3348, 193, 118, 5, 737, 107951), 
    actes_2021 = c(18, 24055, 106, 13735, 5505, 8196, 3376, 352, 
    3035, 2571, 511, 8, 689, 1134, 6504, 42333, 161, 272, 138, 
    7, 0, 4682, 3226, 181, 82, 0, 61, 120938), sejours_2019 = c(4, 
    5493, 44, 2577, 2502, 1221, 852, 260, 1288, 540, 158, 0, 
    236, 397, 1631, 6992, 101, 63, 90, 1, 0, 1028, 1455, 148, 
    246, 1, 1820, 29148), sejours_2020 = c(2, 4946, 34, 2220, 
    1819, 1220, 574, 94, 801, 554, 140, 1, 221, 269, 1335, 5811, 
    79, 42, 58, 0, 1, 726, 1371, 109, 98, 5, 720, 23250), sejours_2021 = c(7, 
    5144, 21, 2523, 2416, 1451, 657, 111, 1106, 649, 162, 1, 
    278, 264, 1109, 7922, 69, 51, 30, 2, 0, 825, 1259, 108, 77, 
    0, 54, 26296)), row.names = c(4L, 5L, 6L, 7L, 8L, 9L, 10L, 
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 
24L, 25L, 26L, 27L, 28L, 29L, 30L, 1L), core = structure(list(
    regroupement = c("Autres", "Ortho (  rhumato et rachis)", 
    "Rachis", "Chirurgie digestive", "Ophtalmo", "Uro-néphro", 
    "Gynéco", "ORL Stomato sf bouche et dent", "bouche et dents", 
    "Tissus mou et chir plastique", "Chir thoracique et vasculaire", 
    "Chir thoracique", "Chir esth et hors sécu", "Divers chir", 
    "Gastro", "Endoscopies digestives", "Cardio Vasc (médecine)", 
    "Pneumologie", "Neurologie", "Soins palliatifs", "Vasculaire interventionnel", 
    "Divers médecine", "Accouchements", "Obstétrique autre (hors IVG)", 
    "IVG", "Néo nat", "Séances autres"), actes_2019 = c(10, 
    29520, 395, 14618, 5589, 6515, 4150, 866, 3458, 2137, 449, 
    0, 575, 2180, 9179, 36079, 311, 388, 714, 4, 0, 6024, 4028, 
    294, 292, 1, 1842), actes_2020 = c(8, 25451, 308, 12845, 
    4167, 7376, 2994, 337, 2206, 2107, 437, 4, 575, 1477, 7933, 
    30192, 218, 897, 267, 0, 11, 3740, 3348, 193, 118, 5, 737
    ), actes_2021 = c(18, 24055, 106, 13735, 5505, 8196, 3376, 
    352, 3035, 2571, 511, 8, 689, 1134, 6504, 42333, 161, 272, 
    138, 7, 0, 4682, 3226, 181, 82, 0, 61), sejours_2019 = c(4, 
    5493, 44, 2577, 2502, 1221, 852, 260, 1288, 540, 158, 0, 
    236, 397, 1631, 6992, 101, 63, 90, 1, 0, 1028, 1455, 148, 
    246, 1, 1820), sejours_2020 = c(2, 4946, 34, 2220, 1819, 
    1220, 574, 94, 801, 554, 140, 1, 221, 269, 1335, 5811, 79, 
    42, 58, 0, 1, 726, 1371, 109, 98, 5, 720), sejours_2021 = c(7, 
    5144, 21, 2523, 2416, 1451, 657, 111, 1106, 649, 162, 1, 
    278, 264, 1109, 7922, 69, 51, 30, 2, 0, 825, 1259, 108, 77, 
    0, 54)), class = "data.frame", row.names = 4:30), tabyl_type = "two_way", totals = 
"row", class = c("tabyl", 
"data.frame"))

I have computed for instance the contribution of the decline in the number of acts between 2020 and 2021 of the medical specialty "ortho" to the evolution of the total growth of the number of acts between these two years :

25451/107951 * ((24055 - 25451)/25451)*100

I would like to compute it for every specialty, on periods 2021-2020 and 2019-2021 in order to then plot a bar plot (not a stacked one), like the second one done here :

Explanation:

Remove the "Total" row (it's never a good/tidy idea to mix marginals with raw data; instead calculate marginals on the fly).
I randomly select some of the regroupement categories because keeping them all will give a very cluttered plot (you've got 28 categories).
Reshape actes_* columns from wide to long and convert the names to years by removing "actes_" and then using as.integer.
Calculate the quantity of interest; because data is in long format we can use group_by with diff to calculate this very easily as value / sum(value) * c(NA, diff(value)) / value. Note that since we group by regroupement, sum(value) is simply the total per regroupement. If you instead want the grand total (I am not so clear on this point), you need to remove the group_by() and ungroup() lines.
Plot as column plot with position = "dodge".