如何将字符向量转换为变量名和str_count？答案

【问题标题】：How to convert character vector into variable names and str_count?如何将字符向量转换为变量名和str_count？
【发布时间】：2019-09-01 01:14:19
【问题描述】：

我正在尝试通过针对文本数据帧执行 str_count 的函数将术语的字符向量转换为变量，但我不知道该怎么做。

给定一个向量：

variablenames <- c("strong","weak","happy","sad")

和一个文本数据框，例如：

library(tidyverse)
textdf <- as.data.frame("Happy was a dwarf who was perpetually sad.") %>% rename(text = 1)

我认为我想要这样的东西：

countstring_fn <- function(variablenames,textdf){
for(term in variablenames){
paste0(term,"count") <- str_count(term,textdf)
}
}

但我很确定那是行不通的。预期的输出是：

text,strongcount,weakcount,happycount,sadcount
"Happy was a dwarf who was perpetually sad.",0,0,1,1

有没有人做过类似的事情并成功了？

【问题讨论】：

标签： r tidyverse stringr

【解决方案1】：

这是另一种方式。

library(tidyverse)
variablenames <- c("strong", "weak", "happy", "sad")
textdf <- tibble(
  text = c(
    '"Happy was a dwarf who was perpetually sad."',
    '"If you\'re strong, you\'re not weak."'
  )
)
textdf[, str_c(variablenames, 'count')] <- do.call(
  rbind, 
  lapply(
    textdf$text, 
    function(df) { 
      str_count(toupper(df), toupper(variablenames)) 
    }
  )
)
invisible(
  apply(
    textdf, 
    1, 
    function(vec) {
      cat(str_c(str_c(vec, collapse = ','), '\n'))
    }
  )
)

这里的主要区别在于 textdf 数据框中的字符串用双引号括起来（如果您从 .csv 导入数据，您可以调用 str_c('"', textdf$text, '"') 以获得相同的效果）。然后，我们将所有文本和模式转换为大写，以确保找到所有匹配项。最后，我们可以调用str_count() 来获取计数的整数向量，我们可以通过定义所需的列名将其单独分配给特定列。

prntFunc 函数然后使用 apply() 将数据框中的每一行打印到控制台（矢量化比使用 for 循环更快）：

"Happy was a dwarf who was perpetually sad.",0,0,1,1
"If you're strong, you're not weak.",1,1,0,0

我们首先使用str_c()，因为它具有折叠能力。换句话说，我们可以将一行中所有五列中的字符串连接成一个字符串，其中,作为分隔符。然后，对于cat()，我们需要再次使用str_c() 在每个“行字符串”的末尾附加一个换行符（\n）。最后，我们可以调用cat()，在控制台中显示带有特殊字符的字符串，例如"，不伴随转义字符（\）。 cat() 调用用 invisible() 包装，以抑制 NULL 在交互调用时附加到末尾的 cat()。

【讨论】：

【解决方案2】：

我们可以将text 转换为小写，并检查每个文本中variablenames 的出现，并返回一个逗号分隔的字符串。我们为每个 variablenames 添加单词边界 (\\b) 以避免将“sad”与“saddened”匹配。然后我们可以separate将数据放到不同的列中

library(tidyverse)

textdf %>%
   mutate(count = map_chr(tolower(text), function(x) 
    toString(map_int(paste0("\\b",variablenames,"\\b"), ~str_count(x, .x))))) %>%
  separate(count, into = paste0(variablenames, "_count"), sep = ",", convert = TRUE)

#                                        text strong_count weak_count happy_count sad_count
#1 Happy was a dwarf who was perpetually sad.            0          0           1         1

【讨论】：

【解决方案3】：

# added second row to show output of function

textdf <- structure(list(text = c("Happy was a dwarf who was perpetually sad.",
"Sad was a dwarf who was perpetually sad.")), row.names = c(NA,
-2L), class = "data.frame")

# counting the occurrences of words in 'variablenames'

pmap_df(
  textdf, function(text) {
    map(variablenames, ~ str_count(tolower(text), pattern = .)) %>%
    t %>% as.data.frame
  }
) %>%
  setNames(variablenames) %>%
  bind_cols(textdf, .)

# Leaves you with a data frame with counts for each word as columns.

                                        text strong weak happy sad
1 Happy was a dwarf who was perpetually sad.      0    0     1   1
2   Sad was a dwarf who was perpetually sad.      0    0     0   2

【讨论】：

【解决方案4】：

另一种方式：

library(tidyverse)

t(sapply(dat$strgs, str_count, pattern = coll(patts, T, 'en'))) %>%
  data.frame %>%
  set_names(., patts) %>%
  bind_cols(dat, .)

#   strgs                                strength ignorance present future collapse
# 1 War Is Peace, Freedom Is Slavery...  1        1         0       0      0
# 2 Who controls the past controls t...  0        0         1       1      0
# 3 The collapse of the USSR was the...  0        0         0       0      1

数据：

patts <- c("strength", "ignorance", "present", "future", "collapse")

dat <- data.frame(
  strgs = c(
    "War Is Peace, Freedom Is Slavery, and Ignorance Is Strength.",
    "Who controls the past controls the future: who controls the present controls the past.",
    "The collapse of the USSR was the greatest geopolitical catastrophe of the century."
  )
)

【讨论】：