dplyr过滤器没有'；他似乎不在循环中工作

我有很多列，其中我想要去掉3个特定的值。我想做一个循环。但由于某种原因，它不起作用，我不明白为什么。以下是函数：

for (i in colnames(df1)){
    z <- as.name(i)
    df1 <- df1 %>% filter(z != "Refusal") %>% filter(z != "Don't know") %>%  filter(z != "No answer")
}

for（i在colnames（df1）中）{
z%filter（z！=“不知道”）%%>%filter（z！=“没有答案”）
}

我知道变量z是不必要的，但我希望它能有所帮助。没有

这是一个完整的示例，每个列都有代码。这是可行的，但却是相当烦人的解决方案

df1 <- data.frame(country = df$cntry, gender = df$gndr, pplfair = df$pplfair,
                  gincdif = df$gincdif, happy = df$happy, sclmeet = df$sclmeet,
                  inprdsc = df$inprdsc, sclat = df$sclact, rlgbg = df$rlgblg, 
                  dfincac = df$dfincac, sblazy = df$sblazy, eduyrs = df$eduyrs,
                  imprich = df$imprich, iprspot = df$iprspot, impfun = df$impfun)

##Wrangling data

###from data removing no answer, don't know, refusal
df1 <- df1 %>% filter(pplfair != "Refusal") %>% filter(pplfair != "Don't know") %>%  filter(pplfair != "No answer")

df1 <- df1 %>% filter(gincdif != "Refusal") %>% filter(gincdif != "Don't know") %>%  filter(gincdif != "No answer")

df1 <- df1 %>% filter(happy != "Refusal") %>% filter(happy != "Don't know") %>%  filter(happy != "No answer")

df1 <- df1 %>% filter(sclmeet != "Refusal") %>% filter(sclmeet != "Don't know") %>%  filter(sclmeet != "No answer")

df1 <- df1 %>% filter(inprdsc != "Refusal") %>% filter(inprdsc != "Don't know") %>%  filter(inprdsc != "No answer")

df1 <- df1 %>% filter(sclat != "Refusal") %>% filter(sclat != "Don't know") %>%  filter(sclat != "No answer")

df1 <- df1 %>% filter(rlgbg != "Refusal") %>% filter(rlgbg != "Don't know") %>%  filter(rlgbg != "No answer")

df1 <- df1 %>% filter(dfincac != "Refusal") %>% filter(dfincac != "Don't know") %>%  filter(dfincac != "No answer")

df1 <- df1 %>% filter(sblazy != "Refusal") %>% filter(sblazy != "Don't know") %>%  filter(sblazy != "No answer")

df1 <- df1 %>% filter(eduyrs != "Refusal") %>% filter(eduyrs != "Don't know") %>%  filter(eduyrs != "No answer")

df1 <- df1 %>% filter(imprich != "Refusal") %>% filter(imprich != "Don't know") %>%  filter(imprich != "No answer")

df1 <- df1 %>% filter(iprspot != "Refusal") %>% filter(iprspot != "Don't know") %>%  filter(iprspot != "No answer")

df1 <- df1 %>% filter(impfun != "Refusal") %>% filter(impfun != "Don't know") %>%  filter(impfun != "No answer")

---

df1OP的代码可以使用
filter\u all
和
%in%
进行大量简化：

library(dplyr)

df1 %>% 
  filter_all(any_vars(!(. %in% c("Refusal", "Don't know", "No answer"))))

或者如果它是所有列的子集，则在

处使用

filter\u：

df1 %>% 
  filter_at(vars(varnames), any_vars(!(. %in% c("Refusal", "Don't know", "No answer"))))

OP的代码可以使用
filter\u all
和
%in%
进行大量简化：

library(dplyr)

df1 %>% 
  filter_all(any_vars(!(. %in% c("Refusal", "Don't know", "No answer"))))

或者如果它是所有列的子集，则在

处使用

filter\u：

df1 %>% 
  filter_at(vars(varnames), any_vars(!(. %in% c("Refusal", "Don't know", "No answer"))))

如果您包含一个简单的示例输入和所需的输出，可以用来测试和验证可能的解决方案，那么就更容易为您提供帮助。您需要将名称拼接到筛选器中。使用
filter（！！z！=“不知道”）
例如，当您试图在过滤器中使用
z
时。如果您包含一个简单的示例输入和所需的输出，可用于测试和验证可能的解决方案，则更容易帮助您。您需要将名称拼接到筛选器中。使用
filter（！！z！=“不知道”）
例如，您尝试在过滤器中使用
z
。