与ifelse语句超限

问题：我写了超过100 ifelse陈述一个巨大的一段代码，不仅要学习，有上ifelse报表数量限制：超过50引发错误。无论如何，我知道有一种更有效的方式来做我想做的事情。与ifelse语句超限

目标：试图编写一个函数，将许多字符串变体（参见下面的例子）重新编码为清晰的类别（例如下面）。我使用str_detect给T/F，然后根据响应更改为正确的类别。我怎么能没有超过100 ifelse陈述（我有更多的类别）。

例子：

mydf <- data_frame(answer = sample(1:5, 10, replace = T), 
       location = c("at home", "home", "in a home", 
"school", "my school", "School", "Work", "work", 
         "working", "work usually")) 

loc_function <- function(x) { 
    home <- "home" 
    school <- "school" 
    work <- "work" 
    ifelse(str_detect(x, regex(home, ignore_case = T)), "At Home", 
    ifelse(str_detect(x, regex(school, ignore_case = T)), "At 
School", 
      ifelse(str_detect(x, regex(work, ignore_case = T)), "At 
Work", x))) 
} 

### Using function to clean up messy strings (and recode first column too) into clean categories 
mycleandf <- mydf %>% 
    as_data_frame() %>% 
    mutate(answer = ifelse(answer >= 2, 1, 0)) %>% 
    mutate(location = loc_function(location)) %>% 
    select(answer, location) 

mycleandf 

# A tibble: 10 x 2 
    answer location 
    <dbl>  <chr> 
1  1 At Home 
2  1 At Home 
3  1 At Home 
4  1 At School 
5  1 At School 
6  1 At School 
7  1 At Work 
8  0 At Work 
9  1 At Work 
10  0 At Work

来源

2017-07-25 tall_table

https://www.tutorialspoint.com/r/r_switch_statement.htm – Kai

*超过100 ifelse语句*当你发现自己需要比的东西屈指可数，你应该开始思考关于寻找更好的方法。当你达到两把时，你应该开始考虑你做错了什么。如果你认为你有一辆独轮车，**知道你已经完全搞砸了，需要寻求帮助。你已经达到了翻车水平。 –

听起来像你想要使用case_when语句，或者使用purr：map（）将函数映射到所有单词以使其成为标题大小写？ – petergensler

你可以把你的模式在一个名为向量，（注意Other = ""，这是一个秋天回来的时候没有你的模式匹配字符串）：

patterns <- c("At Home" = "home", "At School" = "school", "At Work" = "work", "Other" = "")

然后循环图案并检查字符串是否包含图案：

match <- sapply(patterns, grepl, mydf$location, ignore.case = T)

Fin盟友建立新列买检查匹配的模式这是你要替换的人，如果没有匹配，回落到其他的名字：

mydf$clean_loc <- colnames(match)[max.col(match, ties.method = "first")] 
mydf 

# A tibble: 10 x 3 
# answer  location clean_loc 
# <int>  <chr>  <chr> 
# 1  3  at home At Home 
# 2  3   home At Home 
# 3  3 in a home At Home 
# 4  3  school At School 
# 5  2 my school At School 
# 6  4  School At School 
# 7  5   Work At Work 
# 8  1   work At Work 
# 9  2  working At Work 
#10  1 work usually At Work

来源

2017-07-25 22:36:53 Psidom

非常有帮助。如果我有一个匹配两个字符串的字符串，我怎么才能正确排序呢？ EG：“当时在家工作”我想归类为“在工作中”。调整模式或匹配的逻辑顺序？ –

您可以调节模式的顺序，把你想要那些你不前优先考虑的模式。所以，如果你在'At Home'前面加上'At Work'，它会给你'At Work'。 – Psidom

不是嵌套的条件，你可以依次执行它们。使用for循环：

# Store the find-replace pairs in a data frame 

word_map <- data.frame(pattern = c("home", "school", "work"), 
         replacement = c("At Home", "At School", "At Work"), 
         stringsAsFactors = FALSE) 

word_map 
pattern replacement 
1 home  At Home 
2 school At School 
3 work  At Work 

# Iterate through the pairs 

for (i in 1:nrow(word_map)) { 

    pattern  <- word_map$pattern[i] 
    replacement <- word_map$replacement[i] 

    mydf$location <- ifelse(grepl(pattern, mydf$location, ignore.case = TRUE), replacement, mydf$location) 
} 

mydf 
    answer location 
1  4 At Home 
2  4 At Home 
3  1 At Home 
4  5 At School 
5  1 At School 
6  2 At School 
7  5 At Work 
8  2 At Work 
9  1 At Work 
10  3 At Work

来源

2017-07-25 22:42:25 Damian

与ifelse语句超限

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