如何基于字符串向量中的两类关键词重编码生成新向量？

示例数据 #

data <- tibble::tibble(
  w = c("Strongly disagree", "Somewhat disagree", "Disagree", "Somewhat agree", "Strongly agree", "Agree"),
  x = c("Definitely true", "Probably true", "Somewhat false", "Definitely false", "Definitely true", "Definitely false"),
  y = c("Definitely not doing enough", "Definitely doing enough", "Possibly not doing enough", "Possibly doing enough", "Definitely not doing enough", "Somehat doing enough"),
  z = c("Very comfortable", "Comfortable", "Somewhat comfortable", "Very uncomfortable", "Somewhat uncomfortable", "Comfortable")
)

需求说明 #

每列字符串包含两类特定关键词（如w列的agree/disagree），需要生成仅保留这些关键词的新向量，处理后w列预期结果：

[1] "Disagree" "Disagree" "Disagree" "Agree" "Agree" "Agree"

现有代码问题 #

原函数make_dicho在处理无前缀的单关键词字符串（如"Disagree"）时返回NA，原因是正则表达式(?<=\s).+仅匹配空格后的内容，无空格时无法匹配：

# 原函数
make_dicho <- function(df = data, var) {
  
  df %>% 
    dplyr::pull({{ var }}) %>% 
    haven::as_factor() %>% 
    stringr::str_extract("(?<=\\s).+") %>%
    stringr::str_to_sentence()
  
}

# 测试结果（存在NA）
data %>% make_dicho(., w)
# [1] "Disagree" "Disagree" NA         "Agree"    "Agree"    NA  

解决方案 #

修改函数逻辑，直接匹配目标关键词而非依赖空格，同时支持不区分大小写的匹配，确保所有包含关键词的字符串都能被正确提取：

改进后的通用函数 #

make_dicho <- function(var, pattern) {
  var %>%
    haven::as_factor() %>%
    # 不区分大小写匹配目标关键词
    stringr::str_extract(stringr::regex(pattern, ignore_case = TRUE)) %>%
    # 统一格式为首字母大写
    stringr::str_to_sentence()
}

在dplyr::mutate中使用 #

针对不同列传入对应的关键词模式：

processed_data <- data %>%
  mutate(
    w_dicho = make_dicho(w, "agree|disagree"),
    x_dicho = make_dicho(x, "true|false"),
    y_dicho = make_dicho(y, "doing enough|not doing enough"),
    z_dicho = make_dicho(z, "comfortable|uncomfortable")
  )

测试验证 #

处理w列的结果：

processed_data %>% pull(w_dicho)
# [1] "Disagree" "Disagree" "Disagree" "Agree"    "Agree"    "Agree"

所有单关键词的情况都能正确提取，不再返回NA。

内容的提问来源于stack exchange，提问作者jdenn0514