在dplyr中按组查找最接近x的值 [英] find value closest to x by group in dplyr

问题描述

library(dplyr)
a <- data_frame(id = c("A","A","A","B","B","B"),
                b = c(1.2, 1.5, 1.8, 1.1, 1.6, 1.4))

现在，我想为id中的每个类别检索最接近1.43的值。
我想我可以使用：

Now, I´d like to retrieve the values closest to 1.43 for each of the catergories in id. I thought I could use:

a %>% group_by(id) %>% nth(which.min(abs(.$b-1.43)))

但dplyr声明

Error: Don't know how to generate default for object of class grouped_df/tbl_df/tbl/data.frame

推荐答案

which.min（）返回数值（或逻辑）向量的（第一个）最小值或最大值的索引。如果有多个相等的值，彼此之间的距离接近1.43，并且您想保留所有这些值，则可以使用 filter（）：

which.min() returns the index of the (first) minimum or maximum of a numeric (or logical) vector. If there are multiple equal values as close to 1.43 as each other and you want to keep all of them, you can use filter():

a %>% group_by(id) %>% filter(abs(b - 1.43) == min(abs(b - 1.43)))

#Source: local data frame [2 x 2]
#Groups: id [2]

#     id     b
#  <chr> <dbl>
#1     A   1.5
#2     B   1.4

---

如果您喜欢使用 nth（）函数，并且每个组只有一个值是可以的，则可以将其包装在摘要中函数，以便将其应用于每个组，并且根据？nth（），还需要将向量作为参数传递给函数：

---

If you prefer sticking with the nth() function, and it is OK to have only one value for each group, you can wrap it within a summarize function so that it will be applied to each group, and also according to ?nth(), you need to pass the vector to the function as an argument as well:

a %>% group_by(id) %>% summarise(b = nth(b, which.min(abs(b-1.43))))

# A tibble: 2 × 2
#     id     b
#  <chr> <dbl>
#1     A   1.5
#2     B   1.4

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