r 在 2 列上滚动自定义函数

Question

我想在一个数据框上滚动一个使用两个数据列的自定义函数。我知道如何用一个数据列做到这一点，但我不能完全解决两个问题。 （真实的数据框要大得多。）

my_df <- data.frame("id"=c("151", "143", "199", "122", "156"), 
                "person"=c("mother", "father", "grandma", "child", "sister", "mother", "grandma", "grandma", "father", "mother","mother", "mother", "grandma", "child", "sister", "mother", "mother", "grandma", "father", "mother", "mother", "mother", "mother", "mother", "mother"))

my_new_df <- my_df %>%
group_by(id) %>% # first I subset by ID number
mutate(total = n()) # calculate the total number of observations per ID
filter(person=='mother') %>% # then I filter the observations I want to know about
mutate(n_mother = n()) %>% calculate the # of 'mother' observations per ID
mutate(prop_mother = rollapply(n_mother/total, width=1, FUN=(??)) # Here I get stuck - I want the proportion of 'mother' observations updated for every observation from this ID number

我是否编写自定义函数以在管道内调用？

calculate_mother = function(n_mother){
   return(n_mother / total)
}

在此之后，我还想计算 prop_mother 的滚动均值和方差，但在我实际计算 prop_mother 之前我不能这样做

Answer 1

我会尝试这样的：

#count is group_by and n rolled into one
all_ids <- my_df %>% count(id)

mom_ids <- my_df %>% filter(person=='mother') %>% count(id,name = "n_mother")

my_new_df <- full_join(all_ids,mom_ids)

my_new_df$n_mother[is.na(my_new_df$n_mother)] <- 0

my_new_df$prop_mother <- my_new_df$n_mother/my_new_df$n

Answer 2

您正在寻找这样的东西吗？我无法确定要订购的东西，因为“滚动”计算所需的 ID 是为母亲重复的……或者您也可以按 ID 分组，而不仅仅是人

library(dplyr)

my_new_df <- my_df %>%
  dplyr::group_by(id) %>% 
  dplyr::mutate(total = n())  %>% 
  dplyr::mutate(n_mother = n()) %>%
  dplyr::group_by(person) %>%
  dplyr::mutate(prop_mother = n_mother/sum(total),
                roll_prop_mother = cumsum(prop_mother))