get a particular row in R to a new table - regex

Question

i am new to R so please guide me with this.
Below shown is a simple table called Order.
Col1 Col2 Col3
hey hi july 12,2013
hey hi june 12,2013
hey hi April 12,2013
hey hi April 14,2012
If i want to write a query such that i get this as result in a new table ie. i need to use regular expression to match for a part of string in Col3 and then count.
july june April
1 1 2
please help me if anyone knows how to do it.

Answer 1

You can use sub to extract the months' names and table to count the frequencies:
dat <- read.table(text = "Col1 Col2 Col3
hey hi 'july 12,2013'
hey hi 'june 12,2013'
hey hi 'April 12,2013'
hey hi 'April 14,2012'", header = TRUE)
table(sub("^(\\w+) .*", "\\1", dat$Col3))
# April july june
# 2 1 1
How does sub("^(\\w+) .*", "\\1", dat$Col3) work?
The function sub performs replacements in strings. The strings inside quotes are regular expressions. ^ is the beginning of the string, \\w is a word character, + means one or multiple. is a literal space. .* means any number of any character. The parentheses are used to create a group. The first (and only) group (\\w+) matches word characters at the beginning of the string. The second argument in the sub function, "\\1" is used to replace the whole string with the substring representing the first group. In short: the whole string is replaced by the first word.

Answer 2

Data:
data <- read.table(text = "Col1 Col2 Col3
hey hi 'july 12,2013'
hey hi 'june 12,2013'
hey hi 'April 12,2013'
hey hi 'April 14,2012'", header = TRUE)
An answer using dates:
#tranform data in POSIXlt
data$Col3 <- as.POSIXlt(data$Col3, format="%B %d, %Y")
## group using table with POSIXlt numbers (0 is january)
table(data$Col3$mon)
3 5 6
2 1 1
## group using table with normal month numbers
table(month(data$Col3))
4 6 7
2 1 1
## group using aggregate with POSIXlt numbers (0 is january)
aggregate(data$Col1, by=list(data[,"Col3"]$mon), length)
#result
Group.1 x
1 3 2
2 5 1
3 6 1
## group using aggregate with normal month numbers
aggregate(data$Col1, by=list(month(data$Col3)), length)
#result
Group.1 x
1 4 2
2 6 1
3 7 1
PS: whe you get data$Col3$mon in POSIXlt january is 0, so april is 3 and not 4 as you would expect. To get "normal" month numbers you should use month(data$Col3) - just realised that reading Ananda's comment.
If you want a prettier version (by Ananda Mahto):
Col3 <- as.POSIXlt(data$Col3, format="%B %d, %Y"); table(month.name[month(Col3)])
April July June
2 1 1