使用Purrr和Dplyr在多个数据帧之间重新编码相似因子水平

Question

以下是两个简单的数据框。 我想重新编码（折叠） Sat1和Sat2列，以便所有满意程度都简单地编码为Satisfied ，所有不满意程度都编码为Dissatisfied 。 中性将保持为中性。 因此，这些因素将具有三个级别- Satisfied, Dissatisfied, and Neutral 。

通常，我将通过绑定数据帧并使用lapply以及car包装中的重新编码来完成此操作，例如：

  DF1[2:3] <- lapply(DF1[2:3], recode, c('"Somewhat Satisfied"= "Satisfied","Satisfied"="Satisfied","Extremely Dissatisfied"="Dissatisfied"........etc, etc

我想做到这一点使用地图功能，特别是at_map （保持数据帧，但我是新来的purrr所以随时提出地图的其他版本）从purrr ，以及dplyr ，tidyr , stringr and ggplot2`因此所有内容都可以轻松地流水线化。

下面的示例是我想要完成的，但是要进行重新编码，但是我无法使其工作。

http://www.r-bloggers.com/using-purrr-with-dplyr/

我想使用at_map或类似的map函数，以便可以保留Sat1和Sat2的原始列，以便将重新编码的列添加到数据框中Sat2命名。 如果此步骤也可以包含在函数中，那就太好了。

实际上，我将有许多数据帧，所以我只想重新编码一次因子水平，然后使用purrr的函数使用最少的代码对所有数据帧进行更改。

Names<-c("James","Chris","Jessica","Tomoki","Anna","Gerald")
Sat1<-c("Satisfied","Very Satisfied","Dissatisfied","Somewhat Satisfied","Dissatisfied","Neutral")
Sat2<-c("Very Dissatisfied","Somewhat Satisfied","Neutral","Neutral","Satisfied","Satisfied")
Program<-c("A","B","A","C","B","D")
Pets<-c("Snake","Dog","Dog","Dog","Cat","None")

DF1<-data.frame(Names,Sat1,Sat2,Program,Pets)

Names<-c("Tim","John","Amy","Alberto","Desrahi","Francesca")
Sat1<-c("Extremely Satisfied","Satisfied","Satisfed","Somewhat Dissatisfied","Dissatisfied","Satisfied")
Sat2<-c("Dissatisfied","Somewhat Dissatisfied","Neutral","Extremely Dissatisfied","Somewhat Satisfied","Somewhat Dissatisfied")
Program<-c("A","B","A","C","B","D")


DF2<-data.frame(Names,Sat1,Sat2,Program)

Answer 1

我通过联接进行类似的大型编码，在这种情况下，我认为转换为较长的数据帧会使问题更容易考虑。

library(tidyr)
library(dplyr)

mdf <- DF1 %>% 
  gather(var, value, starts_with("Sat"))

recode_df <- data_frame( value = c("Extremely Satisfied","Satisfied","Somewhat Dissatisfied","Dissatisfied"),
                         recode = 1:4)
mdf <- left_join(mdf, recode_df)
mdf %>% spread(var, recode)

Answer 2

一种实现方法是使用mutate_each来完成工作，并结合使用其中一个map函数来遍历data.frames列表。 使用mutate_each或同等功能可以重命名新列。

在这种情况下，可以使用字符串操作而不是重新编码。 我相信您想从当前的字符串中提取“ Satisfied ，“ Dissatisfied ”或“ Neutral ”。 您可以使用sub使用正则表达式来实现此目的。 例如，

sub(".*(Satisfied|Dissatisfied|Neutral).*$", "\\1", DF2$Sat2)
"Dissatisfied" "Dissatisfied" "Neutral"      "Dissatisfied" "Satisfied"    "Dissatisfied"

Package stringr有一个不错的函数，用于提取特定的字符串str_extract 。

library(stringr)
str_extract(DF2$Sat2, "Satisfied|Neutral|Dissatisfied")
 "Dissatisfied" "Dissatisfied" "Neutral"      "Dissatisfied" "Satisfied"    "Dissatisfied"

您可以在mutate_each中使用此功能，以在多个列上使用这些功能之一。 您在funs为函数指定的名称将被添加到新的列名称中。 我用recode 。 对于您的一个数据集：

DF1 %>% 
    mutate_each( funs(recode = str_extract(., "Satisfied|Neutral|Dissatisfied") ), 
              starts_with("Sat") )

    Names               Sat1               Sat2 Program  Pets  Sat1_recode  Sat2_recode
1   James          Satisfied  Very Dissatisfied       A Snake    Satisfied Dissatisfied
2   Chris     Very Satisfied Somewhat Satisfied       B   Dog    Satisfied    Satisfied
3 Jessica       Dissatisfied            Neutral       A   Dog Dissatisfied      Neutral
4  Tomoki Somewhat Satisfied            Neutral       C   Dog    Satisfied      Neutral
5    Anna       Dissatisfied          Satisfied       B   Cat Dissatisfied    Satisfied
6  Gerald            Neutral          Satisfied       D  None      Neutral    Satisfied

要遍历列表中存储的许多数据集，可以使用purrr中的map函数对列表中的每个元素执行功能。

list(DF1, DF2) %>%
    map(~mutate_each(.x, 
                  funs(recode = str_extract(., "Satisfied|Neutral|Dissatisfied") ), 
                  starts_with("Sat")) )

[[1]]
    Names               Sat1               Sat2 Program  Pets  Sat1_recode  Sat2_recode
1   James          Satisfied  Very Dissatisfied       A Snake    Satisfied Dissatisfied
2   Chris     Very Satisfied Somewhat Satisfied       B   Dog    Satisfied    Satisfied
...
[[2]]
      Names                  Sat1                   Sat2 Program  Sat1_recode  Sat2_recode
1       Tim   Extremely Satisfied           Dissatisfied       A    Satisfied Dissatisfied
2      John             Satisfied  Somewhat Dissatisfied       B    Satisfied Dissatisfied
...

相反，使用map_df会将列表中的所有元素绑定到data.frame中，这可能是您想要的，也可能不是。 使用.id参数为每个原始数据集添加一个名称。

list(DF1, DF2) %>%
    map_df(~mutate_each(.x, 
                  funs(recode = str_extract(., "Satisfied|Neutral|Dissatisfied")), 
                  starts_with("Sat")), .id = "Group")

   Group     Names                  Sat1                   Sat2 Program  Pets  Sat1_recode
1      1     James             Satisfied      Very Dissatisfied       A Snake    Satisfied
2      1     Chris        Very Satisfied     Somewhat Satisfied       B   Dog    Satisfied
3      1   Jessica          Dissatisfied                Neutral       A   Dog Dissatisfied
4      1    Tomoki    Somewhat Satisfied                Neutral       C   Dog    Satisfied
5      1      Anna          Dissatisfied              Satisfied       B   Cat Dissatisfied
6      1    Gerald               Neutral              Satisfied       D  None      Neutral
7      2       Tim   Extremely Satisfied           Dissatisfied       A  <NA>    Satisfied
8      2      John             Satisfied  Somewhat Dissatisfied       B  <NA>    Satisfied
...