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Wells
Wells

Reputation: 10969

R: subset/group data frame with a max value?

Given a data frame like this:

  gid set  a  b
1   1   1  1  9
2   1   2 -2 -3
3   1   3  5  6
4   2   2 -4 -7
5   2   6  5 10
6   2   9  2  0

How can I subset/group data frame of a unique gid with the max set value and 1/0 wether its a value is greater than its b value?

So here, it'd be, uh...

1,3,0
2,9,1

Kind of a stupid simple thing in SQL but I'd like to have a bit better control over my R, so...

Upvotes: 3

Views: 1261

Answers (3)

akrun
akrun

Reputation: 887118

In base R, you can use ave 

indx <- with(df, ave(set, gid, FUN=max)==set)
#in cases of ties
#indx <- with(df, !!ave(set, gid, FUN=function(x) 
#                  which.max(x) ==seq_along(x)))


transform(df[indx,], greater=(a>b)+0)[,c(1:2,5)]
#   gid set greater
# 3   1   3       0
# 6   2   9       1

Upvotes: 1

Rich Scriven
Rich Scriven

Reputation: 99331

Here's a data.table possibility, assuming your original data is called df. 

library(data.table)

setDT(df)[, .(set = max(set), b = as.integer(a > b)[set == max(set)]), gid]
#    gid set b
# 1:   1   3 0
# 2:   2   9 1

Note that to account for multiple max(set) rows, I used set == max(set) as the subset so that this will return the same number of rows for which there are ties for the max (if that makes any sense at all).

And courtesy of @thelatemail, another data table option:

setDT(df)[, list(set = max(set), ab = (a > b)[which.max(set)] + 0), by = gid]
#    gid set ab
# 1:   1   3  0
# 2:   2   9  1

Upvotes: 3

hrbrmstr
hrbrmstr

Reputation: 78792

Piece of cake with dplyr:

dat <- read.table(text="gid set  a  b
1   1  1  9
1   2 -2 -3
1   3  5  6
2   2 -4 -7
2   6  5 10
2   9  2  0", header=TRUE)

library(dplyr)

dat %>%
  group_by(gid) %>%
  filter(row_number() == which.max(set)) %>%
  mutate(greater=a>b) %>%
  select(gid, set, greater)

## Source: local data frame [2 x 3]
## Groups: gid
## 
##   gid set greater
## 1   1   3   FALSE
## 2   2   9    TRUE

If you really need 1's and 0's and the dplyr groups cause any angst:

dat %>%
  group_by(gid) %>%
  filter(row_number() == which.max(set)) %>%
  mutate(greater=ifelse(a>b, 1, 0)) %>%
  select(gid, set, greater) %>%
  ungroup

## Source: local data frame [2 x 3]
## 
##   gid set greater
## 1   1   3       0
## 2   2   9       1

You could do the same thing without pipes:

ungroup(
  select(
    mutate(
      filter(row_number() == which.max(set)), 
      greater=ifelse(a>b, 1, 0)), gid, set, greater))

but…but… why?! :-)

Upvotes: 6

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