如何在 R 中找到某些行的总和以获得每行的总计？

Question

我有一个包含每个月员工容量的数据集，我想获得每个员工在所有月份的总数：

library(dplyr)
data <- tibble(employee = c("Justin", "Corey","Sibley", "Justin", "Corey","Sibley"),
               education = c("graudate", "student", "student", "graudate", "student", "student"),
               fte_max_capacity = c(1, 2, 3, 1, 2, 3),
               project = c("big", "medium", "small", "medium", "small", "small"),
               aug_2021 = c(1, 1, 1, 1, 1, 1),
               sep_2021 = c(1, 1, 1, 1, 1, 1),
               oct_2021 = c(1, 1, 1, 1, 1, 1),
               nov_2021 = c(1, 1, 1, 1, 1, 1))

我已尝试使用找到的代码 here 进行跟踪，但出现此错误：

data %>%
  dplyr::select(-contains("project")) %>%
  dplyr::group_by(employee) %>%
  mutate(sum = rowSums(select(., vars(contains("_20")))))

Error: Problem with `mutate()` input `sum`.
x Must subset columns with a valid subscript vector.
x Subscript has the wrong type `quosures`.
ℹ It must be numeric or character.
ℹ Input `sum` is `rowSums(select(., vars(contains("_20"))))`.
ℹ The error occurred in group 1: employee = "Corey".

我还尝试了此website 中解决方案的修改版本。但我也得到一个错误，尽管所有相关的列都是数字：

data %>%
  dplyr::select(-contains("project")) %>%
  dplyr::group_by(employee) %>%
  mutate_at(vars(contains("_20"), rowSums(., na.rm = T)))

Error: 'x' must be numeric

Answer 1

这是一个分组数据，使用cur_data()做select，否则分组变量也会作为属性出现，从而导致错误

library(dplyr)
data %>%
  dplyr::select(-contains("project")) %>%
  dplyr::group_by(employee) %>%
  dplyr::mutate(sum = sum(rowSums(select(cur_data(), contains("_20"))))) %>%
  ungroup

-输出

# A tibble: 6 x 8
  employee education fte_max_capacity aug_2021 sep_2021 oct_2021 nov_2021   sum
  <chr>    <chr>                <dbl>    <dbl>    <dbl>    <dbl>    <dbl> <dbl>
1 Justin   graudate                 1        1        1        1        1     8
2 Corey    student                  2        1        1        1        1     8
3 Sibley   student                  3        1        1        1        1     8
4 Justin   graudate                 1        1        1        1        1     8
5 Corey    student                  2        1        1        1        1     8
6 Sibley   student                  3        1        1        1        1     8