根据单独列中的字符串匹配有条件地替换多列中的值

Question

我正在尝试根据不同列中的字​​符串匹配有条件地替换多列中的值，但我希望能够使用 cross() 函数在一行代码中执行此操作，但我不断得到对我来说不太有意义的错误。我觉得这可能是一个简单的解决方案，所以如果有人能指出我正确的方向，那就太棒了！

df <- data.frame("type" = c("Park", "Neighborhood", "Airport", "Park", "Neighborhood", "Neighborhood"),
               "total" = c(34, 56, 75, 89, 21, 56),
               "group_a" = c(30, 26, 45, 60, 3, 46),
               "group_b" = c(4, 30, 30, 29, 18, 10))

# working but not concise
df %>%
  mutate(total = ifelse(str_detect(type, "Park"), NA, total),
         group_a = ifelse(str_detect(type, "Park"), NA, group_a),
         group_b = ifelse(str_detect(type, "Park"), NA, group_b))

  
# concise but not working
df %>% mutate(across(total, group_a, group_b), ifelse(str_detect(type, "Park"), NA, .))

更新

我们的解决方案适用于我的虚拟数据集，但不适用于我的真实数据，因此我将分享我的真实数据框的一个小 sn-p，其中数字已更改并隐藏了组织名称。当我对这些数据运行这行代码 (df %>% mutate(across(c(Attempts, Canvasses, Completes)), ~ifelse(str_detect(long_name, "park-cemetery"), NA, .))) 时，我收到以下错误消息：

错误：mutate() 输入 ..2 有问题。 x 输入 ..2 必须是 矢量，而不是 formula 对象。 i 输入..2 是 ~ifelse(str_detect(long_name, "park-cemetery"), NA, .).

这是产生此错误的一小部分数据：

df <- structure(list(Org = c("OrgName", "OrgName", "OrgName", "OrgName", 
"OrgName", "OrgName", "OrgName", "OrgName", "OrgName", "OrgName"
), nCode = c("M34", "R36", "R46", "X29", "M31", "K39", "Q12", 
"Q39", "X41", "K27"), Attempts = c(100, 100, 100, 100, 100, 100, 
100, 100, 100, 100), Canvasses = c(80, 80, 80, 80, 80, 80, 80, 
80, 80, 80), Completes = c(50, 50, 50, 50, 50, 50, 50, 50, 50, 
50), van_nocc_id = c(999, 999, 999, 999, 999, 999, 999, 999, 
999, 999), van_name = c("M-Upper West Side", "SI-Rosebank", "SI-Tottenville", 
"BX-park-cemetery-etc-Bronx", "M-Stuyvesant Town-Cooper Village", 
"BK-Kensington", "Q-Broad Channel", "Q-Lindenwood", "BX-Wakefield", 
"BK-East New York"), boro_short = c("M", "SI", "SI", "BX", "M", 
"BK", "Q", "Q", "BX", "BK"), long_name = c("Upper West Side", 
"Rosebank", "Tottenville", "park-cemetery-etc-Bronx", "Stuyvesant Town-Cooper Village", 
"Kensington", "Broad Channel", "Lindenwood", "Wakefield", "East New York"
)), row.names = c(NA, -10L), class = "data.frame")

最终更新

错位右括号的诅咒！感谢大家的帮助...正确的解决方案是df %>% mutate(across(c(Attempts, Canvasses, Completes), ~ifelse(str_detect(long_name, "park-cemetery"), NA, .)))

Answer 1

如果您使用新引入的函数across（这是处理此任务的正确方法），您必须在across 本身内指定您要应用的函数。在这种情况下，函数 ifelse(...) 必须是一个 purrr 样式的 lambda（所以从 ~ 开始）。查看acrossdocumentation 并查找参数.cols 和.fns。

df %>% 
  mutate(across(c(total, group_a, group_b), ~ifelse(str_detect(type, "Park"), NA, .)))

输出

#           type total group_a group_b
# 1         Park    NA      NA      NA
# 2 Neighborhood    56      26      30
# 3      Airport    75      45      30
# 4         Park    NA      NA      NA
# 5 Neighborhood    21       3      18
# 6 Neighborhood    56      46      10

Answer 2

这里有一个 data.table 解决方案。

require(data.table)
df <- data.frame("type" = c("Park", "Neighborhood", "Airport", "Park", "Neighborhood", "Neighborhood"),
               "total" = c(34, 56, 75, 89, 21, 56),
               "group_a" = c(30, 26, 45, 60, 3, 46),
               "group_b" = c(4, 30, 30, 29, 18, 10))

setDT(df)
df[type == "Park", c("total", "group_a", "group_b") := NA]

Answer 3

更新：很快就弄清楚了！只需要将列放在向量中：

# concise AND working!
df %>% mutate(across(c(total, group_a, group_b)), ifelse(str_detect(type, "Park"), NA, .))

我最初尝试过，但将列放在引号中...不要那样做:)