Numbering rows within groups in a data frame

r dataframe r-faq

Working with a data frame similar to this:

set.seed(100)  
df <- data.frame(cat = c(rep("aaa", 5), rep("bbb", 5), rep("ccc", 5)), val = runif(15))             
df <- df[order(df$cat, df$val), ]  
df  

   cat        val  
1  aaa 0.05638315  
2  aaa 0.25767250  
3  aaa 0.30776611  
4  aaa 0.46854928  
5  aaa 0.55232243  
6  bbb 0.17026205  
7  bbb 0.37032054  
8  bbb 0.48377074  
9  bbb 0.54655860  
10 bbb 0.81240262  
11 ccc 0.28035384  
12 ccc 0.39848790  
13 ccc 0.62499648  
14 ccc 0.76255108  
15 ccc 0.88216552

I am trying to add a column with numbering within each group. Doing it this way obviously isn't using the powers of R:

 df$num <- 1  
 for (i in 2:(length(df[,1]))) {  
   if (df[i,"cat"]==df[(i-1),"cat"]) {  
     df[i,"num"]<-df[i-1,"num"]+1  
     }  
 }  
 df  

   cat        val num  
1  aaa 0.05638315   1  
2  aaa 0.25767250   2  
3  aaa 0.30776611   3  
4  aaa 0.46854928   4  
5  aaa 0.55232243   5  
6  bbb 0.17026205   1  
7  bbb 0.37032054   2  
8  bbb 0.48377074   3  
9  bbb 0.54655860   4  
10 bbb 0.81240262   5  
11 ccc 0.28035384   1  
12 ccc 0.39848790   2  
13 ccc 0.62499648   3  
14 ccc 0.76255108   4  
15 ccc 0.88216552   5

What would be a good way to do this?

I would suggest to add something like "seq along levels" or "counting along replicates" in the question title as this is how I found this question and it is exactly what I was looking for

@crazysantaclaus If that were the title, I wouldn't have found what I was looking for :-( I was literally looking for "how to number rows within groups in a data frame"

Frank

Use ave, ddply, dplyr or data.table:

df$num <- ave(df$val, df$cat, FUN = seq_along)

or:

library(plyr)
ddply(df, .(cat), mutate, id = seq_along(val))

or:

library(dplyr)
df %>% group_by(cat) %>% mutate(id = row_number())

or (the most memory efficient, as it assigns by reference within DT):

library(data.table)
DT <- data.table(df)

DT[, id := seq_len(.N), by = cat]
DT[, id := rowid(cat)]

It might be worth mentioning that ave gives a float instead of an int here. Alternately, could change df$val to seq_len(nrow(df)). I just ran into this over here: stackoverflow.com/questions/42796857/…

Interestingly this data.table solution seems to be quicker than using frank:

library(microbenchmark); microbenchmark(a = DT[, .(val ,num = frank(val)), by = list(cat)] ,b =DT[, .(val , id = seq_len(.N)), by = list(cat)] , times = 1000L)

Thanks! The dplyr solution is good. But if, like me, you kept getting weird errors when trying this approach, make sure that you are not getting conflicts between plyr and dplyr as explained in this post It can be avoided by explicitly calling dplyr::mutate(...)

another data.table method is setDT(df)[, id:=rleid(val), by=.(cat)]

How to modify library(plyr) and library(dplyr) answers to make the ranking val column in descending order?

Jaap

For making this r-faq question more complete, a base R alternative with sequence and rle:

df$num <- sequence(rle(df$cat)$lengths)

which gives the intended result:

> df cat val num 4 aaa 0.05638315 1 2 aaa 0.25767250 2 1 aaa 0.30776611 3 5 aaa 0.46854928 4 3 aaa 0.55232243 5 10 bbb 0.17026205 1 8 bbb 0.37032054 2 6 bbb 0.48377074 3 9 bbb 0.54655860 4 7 bbb 0.81240262 5 13 ccc 0.28035384 1 14 ccc 0.39848790 2 11 ccc 0.62499648 3 15 ccc 0.76255108 4 12 ccc 0.88216552 5

If df$cat is a factor variable, you need to wrap it in as.character first:

df$num <- sequence(rle(as.character(df$cat))$lengths)

Just noticed, this solutions requires cat column to be sorted?

@zx8754 yes, unless you want to number by consecutive occurances of cat

Andrii

Here is a small improvement trick that allows sort 'val' inside the groups:

# 1. Data set
set.seed(100)
df <- data.frame(
  cat = c(rep("aaa", 5), rep("ccc", 5), rep("bbb", 5)), 
  val = runif(15))             

# 2. 'dplyr' approach
df %>% 
  arrange(cat, val) %>% 
  group_by(cat) %>% 
  mutate(id = row_number())

Can you not sort after the group_by?

tmfmnk

Another dplyr possibility could be:

df %>%
 group_by(cat) %>%
 mutate(num = 1:n())

   cat      val   num
   <fct>  <dbl> <int>
 1 aaa   0.0564     1
 2 aaa   0.258      2
 3 aaa   0.308      3
 4 aaa   0.469      4
 5 aaa   0.552      5
 6 bbb   0.170      1
 7 bbb   0.370      2
 8 bbb   0.484      3
 9 bbb   0.547      4
10 bbb   0.812      5
11 ccc   0.280      1
12 ccc   0.398      2
13 ccc   0.625      3
14 ccc   0.763      4
15 ccc   0.882      5

In some cases instead of 1:n() using seq_len(n()) is safer, in the event that in your sequence of operations you have a situation where n() might return 0, because 1:0 gives you a length two vector while seq_len(0) gives a length zero vector, thus avoiding a length mismatch error with mutate().

hannes101

I would like to add a data.table variant using the rank() function which provides the additional possibility to change the ordering and thus makes it a bit more flexible than the seq_len() solution and is pretty similar to row_number functions in RDBMS.

