Question

我正在处理文本数据，并正在寻找解决过滤问题的方法。

我设法找到一种解决方案，该解决方案可以过滤包含“ Word 1”的行 OR “ Word 2”

这是可复制的代码

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，当我过滤同时包含'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))

无法找到正确的语法，将不胜感激。

Answer 1

您可以使用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

它将计算dog或brown的次数，尽管它们发生的次数

以下内容比较笼统，不太优雅，但是您可以方便地将搜索到的单词放入向量中：

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 2

我们可以使用双grepl

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

或使用以下条件：我们先检查单词“ brown”（棕色），再检查单词“ dog”（狗）（注意单词边界（\\b）以确保它与其他任何内容都不匹配）或“ dog”其次是“棕色”

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：它将检查单词边界，单词“ brown”，“ dog”以及它们在字符串中是否存在

也可以使用base R

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

Answer 3

尝试以下解决方案：

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

类似于先前的答案，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

R过滤包含单词组合的行

5 个答案: