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Recoding similar factor levels across multiple data frames using Purrr and Dplyr

Below are two simple data frames. I would like to recode (collapse) the columns Sat1and Sat2so that all degrees of satisfaction are encoded just like Satisfied, and all degrees of dissatisfaction are encoded like Dissatisfied. Neutral will remain neutral. Consequently, these factors will have three levels - Satisfied, Dissatisfied, and Neutral.

I usually do this by linking data frames and using lapplyalong with the repeated code from the package car, for example:

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

I would like to accomplish this using the map functions, in particular at_map(to save the data frame, but I'm new to purrr, so feel free to offer other versions of the map) from purrr, as well as dplyr, tidyr ,stringr andggplot2`, so everything can be easily pipelined.

The example below is what I would like to execute, but for re-encoding, but I could not get it to work.

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

I would like to use at_map or a similar map function to keep the original columns Sat1and Sat2, therefore, the encoded columns will be added to the data frame and renamed. It would be great if this step could also be included in the function.

, , purrr, .

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)
0
2

- mutate_each, map, data.frames. mutate_each dplyr_0.4.3.9001 .

. , Satisfied, Dissatisfied Neutral , . sub, . ,

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

stringr , str_extract.

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

mutate_each . , funs, . recode. :

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

, , map purrr .

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
...

map_df data.frame, , . .id .

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
...
+1

, , , , .

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)
+1

Source: https://habr.com/ru/post/1668763/

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