将 R 数据帧与字数（长度不等）合并 - 文本挖掘答案

【问题标题】：Merging R dataframes with word counts (of unequal length) - Text mining将 R 数据帧与字数（长度不等）合并 - 文本挖掘
【发布时间】：2021-01-04 12:06:23
【问题描述】：

对于我的文本挖掘任务，我正在尝试使用三个单独文本的字数（我已经过滤和标记化）创建一个矩阵。我知道每个文本都有这个数据框：

word          count
film             82
camera           18
director         10
action            5
character         2

我还创建了一个列表，将三个文本的所有单词组合在一起，字数组合在一起，但我试图达到这样的效果：

word           text1.       text2.        text3. 
film.             82.         16.           8
camera.           18.         76.           3
director.         10.          2.           91
character.        2.           20.          0
screen.           0.           4.           10
movie.            12.          0.           0
action.           5.           23.          54
dance.            0.           1.           16

为此使用什么代码？如上面的示例所示，我想为文本中没有出现数字“0”的每个单词填写。我总共有大约 4459 个单词，文本分别有 1804、1522 和 1133 个单词。

提前非常感谢！

【问题讨论】：

标签： r merge text-mining word-count

【解决方案1】：

如果您已经数过三张桌子。然后你只需要对这些表进行完全合并，然后删除 NA。喜欢

library(dplyr)

first <- data.frame(word = sample(letters, 10),
                count = sample(1:100, 10))

second <- data.frame(word = sample(letters, 10),
                count = sample(1:100, 10))

third <- data.frame(word = sample(letters, 10),
                count = sample(1:100, 10))

combined <- merge(first, second, by = "word", all = TRUE)
combined <- merge(combined, third, by = "word", all = TRUE)
  
combined %>% 
  mutate_all(.funs = function(x){
    ifelse(is.na(x),0, x)
  })

【讨论】：

【解决方案2】：

使用dplyr 和tidyr 的解决方案

library(dplyr)
library(tidyr)

full_join(df1, df2, by = "word", suffix = c(".text1", ".text2")) %>%
   full_join(., df3, by = "word") %>%
   rename(count.text3 = count) %>%
   mutate_at(vars(count.text1:count.text3), tidyr::replace_na, 0)
#>        word count.text1 count.text2 count.text3
#> 1      film          82          16           8
#> 2    camera          18          76           3
#> 3  director          10           2          91
#> 4    action           5          23          54
#> 5 character           2          20           0
#> 6    screen           0           4          10
#> 7     dance           0           1          16

模拟您的数据示例

df1 <- data.frame(
   word = c("film", "camera", "director", "action", "character"),       
   count = c(82, 18, 10, 5, 2)
)

df2 <- data.frame(
   word = c("film", "camera", "director", "character", "screen", "action", "dance"),       
   count = c(16, 76, 2, 20, 4, 23, 1)
)

df3 <- data.frame(
   word = c("film", "camera", "director", "screen", "action", "dance"),       
   count = c(8, 3, 91, 10, 54, 16)
)

【讨论】：