Currently I have a df like so:
df <- data.frame(
player = c('Player To Have 1 Or More Shots On Target', 'Player To Have 1 Or More Shots On Target',
'Player To Have 2 Or More Shots On Target', 'Player To Have 3 Or More Shots On Target',
'Player To Have 1 Or More Shots On Target in 1st Half'))
Output:
player
1 Player To Have 1 Or More Shots On Target
2 Player To Have 1 Or More Shots On Target
3 Player To Have 2 Or More Shots On Target
4 Player To Have 3 Or More Shots On Target
5 Player To Have 1 Or More Shots On Target in 1st Half
I would like to use grepl (or another suitable alternative) to only capture 1,2,3,4, etc. shots on target (disregarding anything else like row 5 which also contains 'in 1st Half).
In the example above, I wish to capture all of the first 4 rows (the original data has many more rows). I tried the following which works:
df2 <- dplyr::filter(df, grepl("Player To Have 1 Or More Shots On Target", player))
How can the above be ameneded to include multiple digits for the "1"? E.g. I would like to capture 1,2,3,4, etc. shots?
I tried something like:
number_of_shots <- c("1","2")
df2 <- dplyr::filter(df, grepl("Player To Have", number_of_shots, "Or More Shots On Target", player))
But I get the following error:
Error in `dplyr::filter()`:
ℹ In argument: `grepl(...)`.
Caused by error:
! `..1` must be of size 5 or 1, not size 2.
Regular expressions can be used
^ and ending with $ matching[0-9] to match any digit from 0-9, and [1-4] if you just want to match 1 to 4. Use .* to match anything.
df <- data.frame(
player = c('Player To Have 1 Or More Shots On Target', 'Player To Have 1 Or More Shots On Target',
'Player To Have 10 Or More Shots On Target', 'Player To Have 3 Or More Shots On Target',
'Player To Have 1 Or More Shots On Target in 1st Half'))
# match 0-9
df %>%
filter(grepl('^Player To Have [0-9] Or More Shots On Target$', player))
# match anything
df %>%
filter(grepl('^Player To Have .* Or More Shots On Target$', player))