我想从列表列中提取元素并将它们存储为新列。我可以在函数之外执行此操作,但我无法在函数中使用它。
在下面的示例代码中,我希望行mutate(!!F_name := map(!!sum_name, ~.$statistic[[1]]))
从模型摘要列中提取测试统计信息并将其存储在新列中。这给出了评估错误$ operator is invalid for atomic vectors
。
aov_f1 <- function(df) {aov(value~ carb, data = df)}
aov_f2 <- function(df) {aov(value~ carb + gear, data = df)}
aov_sum_plus <- function(df, mod) {
mod <- enquo(mod)
sum_name <- paste0(quo_name(mod), "_sum")
F_name <-paste0(quo_name(mod), "_F")
df <- df %>%
mutate(!!sum_name := map(!! mod, broom::tidy)) %>%
mutate(!!F_name := map(!!sum_name, ~.$statistic[[1]]))
df
}
mtcars_n <- gather(mtcars, obs, value, mpg:qsec) %>%
group_by(obs) %>%
nest() %>%
mutate(aov1 = map(data, aov_f1)) %>%
mutate(aov2 = map(data, aov_f2)) %>%
aov_sum_plus(aov1) %>%
aov_sum_plus(aov2)
下面的等效代码给出了期望的结果。
aov_f1 <- function(df) {aov(value~ carb, data = df)}
aov_f2 <- function(df) {aov(value~ carb + gear, data = df)}
mtcars_n <- gather(mtcars, obs, value, mpg:qsec) %>%
group_by(obs) %>%
nest() %>%
mutate(aov1 = map(data, aov_f1)) %>%
mutate(aov2 = map(data, aov_f2)) %>%
mutate(aov1_sum = map(aov1, broom::tidy)) %>%
mutate(aov2_sum = map(aov2, broom::tidy)) %>%
mutate(aov1_sum_f = map_dbl(aov1_sum, ~.$statistic[[1]])) %>%
mutate(aov1_sum_p = map_dbl(aov1_sum, ~.$p.value[[1]])) %>%
mutate(aov2_sum_f = map_dbl(aov2_sum, ~.$statistic[[1]])) %>%
mutate(aov2_sum_p = map_dbl(aov2_sum, ~.$p.value[[1]]))
你没有把sum_name
变成一个字符串。这在map
中不起作用。您可以通过运行来检查:
debugfun <- function(df, mod) {
mod <- enquo(mod)
sum_name <- paste0(quo_name(mod), "_sum")
F_name <-paste0(quo_name(mod), "_F")
quo(df <- df %>%
mutate(!!sum_name := map(!! mod, broom::tidy),
!!F_name := map(!!sum_name, ~.$statistic[[1]])
)
)
}
gather(mtcars, obs, value, mpg:qsec) %>%
group_by(obs) %>%
nest() %>%
mutate(aov1 = map(data, aov_f1)) %>%
debugfun(aov1)
赠送:
<quosure> expr: ^df <- df %>% mutate("aov1_sum" := map(^aov1, broom::tidy), "aov1_F" := map("aov1_sum", ~.$statistic[[1]])) env: 0000015EF2AD5C88
这是一个需要的技巧!在整个表达式上使用quo
将为您翻译它。看着第二个map
,我们看到了字符串的问题。
您需要从字符串中创建符号(或名称)。您可以将它们添加到paste0
行:
aov_sum_plus <- function(df, mod) {
mod <- enquo(mod)
sum_name <- sym(paste0(quo_name(mod), "_sum"))
F_name <- sym(paste0(quo_name(mod), "_F"))
mutate(
df,
!!sum_name := map(!! mod, broom::tidy),
!!F_name := map_dbl(!!sum_name, ~.$statistic[[1]])
)
}
gather(mtcars, obs, value, mpg:qsec) %>%
group_by(obs) %>%
nest() %>%
mutate(aov1 = map(data, aov_f1)) %>%
aov_sum_plus(aov1)
# A tibble: 7 x 5 obs data aov1 aov1_sum aov1_F <chr> <list> <list> <list> <dbl> 1 mpg <tibble [32 x 5]> <S3: aov> <tibble [2 x 6]> 13.1 2 cyl <tibble [32 x 5]> <S3: aov> <tibble [2 x 6]> 11.5 3 disp <tibble [32 x 5]> <S3: aov> <tibble [2 x 6]> 5.55 4 hp <tibble [32 x 5]> <S3: aov> <tibble [2 x 6]> 38.5 5 drat <tibble [32 x 5]> <S3: aov> <tibble [2 x 6]> 0.249 6 wt <tibble [32 x 5]> <S3: aov> <tibble [2 x 6]> 6.71 7 qsec <tibble [32 x 5]> <S3: aov> <tibble [2 x 6]> 22.7