資料框看起來像這樣
df = data.frame(name = c("A","B","C"),
exam1 = c(2,6,4),
exam2 = c(3,5,6),
exam3 = c(5,3,3),
exam4 = c(1,NA,5))
我想提取每個“名稱”的前 3 名考試成績，并使用apply()或 dplyr rowwise()函式找到它們的平均值。
uj5u.com熱心網友回復：
使用apply,MARGIN = 1回圈遍歷數字列上的行sort，獲取head/tail依賴decreasing = TRUE/FALSE并回傳meaninbase R
apply(df[-1], 1, FUN = function(x) mean(head(sort(x, decreasing = TRUE), 3)))
[1] 3.333333 4.666667 5.000000
或與 dplyr/rowwise
library(dplyr)
df %>%
rowwise %>%
mutate(Mean = mean(head(sort(c_across(where(is.numeric)),
decreasing = TRUE), 3))) %>%
ungroup
# A tibble: 3 × 6
name exam1 exam2 exam3 exam4 Mean
<chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 A 2 3 5 1 3.33
2 B 6 5 3 NA 4.67
3 C 4 6 3 5 5
uj5u.com熱心網友回復：
這是一種使用旋轉和使用的替代方法top_n：這將只回傳前 3 個：
library(dplyr)
library(tidyr)
df %>%
pivot_longer(
-name,
names_to = "exam",
values_to = "value"
) %>%
group_by(name) %>%
top_n(3, value) %>%
mutate(mean = mean(value)) %>%
pivot_wider(
names_from = exam,
values_from = value
)
name mean exam1 exam2 exam3 exam4
<chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 A 3.33 2 3 5 NA
2 B 4.67 6 5 3 NA
3 C 5 4 6 NA 5
或者：
library(tidyr)
df %>%
pivot_longer(
-name,
names_to = "exam",
values_to = "value"
) %>%
group_by(name) %>%
top_n(3, value) %>%
summarise(mean = mean(value))
name mean
<chr> <dbl>
1 A 3.33
2 B 4.67
3 C 5
uj5u.com熱心網友回復：
使用purrr::pmap_dfr：
library(tidyverse)
df = data.frame(name = c("A","B","C"),
exam1 = c(2,6,4),
exam2 = c(3,5,6),
exam3 = c(5,3,3),
exam4 = c(1,NA,5))
df %>%
pmap_dfr(~ list(means = mean(sort(c(..2,..3,..4,..5), decreasing=T)[1:3]))) %>%
bind_cols(df,.)
#> name exam1 exam2 exam3 exam4 means
#> 1 A 2 3 5 1 3.333333
#> 2 B 6 5 3 NA 4.666667
#> 3 C 4 6 3 5 5.000000
另一種可能的解決方案，基于tidyr::pivot_longer和不使用rowwise：
library(tidyverse)
df = data.frame(name = c("A","B","C"),
exam1 = c(2,6,4),
exam2 = c(3,5,6),
exam3 = c(5,3,3),
exam4 = c(1,NA,5))
df %>%
pivot_longer(cols = 2:5, names_to = "names") %>%
group_by(name) %>%
slice_max(value, n=3) %>%
summarise(mean = mean(value)) %>%
inner_join(df)
#> Joining, by = "name"
#> # A tibble: 3 × 6
#> name mean exam1 exam2 exam3 exam4
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 A 3.33 2 3 5 1
#> 2 B 4.67 6 5 3 NA
#> 3 C 5 4 6 3 5
uj5u.com熱心網友回復：
我回到這個問題并嘗試使用“df”的基本 dplyr 操作，這也有效，就像早期帖子中的一些真正有用的解決方案一樣。
df_long <- df %>%
pivot_longer(cols = -name,
names_to = "exam",
values_to = "score")
df_long %>%
group_by(name) %>%
arrange(desc(score)) %>%
slice(1:3) %>%
summarise(mean_score = mean(score))
@Paul Smith 添加的好主意 inner_join(df)
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