用 lookup table dplyr 替换字符串

Question

我正在尝试在 R 中创建一个查找 table，以便获取与我工作的公司格式相同的数据。

它涉及我想使用 dplyr 合并的不同教育类别。

library(dplyr)

# Create data
education <- c("Mechanichal Engineering","Electric Engineering","Political Science","Economics")

    data <- data.frame(X1=replicate(1,sample(education,1000,rep=TRUE)))

    tbl_df(data)

    # Create lookup table
    lut <- c("Mechanichal Engineering" = "Engineering",
             "Electric Engineering" = "Engineering",
             "Political Science" = "Social Science",
             "Economics" = "Social Science")

    # Assign lookup table
    data$X1 <- lut[data$X1]

但在我的输出中，我的旧值被替换为错误的值，即不是我在查找 table 中创建的值。相反，查找 table 似乎是随机分配的。

Answer 1

我发现最好的方法是使用 car 包

中的 recode()

# Observe that dplyr also has a recode function, so require car after dplyr
    require(dplyr)
    require(car)

数据是从中抽取的四个教育类别。

    education <- c("Mechanichal Engineering",
                   "Electric Engineering","Political Science","Economics")

data <- data.frame(ID = c(1:1000), X1 = replicate(1,sample(education,1000,rep=TRUE)))

对数据使用 recode() 我重新编码类别

lut <- data.frame(ID = c(1:1000), X2 = recode(data$X1, '"Economics" = "Social Science";
                         "Electric Engineering" = "Engineering";
                          "Political Science" = "Social Science";
                          "Mechanichal Engineering" = "Engineering"'))

要查看它是否执行正确，请加入原始数据和重新编码的数据

data <- full_join(data, lut, by = "ID")

head(data)

   ID                     X1             X2
1  1       Political Science Social Science
2  2               Economics Social Science
3  3    Electric Engineering    Engineering
4  4       Political Science Social Science
5  5               Economics Social Science
6  6 Mechanichal Engineering    Engineering

使用重新编码，您无需在重新编码之前对数据进行排序。

Answer 2

education <- c("Mechanichal Engineering","Electric Engineering","Political Science","Economics")
lut <- list("Mechanichal Engineering" = "Engineering",
            "Electric Engineering" = "Engineering",
            "Political Science" = "Social Science",
            "Economics" = "Social Science")
lut2<-melt(lut)
data1 <- data.frame(X1=replicate(1,sample(education,1000,rep=TRUE)))
data1$new <- lut2[match(data1$X1,lut2$L1),'value']
head(data1)


=======================  ==============
X1                       new           
=======================  ==============
Political Science        Social Science
Political Science        Social Science
Mechanichal Engineering  Engineering   
Mechanichal Engineering  Engineering   
Political Science        Social Science
Political Science        Social Science
=======================  ==============

Answer 3

我一直在尝试自己解决这个问题。我对找到的大多数解决方案都不太满意，所以这就是我最终得到的。我添加了一个 "other" 类别以表明它即使在查找 table.

中未定义值的情况下也能正常工作

library(dplyr)

# Create data
education <- c("Mechanichal Engineering",
               "Electric Engineering",
               "Political Science",
               "Economics",
               "Other")

data <- data.frame(X1 = replicate(1, sample(education, 20, rep=TRUE)))

# Create lookup table
lut <- c("Mechanichal Engineering" = "Engineering",
         "Electric Engineering" = "Engineering",
         "Political Science" = "Social Science",
         "Economics" = "Social Science")

data %>%
    mutate(X2 = recode(X1, !!!lut))
#>                         X1             X2
#> 1     Electric Engineering    Engineering
#> 2                    Other          Other
#> 3                    Other          Other
#> 4                    Other          Other
#> 5                    Other          Other
#> 6        Political Science Social Science
#> 7                    Other          Other
#> 8                Economics Social Science
#> 9        Political Science Social Science
#> 10    Electric Engineering    Engineering
#> 11               Economics Social Science
#> 12               Economics Social Science
#> 13 Mechanichal Engineering    Engineering
#> 14               Economics Social Science
#> 15       Political Science Social Science
#> 16                   Other          Other
#> 17                   Other          Other
#> 18                   Other          Other
#> 19 Mechanichal Engineering    Engineering
#> 20       Political Science Social Science

用 lookup table dplyr 替换字符串

Replacing strings with lookup table dplyr

string

r

dplyr