在R中以长格式(相对于基组)按组计算跨行的增长率

发布于05月09日

我想在一个长格式的数据集中，按组(这里的组是"国家"和"年份")计算各行的增长率.由于增长率应与"基准"情景下的相同值(即相同的"国家"和相同的"年份")相关(而不是与前一行相关)，因此我将数据格式更改为宽格式，如下所示:

df <- spread(df, scenario, value) %>% 
    mutate(NDC_growth=((NDC/Baseline)-1)*100,
       `Partial BCA_growth`=((`Partial BCA`/Baseline)-1)*100,
       BCA_growth=((BCA/Baseline)-1)*100,
       `Full BCA_growth`=((`Full BCA`/Baseline)-1)*100 )

有没有办法用长格式来做？

以下是数据:

    df<- structure(list(country = c("CAN", "CAN", "CAN", "CAN", "CAN", 
"CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", 
"CAN", "NCOA", "NCOA", "NCOA", "NCOA", "NCOA"), year = c("2020", 
"2020", "2020", "2020", "2020", "2025", "2025", "2025", "2025", 
"2025", "2030", "2030", "2030", "2030", "2030", "2020", "2020", 
"2020", "2020", "2020"), scenario = c("Baseline", "BCA", "Full BCA", 
"NDC", "Partial BCA", "Baseline", "BCA", "Full BCA", "NDC", "Partial BCA", 
"Baseline", "BCA", "Full BCA", "NDC", "Partial BCA", "Baseline", 
"BCA", "Full BCA", "NDC", "Partial BCA"), value = c(50527.8708215592, 
50487.4619290311, 50485.0924261504, 50489.4453487844, 50486.1975947164, 
55845.9708589775, 55070.2745559464, 55133.107605613, 55153.4525662034, 
55065.0036253937, 61463.2383809614, 59893.8712077455, 59971.8726308887, 
59936.72156767, 59875.7762254252, 338418.917408225, 338420.617142445, 
338428.007621131, 338419.514027857, 338427.263672463)), row.names = c(NA, 
-20L), class = c("tbl_df", "tbl", "data.frame"))

df<- structure(list( country = c("CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "CAN", "NCOA", "NCOA", "NCOA", "NCOA", "NCOA"), year = c("2020", "2020", "2020", "2020", "2020", "2025", "2025", "2025", "2025", "2025", "2030", "2030", "2030", "2030", "2030", "2020", "2020", "2020", "2020", "2020"), scenario = c("Baseline", "BCA", "Full BCA", "NDC", "Partial BCA", "Baseline", "BCA", "Full BCA", "NDC", "Partial BCA", "Baseline", "BCA", "Full BCA", "NDC", "Partial BCA", "Baseline", "BCA", "Full BCA", "NDC", "Partial BCA"), value = c(50527.8708215592, 50487.4619290311, 50485.0924261504, 50489.4453487844, 50486.1975947164, 55845.9708589775, 55070.2745559464, 55133.107605613, 55153.4525662034, 55065.0036253937, 61463.2383809614, 59893.8712077455, 59971.8726308887, 59936.72156767, 59875.7762254252, 338418.917408225, 338420.617142445, 338428.007621131, 338419.514027857, 338427.263672463)), row.names = c(NA, -20L), class = c("tbl_df", "tbl", "data.frame")) suppressPackageStartupMessages(library(dplyr)) df %>% group_by(country, year) %>% mutate(growth = (value/first(value) - 1)*100) #> # A tibble: 20 × 5 #> # Groups: country, year [4] #> country year scenario value growth #> <chr> <chr> <chr> <dbl> <dbl> #> 1 CAN 2020 Baseline 50528. 0 #> 2 CAN 2020 BCA 50487. -0.0800 #> 3 CAN 2020 Full BCA 50485. -0.0847 #> 4 CAN 2020 NDC 50489. -0.0760 #> 5 CAN 2020 Partial BCA 50486. -0.0825 #> 6 CAN 2025 Baseline 55846. 0 #> 7 CAN 2025 BCA 55070. -1.39 #> 8 CAN 2025 Full BCA 55133. -1.28 #> 9 CAN 2025 NDC 55153. -1.24 #> 10 CAN 2025 Partial BCA 55065. -1.40 #> 11 CAN 2030 Baseline 61463. 0 #> 12 CAN 2030 BCA 59894. -2.55 #> 13 CAN 2030 Full BCA 59972. -2.43 #> 14 CAN 2030 NDC 59937. -2.48 #> 15 CAN 2030 Partial BCA 59876. -2.58 #> 16 NCOA 2020 Baseline 338419. 0 #> 17 NCOA 2020 BCA 338421. 0.000502 #> 18 NCOA 2020 Full BCA 338428. 0.00269 #> 19 NCOA 2020 NDC 338420. 0.000176 #> 20 NCOA 2020 Partial BCA 338427. 0.00247

在R中以长格式(相对于基组)按组计算跨行的增长率

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