计算各自列中的关键字数量

假设我有这样的数据：

df <-  read.table(text= "title     date    text
blablabla   22.07.2023  'blablablabla Blue blablabla'
blablabla   23.06.2023  'bala Blue blabla Blue Night Blue'
blablabla   23.08.2023  'bala Mountain blabla House Night Blue'", 
header = T, stringsAsFactor = F) 

和一个向量words我考虑的关键词：

words <- c("House", "Mountain", "Blue", "Night")

我想要实现的是计算次数words发生在df$text but 计算每种类型的word分别在自己的专栏中。到目前为止我有这个代码：

llibrary(tidyverse)
df %>%
  # extract instances of keywords:
  mutate(
    keyword = str_extract_all(text, 
                              str_c("(?i)\\b(", str_c(words, collapse = "|"), ")\\b")
  )) %>%
  # turn into alternation pattern:
  mutate(keyword = lapply(keyword, function(x) str_c(x, collapse = "|"))) %>%
  # create row ID:
  mutate(row = row_number()) %>%
  # separate into rows splitting by `|`:
  separate_rows(keyword, sep = '\\|') %>% 
  # cast each keyword in its own row:
  pivot_wider(names_from = keyword, values_from = keyword, 
              values_fn = function(x) 1, values_fill = 0
              ) %>%
  select(-row)
# A tibble: 3 × 7
  title     date       text                                   Blue Night Mountain House
  <chr>     <chr>      <chr>                                 <dbl> <dbl>    <dbl> <dbl>
1 blablabla 22.07.2023 blablablabla Blue blablabla               1     0        0     0
2 blablabla 23.06.2023 bala Blue blabla Blue Night Blue          1     1        0     0
3 blablabla 23.08.2023 bala Mountain blabla House Night Blue     1     1        1     1

这不是我想要的，因为function(x) 1部分并不总结，而只是记录是否word存在或不存在。必须如何更改才能获得此输出：

# A tibble: 3 × 7
  title     date       text                                   Blue Night Mountain House
  <chr>     <chr>      <chr>                                 <dbl> <dbl>    <dbl> <dbl>
1 blablabla 22.07.2023 blablablabla Blue blablabla               1     0        0     0
2 blablabla 23.06.2023 bala Blue blabla Blue Night Blue          3     1        0     0
3 blablabla 23.08.2023 bala Mountain blabla House Night Blue     1     1        1     1

选择，split在空间上，设置factor级别，获取频率table:

cbind(df[ "text" ],
      t(sapply(strsplit(df$text, " ", fixed = TRUE), 
               function(i) table(factor(i, levels = words))))
      )
#                                    text House Mountain Blue Night
# 1           blablablabla Blue blablabla     0        0    1     0
# 2      bala Blue blabla Blue Night Blue     0        0    3     1
# 3 bala Mountain blabla House Night Blue     1        1    1     1

或者要修复您的解决方案，请使用length:

#...
pivot_wider(names_from = keyword, values_from = keyword, 
            values_fn = length, values_fill = 0)
#...