我有两个数据集。第一个列表包含城市及其距目的地的距离(以英里为单位)的列表。第二个列表包含目的地。我想使用purrr将最近目的地的名称放入第一个数据集中的新列中。
这是第一个数据集(由数据/距离组成):
library(tidyverse)
data1 <- tibble(city = c("Atlanta", "Tokyo", "Paris"),
dist_Rome = c(1000, 2000, 300),
dist_Miami = c(400, 3000, 1500),
dist_Singapore = c(3000, 600, 2000),
dist_Toronto = c(900, 3200, 1900))
这是带有目的地的第二个数据集:
library(tidyverse)
data2 <- tibble(destination = c("Rome Italy", "Miami United States", "Singapore Singapore", "Toronto Canada"))
这就是我想要的样子:
library(tidyverse)
solution <- tibble(city = c("Atlanta", "Tokyo", "Paris"),
dist_Rome = c(1000, 2000, 300),
dist_Miami = c(400, 3000, 1500),
dist_Singapore = c(3000, 600, 2000),
dist_Toronto = c(900, 3200, 1900),
nearest = c("Miami United States", "Singapore Singapore", "Rome Italy"))
理想情况下,我正在寻找一个整洁的解决方案,而我尝试使用purrr做到这一点,但无济于事。这是我失败的尝试:
library(tidyverse)
solution <- data1 %>%
mutate(nearest_hub = map(select(., contains("dist")), ~
case_when(which.min(c(...)) ~ data2$destination),
TRUE ~ "NA"))
Error in which.min(c(...)) :
(list) object cannot be coerced to type 'double'
谢谢!
答案 0 :(得分:2)
我们可以将gather
转换为'long'格式,按'city'分组,slice
最小'val'的行,left_join
和'data2'以获得'nearest '
library(tidyverse)
data1 %>%
gather(key, val, starts_with("dist")) %>%
group_by(city) %>%
slice(which.min(val)) %>%
ungroup %>%
transmute(city, key = str_remove(key, 'dist_')) %>%
left_join(data2 %>%
mutate(key = word(destination, 1))) %>%
select(city, nearest = destination) %>%
left_join(data1)
答案 1 :(得分:2)
使用tidyverse
的解决方案。
library(tidyverse)
data3 <- data1 %>%
mutate(City = apply(data1 %>% select(-city), 1, function(x) names(x)[which.min(x)])) %>%
mutate(City = str_remove(City, "^dist_")) %>%
left_join(data2 %>%
separate(destination, into = c("City", "Country"), sep = " ", remove = FALSE),
by = "City") %>%
select(-City, -Country) %>%
rename(nearest = destination)
data3
# # A tibble: 3 x 6
# city dist_Rome dist_Miami dist_Singapore dist_Toronto nearest
# <chr> <dbl> <dbl> <dbl> <dbl> <chr>
# 1 Atlanta 1000 400 3000 900 Miami United States
# 2 Tokyo 2000 3000 600 3200 Singapore Singapore
# 3 Paris 300 1500 2000 1900 Rome Italy