R过滤包含单词组合的行

Question

我正在处理文本数据，并寻找过滤问题的解决方案。

我设法找到一个解决方案，过滤包含'Word 1'或'Word 2'的行

这是可重现的代码

df=data.frame(UID=c(1,2,3,4,5),Text=c("the quick brown fox jumped over the lazy dog",
                                 "long live the king",
                                 "I love my dog a lot",
                                 "Tomorrow will be a rainy day",
                                 "Tomorrow will be a sunny day"))


#Filter for rows that contain "brown" OR "dog"
filtered_results_1=dplyr::filter(df, grepl('brown|dog', Text))

但是，当我筛选包含“Word 1”和“Word 2”的行时，它不起作用。

#Filter for rows that contain "brown" AND "dog"
filtered_results_2=dplyr::filter(df, grepl('brown & dog', Text))

无法找出这个的正确语法，任何帮助将不胜感激。

Answer 1

我们可以使用双grepl

dplyr::filter(df, grepl('\\bbrown\\b', Text) & grepl('\\bdog\\b', Text))

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或者使用一个条件，我们检查单词'brown'后跟'dog'一词（注意单词边界（\\b）以确保它与其他任何东西不匹配）或'dog'后跟'brown'

dplyr::filter(df, grepl("\\bbrown\\b.*\\bdog\\b|\\bdog\\b.*\\bbrown\\b", Text))
#   UID                                         Text
#1   1 the quick brown fox jumped over the lazy dog

注意：它检查字边界，单词'brown'，'dog'，字符串中是否存在两个字

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它也可以用base R完成

subset(df, grepl("\\bbrown\\b.*\\bdog\\b|\\bdog\\b.*\\bbrown\\b", Text))

Answer 2

你可以使用stringr::str_count：

dplyr::mutate(df, test = stringr::str_count(Text,'brown|dog'))
#   UID                                         Text test
# 1   1 the quick brown fox jumped over the lazy dog    2
# 2   2                           long live the king    0
# 3   3                          I love my dog a lot    1
# 4   4                 Tomorrow will be a rainy day    0
# 5   5                 Tomorrow will be a sunny day    0

dplyr::filter(df, stringr::str_count(Text,'brown|dog') == 2)
#   UID                                         Text
# 1   1 the quick brown fox jumped over the lazy dog

它会尽可能多地计算dog或brown

以下是更通用的，不如某些优雅，但您可以方便地将搜索到的单词放在向量中：

dplyr::filter(df, purrr::map_int(strsplit(as.character(Text),'[[:punct:] ]'),
               ~sum(unique(.) %in% c("brown","dog"))) == 2)

#   UID                                         Text
# 1   1 the quick brown fox jumped over the lazy dog

Answer 3

尝试此解决方案：

filtered_results_2=dplyr::filter(df, grepl('brown.*dog|dog.*brown', Text))
filtered_results_2
  UID                                         Text
1   1 the quick brown fox jumped over the lazy dog

Answer 4

使用sqldf：

library(sqldf)
sqldf("select * from df where Text like '%dog%' AND Text like '%brown%'")

输出：

    UID                                         Text
     1   1 the quick brown fox jumped over the lazy dog

Answer 5

与之前的答案类似，但使用base

df[grepl("(?=.*dog)(?=.*brown)", df$Text, perl = TRUE),]
  UID                                         Text
1   1 the quick brown fox jumped over the lazy dog