遍历数据框中的行并应用函数

Question

我创建了一个将数据帧作为输入的函数

df <- structure(list(flight="N912DE", origin_lon = -84.42778, origin_lat = 33.63667, 
dest_lon = -87.90667, dest_lat = 41.9744), class = "data.frame", 
row.names = c(NA, -1L))

get_coordinates <- function(df){
  n = 5
  df %>%
  pivot_longer(cols = c(-flight), 
               names_to = c('col', '.value'),
               names_sep = '_') %>%
   summarise(flight,
             lon = list(seq(max(lon), min(lon), length.out = n)), 
             lat = list(seq(min(lat), max(lat), length.out = n))) %>%
   unnest(cols = c(flight,lat, lon))
}

但我现在想对数据帧的每一行应用相同的函数，并将所有生成的数据帧绑定到一个数据帧中。

我尝试遍历行但无法弄清楚。

Answer 1

我们可以 group_split 按行顺序，然后 map 在 list 上应用函数

library(dplyr)#1.0.0
library(purrr)
df %>%
    group_split(rn = row_number(), .keep = FALSE)  %>% 
    map_dfr(get_coordinates)

Answer 2

考虑一个包含两行和唯一航班号的数据框：

d <- structure(list(flight = c("N912DE", "ANCD123"), origin_lon = c(-84.42778, 
     -85), origin_lat = c(33.63667, 33.63667), dest_lon = c(-87.90667, 
     -87.90667), dest_lat = c(41.9744, 41.9744)), 
      row.names = c(NA, -2L), class = "data.frame")

对于每个 flight，您可以在 summarise 中创建序列。

library(dplyr)
library(tidyr)

n <- 5
df %>%
  pivot_longer(cols = c(-flight), 
               names_to = c('col', '.value'),
               names_sep = '_') %>%
   group_by(flight) %>%
   summarise(lon = list(seq(max(lon), min(lon), length.out = n)), 
             lat = list(seq(min(lat), max(lat), length.out = n))) %>%
   unnest(cols = c(lat, lon))


# A tibble: 10 x 3
#   flight    lon   lat
#   <chr>   <dbl> <dbl>
# 1 ANCD123 -85    33.6
# 2 ANCD123 -85.7  35.7
# 3 ANCD123 -86.5  37.8
# 4 ANCD123 -87.2  39.9
# 5 ANCD123 -87.9  42.0
# 6 N912DE  -84.4  33.6
# 7 N912DE  -85.3  35.7
# 8 N912DE  -86.2  37.8
# 9 N912DE  -87.0  39.9
#10 N912DE  -87.9  42.0

遍历数据框中的行并应用函数

Iterate through rows in dataframe and apply function

r

function

rbind