與ifelse語句超限

問題：我寫了超過100 ifelse陳述一個巨大的一段代碼，不僅要學習，有上ifelse報表數量限制：超過50引發錯誤。無論如何，我知道有一種更有效的方式來做我想做的事情。與ifelse語句超限

目標：試圖編寫一個函數，將許多字符串變體（參見下面的例子）重新編碼爲清晰的類別（例如下面）。我使用str_detect給T/F，然後根據響應更改爲正確的類別。我怎麼能沒有超過100 ifelse陳述（我有更多的類別）。

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

來源

2017-07-25 tall_table

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

*超過100 ifelse語句*當你發現自己需要比的東西屈指可數，你應該開始思考關於尋找更好的方法。當你達到兩把時，你應該開始考慮你做錯了什麼。如果你認爲你有一輛獨輪車，**知道你已經完全搞砸了，需要尋求幫助。你已經達到了翻車水平。 –

聽起來像你想要使用case_when語句，或者使用purr：map（）將函數映射到所有單詞以使其成爲標題大小寫？ – petergensler

你可以把你的模式在一個名爲向量，（注意Other = ""，這是一個秋天回來的時候沒有你的模式匹配字符串）：

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

然後循環圖案並檢查字符串是否包含圖案：

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

Fin盟友建立新列買檢查匹配的模式這是你要替換的人，如果沒有匹配，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

來源

2017-07-25 22:36:53 Psidom

非常有幫助。如果我有一個匹配兩個字符串的字符串，我怎麼才能正確排序呢？ EG：「當時在家工作」我想歸類爲「在工作中」。調整模式或匹配的邏輯順序？ –

您可以調節模式的順序，把你想要那些你不前優先考慮的模式。所以，如果你在'At Home'前面加上'At Work'，它會給你'At Work'。 – Psidom

不是嵌套的條件，你可以依次執行它們。使用for循環：

# 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

來源

2017-07-25 22:42:25 Damian

與ifelse語句超限

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