Order dataframe by month - r

Question

I have calculated the maximum counts per month in this data.frame:
counts <- data.frame(year = sort(rep(2000:2009, 12)), month = rep(month.abb,10), count = sample(1:500, 120, replace = T))
library(plyr)
count_max <- ddply(counts, .(month), summarise, max.count = max(count))
month max.count
1 Apr 470
2 Aug 389
3 Dec 446
4 Feb 487
5 Jan 473
6 Jul 460
7 Jun 488
8 Mar 449
9 May 488
10 Nov 464
11 Oct 483
12 Sep 394
I now want to sort count_max by the month.abb vector, so that month is in the usual order Jan-Dec. This is what I tried:
count_max[match(count_max$month, month.abb),]
...but it didn't work. How can I arrange count_max$month in the order Jan-Dec?

Answer 1

An alternate without conversion:
count_max[order(match(count_max$month, month.abb)), ]
# month max.count
# 5 Jan 466
# 4 Feb 356
# 8 Mar 496
# 1 Apr 489
# 9 May 498
# 7 Jun 497
# 6 Jul 491
# 2 Aug 446
# 12 Sep 414
# 11 Oct 490
# 10 Nov 416
# 3 Dec 475
Note that in your example, match(count...) returns the position of a given month in month.abb, which is what you want to sort by. You came real close, but instead of sorting by that vector, you subsetted by it. So, for example, August is the 2nd value in your original DF, but the 8th value in month.abb, so the match value for the 2nd value in your subset vector is 8, which means you are going to put the 8th row of your original data frame (in your case March), into the second position of your new DF, instead of ranking the 2nd row in your original DF into 8th position of the new one.
The distinction is a bit of a brain twister, but if you think it through it should make sense.

Answer 2

Convert your "month" column into an ordered factor:
factor(count_max$month, month.abb, ordered=TRUE)
# [1] Apr Aug Dec Feb Jan Jul Jun Mar May Nov Oct Sep
# Levels: Jan < Feb < Mar < Apr < May < Jun < Jul < Aug < Sep < Oct < Nov < Dec
Example:
count_max$month <- factor(count_max$month, month.abb, ordered=TRUE)
count_max[order(count_max$month), ]
# month max.count
# 5 Jan 482
# 4 Feb 408
# 8 Mar 483
# 1 Apr 489
# 9 May 369
# 7 Jun 432
# 6 Jul 344
# 2 Aug 470
# 12 Sep 474
# 11 Oct 450
# 10 Nov 492
# 3 Dec 366