使用mutate和case_when定义的用户函数
使用mutate和case_when定义的用户函数
提问于 2019-12-01 01:48:39
我有学校级别的数据显示每个种族群体中学生的百分比(前黑人学生/学生总数)。
我的样本数据如下：
School Race perc_race
1 EnrollBlack 3
2 EnrollBlack 67
3 EnrollWhite 4
4 EnrollWhite 8
5 EnrollHis 55
6 EnrollHis 88
7 EnrollAsian 43
8 EnrollAsian 34我试图为每一个种族创建一个虚拟变量，显示一个学校属于哪个种族。例如，如果一所学校有20%的黑人学生，黑人的价值将是1，因为那所学校属于第一梯队。如果一所学校有67%的黑人，那么他们就会进入第三层，并在黑栏中有"3“。
School Race Percent_race black white hisp asian
1 EnrollBlack 3 1
2 EnrollBlack 67 3
3 EnrollWhite 4 1
4 EnrollWhite 8 1
5 EnrollHis 55 2
6 EnrollHis 88 3
7 EnrollAsian 43 2
8 EnrollAsian 3 4 2我可以为我的数据集中的每个种族重复这段代码，但是通过相应地替换比赛(即"EnrollWhite"，“EnrollHis”.)
mutate(black = case_when(race=='EnrollBlack' & perc_race>66.66 ~"3",
race=='EnrollBlack' & perc_race>33.33 ~"2",
race=='EnrollBlack' & perc_race<=33.33 ~"1"))而不是复制粘贴这5次，我试着想出一个用户-defined函数，像这样。
def_tercile <- function(x,y){
mutate(y = case_when(race=='x' & perc_race>66.66 ~"3",
race=='x' & perc_race>33.33 ~"2",
race=='x' & perc_race<=33.33 ~"1"))
}其中，data %>% def_tercile(EnrollWhite，White)将返回一个新列，该列定义了学校所属的“白色”terciles。
我不确定是否可以以这种方式在函数中使用dplyr (在运行函数时，dplyr会一直抛出错误)。我该怎么处理这件事有什么想法吗？
回答 1
Stack Overflow用户
回答已采纳
发布于 2019-12-01 02:02:17
library("tidyverse")
df <- read_table2("School Race perc_race
1 EnrollBlack 3
2 EnrollBlack 67
3 EnrollWhite 4
4 EnrollWhite 8
5 EnrollHis 55
6 EnrollHis 88
7 EnrollAsian 43
8 EnrollAsian 34")要得到33.33，我们只需除以1并添加1即可。
df %>%
group_by(Race) %>%
mutate(
tercile = 1 + perc_race %/% (100/3)
)
#> # A tibble: 8 x 4
#> # Groups: Race [4]
#> School Race perc_race tercile
#> <dbl> <chr> <dbl> <dbl>
#> 1 1 EnrollBlack 3 1
#> 2 2 EnrollBlack 67 3
#> 3 3 EnrollWhite 4 1
#> 4 4 EnrollWhite 8 1
#> 5 5 EnrollHis 55 2
#> 6 6 EnrollHis 88 3
#> 7 7 EnrollAsian 43 2
#> 8 8 EnrollAsian 34 2然后，我们可以使用pivot_wider给他们自己的列。
df %>%
group_by(Race) %>%
mutate(
tercile = 1 + perc_race %/% (100/3),
simple_race = Race %>% str_replace("Enroll", "") %>% str_to_lower()
) %>%
pivot_wider(names_from = simple_race, values_from = tercile)
#> # A tibble: 8 x 7
#> # Groups: Race [4]
#> School Race perc_race black white his asian
#> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 EnrollBlack 3 1 NA NA NA
#> 2 2 EnrollBlack 67 3 NA NA NA
#> 3 3 EnrollWhite 4 NA 1 NA NA
#> 4 4 EnrollWhite 8 NA 1 NA NA
#> 5 5 EnrollHis 55 NA NA 2 NA
#> 6 6 EnrollHis 88 NA NA 3 NA
#> 7 7 EnrollAsian 43 NA NA NA 2
#> 8 8 EnrollAsian 34 NA NA NA 2要回答关于dplyr函数的问题，您想要定义的函数可以这样编写。对于将race_name作为列名处理的函数，我们需要使用!!和:=语法。
def_tercile <- function(data, race_value, race_name) {
mutate(data,
!!race_name := case_when(
Race == race_value & perc_race > 66.66 ~ "3",
Race == race_value & perc_race > 33.33 ~"2",
Race == race_value & perc_race <= 33.33 ~"1")
)
}
df %>%
def_tercile("EnrollBlack", "black") %>%
def_tercile("EnrollWhite", "white") %>%
def_tercile("EnrollHis", "his") %>%
def_tercile("EnrollAsian", "asian")
#> # A tibble: 8 x 7
#> School Race perc_race black white his asian
#> <dbl> <chr> <dbl> <chr> <chr> <chr> <chr>
#> 1 1 EnrollBlack 3 1 NA NA NA
#> 2 2 EnrollBlack 67 3 NA NA NA
#> 3 3 EnrollWhite 4 NA 1 NA NA
#> 4 4 EnrollWhite 8 NA 1 NA NA
#> 5 5 EnrollHis 55 NA NA 2 NA
#> 6 6 EnrollHis 88 NA NA 3 NA
#> 7 7 EnrollAsian 43 NA NA NA 2
#> 8 8 EnrollAsian 34 NA NA NA 2 页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/59121882
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