# Variant with ascending ordering
library(data.table)
dt <- data.table(df)
dt[, .( val
   , num = rank(val))
    , by = list(cat)][order(cat, num),]

    cat        val num
 1: aaa 0.05638315   1
 2: aaa 0.25767250   2
 3: aaa 0.30776611   3
 4: aaa 0.46854928   4
 5: aaa 0.55232243   5
 6: bbb 0.17026205   1
 7: bbb 0.37032054   2
 8: bbb 0.48377074   3
 9: bbb 0.54655860   4
10: bbb 0.81240262   5
11: ccc 0.28035384   1
12: ccc 0.39848790   2
13: ccc 0.62499648   3
14: ccc 0.76255108   4

# Variant with descending ordering
dt[, .( val
   , num = rank(desc(val)))
    , by = list(cat)][order(cat, num),]

Edit on 2021-04-16 to make the switch between descending and ascending order more fail-safe

David Arenburg

Here is an option using a for loop by groups rather by rows (like OP did)

for (i in unique(df$cat)) df$num[df$cat == i] <- seq_len(sum(df$cat == i))

AKRosenblad

Using the rowid() function in data.table:

> set.seed(100)  
> df <- data.frame(cat = c(rep("aaa", 5), rep("bbb", 5), rep("ccc", 5)), val = runif(15))
> df <- df[order(df$cat, df$val), ]  
> df$num <- data.table::rowid(df$cat)
> df
   cat        val num
4  aaa 0.05638315   1
2  aaa 0.25767250   2
1  aaa 0.30776611   3
5  aaa 0.46854928   4
3  aaa 0.55232243   5
10 bbb 0.17026205   1
8  bbb 0.37032054   2
6  bbb 0.48377074   3
9  bbb 0.54655860   4
7  bbb 0.81240262   5
13 ccc 0.28035384   1
14 ccc 0.39848790   2
11 ccc 0.62499648   3
15 ccc 0.76255108   4
12 ccc 0.88216552   5

Thanks for your answer but it seems to be already covered in the last suggestion in @mnel's answer

stevec

Very simple, tidy solutions.

Row number for entire data.frame

library(tidyverse)

iris %>%
  mutate(row_num = seq_along(Sepal.Length)) %>%
  head

    Sepal.Length Sepal.Width Petal.Length Petal.Width    Species row_num
1            5.1         3.5          1.4         0.2     setosa       1
2            4.9         3.0          1.4         0.2     setosa       2
3            4.7         3.2          1.3         0.2     setosa       3
..           ...         ...          ...         ...     ......     ...
148          6.5         3.0          5.2         2.0  virginica     148
149          6.2         3.4          5.4         2.3  virginica     149
150          5.9         3.0          5.1         1.8  virginica     150

Row number by group in data.frame

iris %>% 
  group_by(Species) %>% 
  mutate(num_in_group=seq_along(Species)) %>% 
  as.data.frame


    Sepal.Length Sepal.Width Petal.Length Petal.Width    Species num_in_group
1            5.1         3.5          1.4         0.2     setosa            1
2            4.9         3.0          1.4         0.2     setosa            2
3            4.7         3.2          1.3         0.2     setosa            3
..           ...         ...          ...         ...     ......           ..
48           4.6         3.2          1.4         0.2     setosa           48
49           5.3         3.7          1.5         0.2     setosa           49
50           5.0         3.3          1.4         0.2     setosa           50
51           7.0         3.2          4.7         1.4 versicolor            1
52           6.4         3.2          4.5         1.5 versicolor            2
53           6.9         3.1          4.9         1.5 versicolor            3
..           ...         ...          ...         ...     ......           ..
98           6.2         2.9          4.3         1.3 versicolor           48
99           5.1         2.5          3.0         1.1 versicolor           49
100          5.7         2.8          4.1         1.3 versicolor           50
101          6.3         3.3          6.0         2.5  virginica            1
102          5.8         2.7          5.1         1.9  virginica            2
103          7.1         3.0          5.9         2.1  virginica            3
..           ...         ...          ...         ...     ......           ..
148          6.5         3.0          5.2         2.0  virginica           48
149          6.2         3.4          5.4         2.3  virginica           49
150          5.9         3.0          5.1         1.8  virginica           50

gdkrmr

Another base R solution would be to split the data frame per cat, after that using lapply: add a column with number 1:nrow(x). The last step is to have your final data frame back with do.call, that is:

        df_split <- split(df, df$cat)
        df_lapply <- lapply(df_split, function(x) {
          x$num <- seq_len(nrow(x))
          return(x)
        })
        df <- do.call(rbind, df_lapply)

Numbering rows within groups in a data frame

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