如何根据另一列的值聚合两列的 R dataframe

Question

我的dataframe如下，其中gender=="1"是指男性，gender=="2"是指女性，职业go从A到U，年份从2010年到2018年（我给你一个小例子）

Gender   Occupation    Year
1            A         2010
1            A         2010
2            A         2010
1            B         2010
2            B         2010
1            A         2011
2            A         2011
1            C         2011
2            C         2011

我想要一个 output ，它将性别、年份和职业不同的行数相加，如下所示：

Year | Occupation | Men | Woman
2010 |      A     |  2  |   1
2010 |      B     |  1  |   1
2011 |      A     |  1  |   1
2011 |      C     |  1  |   1

我尝试了以下方法：

Nr_gender_occupation <- data %>%
   group_by(year, occupation) %>%
   summarise(
      Men = aggregate(gender=="1" ~ occupation, FUN= count),
      Women = aggregate(gender=="2" ~ occupation, FUN=count)
)

Answer 1

我们可以使用“性别”中的索引来更改值，然后使用pivot_wider中的tidyr将数据重塑为“宽”格式

library(dplyr)
library(tidyr)
data %>%
 mutate(Gender = c("Male", "Female")[Gender]) %>%
 pivot_wider(names_from = Gender, values_from = Gender, values_fn = length)

-输出

# A tibble: 4 x 4
#  Occupation  Year  Male Female
#  <chr>      <int> <int>  <int>
#1 A           2010     2      1
#2 B           2010     1      1
#3 A           2011     1      1
#4 C           2011     1      1

---

或者使用带有unnest的table

library(tidyr)
data %>%
   group_by(Year, Occupation) %>%
   summarise(out = list(table(Gender)), .groups = 'drop') %>%     
   unnest_wider(out)

---

或者我们可以使用count和pivot_wider

data %>%
  count(Gender, Occupation, Year) %>%
  pivot_wider(names_from = Gender, values_from = n)

数据

data <- structure(list(Gender = c(1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L), 
    Occupation = c("A", "A", "A", "B", "B", "A", "A", "C", "C"
    ), Year = c(2010L, 2010L, 2010L, 2010L, 2010L, 2011L, 2011L, 
    2011L, 2011L)), class = "data.frame", row.names = c(NA, -9L
))

Answer 2

您还可以在您的组内进行计数：

library(dplyr)

df %>% 
  group_by(Occupation, Year) %>% 
  summarize(Men = sum(Gender == 1),
            Woman = sum(Gender == 2), .groups = "drop")

Output

  Occupation  Year   Men Woman
  <chr>      <dbl> <int> <int>
1 A           2010     2     1
2 A           2011     1     1
3 B           2010     1     1
4 C           2011     1     1

Answer 3

使用dcast的data.table选项

dcast(setDT(df), Year + Occupation ~ c("Men", "Woman")[Gender])

给

   Year Occupation Men Woman
1: 2010          A   2     1
2: 2010          B   1     1
3: 2011          A   1     1
4: 2011          C   1     1