Question

我有一个数据框：

source= c("A", "A", "B") 
target = c("B", "C", "C") 
source_A = c(5, 5, 6) 
target_A = c(6, 7, 7) 
source_B = c(10, 10, 11)
target_B = c(11, 12, 12) 
c = c(0.5, 0.6, 0.7) 
df = data.frame(source, target, source_A, target_A, source_B, target_B, c) 

> df
  source target source_A target_A source_B target_B   c
1      A      B        5        6       10       11 0.5
2      A      C        5        7       10       12 0.6
3      B      C        6        7       11       12 0.7

如何减少此数据框以仅返回唯一源和目标值的值并返回（忽略列c）。

对于值[A B C]

此刻我做了类似的事情：

df1 <- df[,c("source","source_A", "source_B")]
df2 <- df[,c("target","target_A", "target_B")]

names(df1)[names(df1) == 'source'] <- 'id'
names(df1)[names(df1) == 'source_A'] <- 'A'
names(df1)[names(df1) == 'source_B'] <- 'B'
names(df2)[names(df2) == 'target'] <- 'id'
names(df2)[names(df2) == 'target_A'] <- 'A'
names(df2)[names(df2) == 'target_B'] <- 'B'

df3 <- rbind(df1,df2)
df3[!duplicated(df3$id),]

  id A  B
1  A 5 10
3  B 6 11
5  C 7 12

实际上，我有数十个专栏，所以这是长期不可行的。

我怎样才能更简洁地做到这一点（理想情况下，更多列可以推广）？

Answer 1

library(dplyr)
library(magrittr)

df1 <- subset(df, select = ls(pattern = "source"))
df2 <- subset(df, select = ls(pattern = "target"))

names(df1) <- names(df2)
df <- bind_rows(df1, df2)
df %<>% group_by(target, target_A, target_B) %>% slice(1)

这应该这样做，但我不太清楚你想如何概括它。我不认为这是世界上最优雅的解决方案，但它有助于达到目的。希望您打算使用的列可以通过列名字符串模式进行定位！

Answer 2

这是一个使用dplyr函数的更通用的方法。您基本上需要将所有内容收集到一个长格式中，您可以相应地重命名该变量，然后将它们重新分配到id, A, B：

library(dplyr)
library(tidyr)

df %>% 
  select(-c) %>% 
  mutate(index = row_number()) %>% 
  gather(key , value, -index) %>%  
  separate(key, c("type", "name"), fill = "right") %>% 
  mutate(name = ifelse(is.na(name), "id", name)) %>% 
  spread(key = name, value = value) %>% 
  select(id, matches("[A-Z]", ignore.case = FALSE)) %>% 
  distinct

R Dataframe - 从列中提取唯一行

2 个答案: