Question

我有以下数据框：

df1 <- data.frame( id = c(1,2,2,3),
                   word = c("house, garden, flower", "flower, red", "garden, tree, forest", "house, window, door, red"),
                   value = c(10,12,20,5),
                   stringsAsFactors = FALSE
)

现在我想基于id整合行。因此，如果存在重复的id，则应合并列字中的值，并且应将列值相加。这意味着df应如下所示：

id | word                              | value
1  | house, garden, flower             | 10
2  | flower, red, garden, tree, forest | 32
3  | house, window, door, red          | 5

有人有想法，如何解决这个问题？

Answer 1

在基地R：

df1 <- data.frame( id = c(1,2,2,3),
                   word = c("house, garden, flower", "flower, red", "garden, tree, forest", "house, window, door, red"),
                   value = c(10,12,20,5),
                   stringsAsFactors = FALSE
)

want <- data.frame(id = unique(df1$id),
                   word = tapply(df1$word, df1$id, paste, collapse = ", "),
                   value = tapply(df1$value, df1$id, sum))
want

  id                              word value
1  1             house, garden, flower    10
2  2 flower, red, garden, tree, forest    32
3  3          house, window, door, red     5

Answer 2

使用tidyverse非常简单。只需按id分组，然后使用summarize函数生成所需的组变量：

library(tidyverse)
df1 %>%
    group_by(id) %>%
    dplyr::summarize(word = paste0(word, collapse=", "),
              value = sum(value))

     id word                              value
  <dbl> <chr>                             <dbl>
1     1 house, garden, flower                10
2     2 flower, red, garden, tree, forest    32
3     3 house, window, door, red              5

Answer 3

只需使用dplyr包：

library(dplyr)

df1 %>%
  group_by(id) %>%
  summarise(
    word = paste(word, collapse = ', '),
    value=sum(value)
  )

输出：

# A tibble: 3 x 3
     id word                              value
  <dbl> <chr>                             <dbl>
1    1. house, garden, flower               10.
2    2. flower, red, garden, tree, forest   32.
3    3. house, window, door, red             5.

R - 基于条件的和值和合并列

3 个答案: