英文:
Looping over groups in R
问题
我有一个df，包括一组数据框df1，df2和df3，每个数据框都遵循这个结构：
df1 <- data.frame(year = c("2013", "2013", "2013", "2013", "2013","2013"),site = c("a", "a", "a", "a", "a", "a"),trt = c("x", "y", "x", "y", "x", "y"),cover = c(2, 5, 1,20,50,12))df2 <- data.frame(year = c("2014", "2014", "2014", "2014", "2014","2014"),site = c("a", "a", "a", "a", "a", "a"),trt = c("x", "y", "x", "y", "x", "y"),cover = c(1, 3, 1,24,32,12))df3 <- data.frame(year = c("2015", "2015", "2015", "2015", "2015","2015"),site = c("a", "a", "a", "a", "a", "a"),trt = c("x", "y", "z", "z", "x", "y"),cover = c(2, 5, 1,2,11,32))df <- rbind(df1, df2, df3)dfyear site trt cover1 2013 a x 22 2013 a y 53 2013 a x 14 2013 a y 205 2013 a x 506 2013 a y 127 2014 a x 18 2014 a y 39 2014 a x 110 2014 a y 2411 2014 a x 3212 2014 a y 1213 2015 a x 214 2015 a y 515 2015 a z 116 2015 a z 217 2015 a x 1118 2015 a y 32
我过去常用for loop对每年的cover列进行排名。
v1 <- unique(df$year)lst <- list()for (i in seq_along(v1)) {lst[[i]] <- df |>filter(year == v1[i]) |>mutate(rank = dense_rank(desc(cover)))}
现在，我尝试对每年的每个组（在trt列中定义）的值进行排名，但我在想如何做到。我该如何使用for loop实现这个目标。我愿意使用lapply函数来得到答案，因为我想了解它。
英文:
I have a df including a set of data frames, df1, df2, and df3 where each data frame follow this structure:
df1 <- data.frame(year = c("2013", "2013", "2013", "2013", "2013","2013"),site = c("a", "a", "a", "a", "a", "a"),trt = c("x", "y", "x", "y", "x", "y"),cover = c(2, 5, 1,20,50,12))df2 <- data.frame(year = c("2014", "2014", "2014", "2014", "2014","2014"),site = c("a", "a", "a", "a", "a", "a"),trt = c("x", "y", "x", "y", "x", "y"),cover = c(1, 3, 1,24,32,12))df3 <- data.frame(year = c("2015", "2015", "2015", "2015", "2015","2015"),site = c("a", "a", "a", "a", "a", "a"),trt = c("x", "y", "z", "z", "x", "y"),cover = c(2, 5, 1,2,11,32))df <- rbind(df1, df2, df3)dfyear site trt cover1 2013 a x 22 2013 a y 53 2013 a x 14 2013 a y 205 2013 a x 506 2013 a y 127 2014 a x 18 2014 a y 39 2014 a x 110 2014 a y 2411 2014 a x 3212 2014 a y 1213 2015 a x 214 2015 a y 515 2015 a z 116 2015 a z 217 2015 a x 1118 2015 a y 32
I used to rank the values in the cover column for each year, using a for loop.
v1 <- unique(df$year)lst <- list()for (i in seq_along(v1)) {lst[[i]] <- df |>filter(year == v1[i]) |>mutate(rank = dense_rank(desc(cover)))}
Now, I am trying to rank the values of each group (as defined in the trt column) for each year, but I am having trouble figuring out how to do so. How can I do this with for loop. I am open to get an answer with lapply function as I would like to learn about it.
答案1
得分: 1
使用 dplyr，我们可以通过在 mutate 之前使用 group 来避免循环和过滤，然后使用 group_split 构建列表。
library(dplyr)df |>group_by(year) |>mutate(rank = dense_rank(desc(cover))) |>group_split()
输出：
[[1]]# 一个 tibble: 6 × 5year site trt cover rank<chr> <chr> <chr> <dbl> <int>1 2013 a x 2 52 2013 a y 5 43 2013 a x 1 64 2013 a y 20 25 2013 a x 50 16 2013 a y 12 3[[2]]# 一个 tibble: 6 × 5year site trt cover rank<chr> <chr> <chr> <dbl> <int>1 2014 a x 1 52 2014 a y 3 43 2014 a x 1 54 2014 a y 24 25 2014 a x 32 16 2014 a y 12 3[[3]]# 一个 tibble: 6 × 5year site trt cover rank<chr> <chr> <chr> <dbl> <int>1 2015 a x 2 42 2015 a y 5 33 2015 a z 1 54 2015 a z 2 45 2015 a x 11 26 2015 a y 32 1
英文:
Using dplyr, we can avoid the loop and the filtering by using group before mutate, and then construct the list using group_split.
library(dplyr)df |>group_by(year) |>mutate(rank = dense_rank(desc(cover))) |>group_split()
Output:
[[1]]# A tibble: 6 × 5year site trt cover rank<chr> <chr> <chr> <dbl> <int>1 2013 a x 2 52 2013 a y 5 43 2013 a x 1 64 2013 a y 20 25 2013 a x 50 16 2013 a y 12 3[[2]]# A tibble: 6 × 5year site trt cover rank<chr> <chr> <chr> <dbl> <int>1 2014 a x 1 52 2014 a y 3 43 2014 a x 1 54 2014 a y 24 25 2014 a x 32 16 2014 a y 12 3[[3]]# A tibble: 6 × 5year site trt cover rank<chr> <chr> <chr> <dbl> <int>1 2015 a x 2 42 2015 a y 5 33 2015 a z 1 54 2015 a z 2 45 2015 a x 11 26 2015 a y 32 1
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