R data frame rank by groups (group by rank) with package dplyr

问题

I have a data frame 'test' that look like this:

    session_id  seller_feedback_score
1   1   282470
2   1   275258
3   1   275258
4   1   275258
5   1   37831
6   1   282470
7   1   26
8   1   138351
9   1   321350
10  1   841
11  1   138351
12  1   17263
13  1   282470
14  1   396900
15  1   282470
16  1   282470
17  1   321350
18  1   321350
19  1   321350
20  1   0
21  1   1596
22  7   282505
23  7   275283
24  7   275283
25  7   275283
26  7   37834
27  7   282505
28  7   26
29  7   138359
30  7   321360

and a code (using package dplyr) that apparently should rank the 'seller_feedback_score' within each group of session_id:

 test <- test %>% group_by(session_id) %>% 
  mutate(seller_feedback_score_rank = dense_rank(-seller_feedback_score))

however, what is really happening is that R rank the entire data frame together without relating to the groups (session_id's):

session_id  seller_feedback_score   seller_feedback_score_rank_2
1   1   282470  5
2   1   275258  7
3   1   275258  7
4   1   275258  7
5   1   37831   11
6   1   282470  5
7   1   26  15
8   1   138351  9
9   1   321350  3
10  1   841 14
11  1   138351  9
12  1   17263   12
13  1   282470  5
14  1   396900  1
15  1   282470  5
16  1   282470  5
17  1   321350  3
18  1   321350  3
19  1   321350  3
20  1   0   16
21  1   1596    13
22  7   282505  4
23  7   275283  6
24  7   275283  6
25  7   275283  6
26  7   37834   10
27  7   282505  4
28  7   26  15
29  7   138359  8
30  7   321360  2

I checked this by counting the unique 'seller_feedback_score_rank' values and not surprisingly it equals to the highest rank value. I'd appreciate if someone could reproduce and help. thanks

link to my original question: R group by and aggregate - return relative rank within groups using plyr

回答1:

Had a similar issue, my answer was sorting on groups and the relevant ranked variable(s) in order to then use row_number() when using group_by.

# Sample dataset
df <- data.frame(group=rep(c("GROUP 1", "GROUP 2"),10),
               value=as.integer(rnorm(20, mean=1000, sd=500)))
require(dplyr)
print.data.frame(df[0:10,])
   group value
1  GROUP 1  1273
2  GROUP 2  1261
3  GROUP 1  1189
4  GROUP 2  1390
5  GROUP 1  1942
6  GROUP 2  1111
7  GROUP 1   530
8  GROUP 2   893
9  GROUP 1   997
10 GROUP 2   237

sorted <- df %>% 
          arrange(group, -value) %>%
          group_by(group) %>%
          mutate(rank=row_number())
print.data.frame(sorted)

      group value rank
1  GROUP 1  1942    1
2  GROUP 1  1368    2
3  GROUP 1  1273    3
4  GROUP 1  1249    4
5  GROUP 1  1189    5
6  GROUP 1   997    6
7  GROUP 1   562    7
8  GROUP 1   535    8
9  GROUP 1   530    9
10 GROUP 1     1   10
11 GROUP 2  1472    1
12 GROUP 2  1390    2
13 GROUP 2  1281    3
14 GROUP 2  1261    4
15 GROUP 2  1111    5
16 GROUP 2   893    6
17 GROUP 2   774    7
18 GROUP 2   669    8
19 GROUP 2   631    9
20 GROUP 2   237   10

回答2:

Found an answer in : Add a "rank" column to a data frame

data.selected <- transform(data.selected, 
              seller_feedback_score_rank = ave(seller_feedback_score, session_id, 
                              FUN = function(x) rank(-x, ties.method = "first")))

回答3:

One way you can do this is :

dataset<-dataset%>%arrange(ID, DateTime,Index)
dataset$Rank<-c(0,ID)[-(nrow(dataset)+1)] == ID
dataset<- dataset%>%group_by(ID)%>%mutate(Rank = cumsum(Rank))

Had the same issue!

来源：https://stackoverflow.com/questions/28018933/r-data-frame-rank-by-groups-group-by-rank-with-package-dplyr

标签

dataframe

dplyr

rank