Styjun

I'm trying to extract a list of rugby players names from a string. The string contains all of the information from a table, containing the headers (team names) as well as the name of the player in each position for each team. It also has the player ranking but I don't care about that.

Note, the 1-15 numbers indicate positions, and there's always two names following each position (home player and away player).

Here's the string:

"Team Sheets # LIO Lions RPI JAG Jaguares RPI 1 Dylan Smith 83 Juan Pablo Zeiss 59 2 Malcolm Marx 90 Julian Montoya 73 3 Carlu Sadie 78 Enrique Pieretto Heilan 54 4 Ruan Vermaak 72 Guido Petti Pagadizaval 77 5 Rhyno Herbst 72 Matias Alemanno 67 6 Marnus Schoeman 82 Juan Manuel Leguizamon 58 7 Vincent Tshituka 64 Marcos Kremer 55 8 Kwagga Smith 88 Rodrigo Bruni 62 9 Ross Cronje 74 Martin Landajo 52 10 Elton Jantjies 80 Joaquin Diaz Bonilla 62 11 Courtnall Skosan 76 Emiliano Boffelli 75 12 Franco Naude 52 Bautista Ezcurra 66 13 Wandisile Simelane 73 Matias Moroni 75 14 Sylvian Mahuza 76 Sebastian Cancelliere 65 15 Andries Coetzee 73 Joaquin Tuculet 68 Substitutes # LIO Lions RPI JAG Jaguares RPI 16 Pieter Jansen 58 Gaspar Baldunciel 61 17 Nathan McBeth 60 Santiago Garcia Botta 65 18 Frans van Wyk 58 Santiago Medrano 72 19 Stephan Lewies 81 Tomas Lavanini 68 20 James Venter 61 Tomas Lezana 62 21 Dillon Smit 61 Tomas Cubelli 63 22 Harold Vorster 69 Juan Cruz Mallia 66 23 Gianni Lombard 64 Ramiro Moyano 78"

So basically what I want is just the list of names with the team names as the headers e.g.

Lions Jaguares

Dylan Smith Juan Pablo Zeiss
Malcolm Marx Julian Montoya
... ...

Any help would be much appreciated!

While I agree with R.S.'s comment to read the data as dataframe directly, here's my solution using regex:

# build a "player name - RPI" pattern
pattern = "[a-zA-Z]+(\s[a-zA-Z]+)+\s+\d1,2"

# find all matches in string
m = gregexpr(pattern, x)

# extract all matches from string
plyrs = regmatches(x, m)[[1]]

# build dataframe
data.frame(lions = plyrs[c(TRUE, FALSE)],
 jaguares = plyrs[c(FALSE, TRUE)],
 stringsAsFactors=FALSE)

First of all, you could try to create a table structure instead of a huge long string.
Something like this could give you a little start.

data = 'Team Sheets # LIO Lions RPI JAG Jaguares RPI 1 Dylan Smith 83 Juan Pablo Zeiss 59 2 Malcolm Marx 90 Julian Montoya 73 3 Carlu Sadie 78 Enrique Pieretto Heilan 54 4 Ruan Vermaak 72 Guido Petti Pagadizaval 77 5 Rhyno Herbst 72 Matias Alemanno 67 6 Marnus Schoeman 82 Juan Manuel Leguizamon 58 7 Vincent Tshituka 64 Marcos Kremer 55 8 Kwagga Smith 88 Rodrigo Bruni 62 9 Ross Cronje 74 Martin Landajo 52 10 Elton Jantjies 80 Joaquin Diaz Bonilla 62 11 Courtnall Skosan 76 Emiliano Boffelli 75 12 Franco Naude 52 Bautista Ezcurra 66 13 Wandisile Simelane 73 Matias Moroni 75 14 Sylvian Mahuza 76 Sebastian Cancelliere 65 15 Andries Coetzee 73 Joaquin Tuculet 68 Substitutes # LIO Lions RPI JAG Jaguares RPI 16 Pieter Jansen 58 Gaspar Baldunciel 61 17 Nathan McBeth 60 Santiago Garcia Botta 65 18 Frans van Wyk 58 Santiago Medrano 72 19 Stephan Lewies 81 Tomas Lavanini 68 20 James Venter 61 Tomas Lezana 62 21 Dillon Smit 61 Tomas Cubelli 63 22 Harold Vorster 69 Juan Cruz Mallia 66 23 Gianni Lombard 64 Ramiro Moyano 78'
import re
data = re.sub(r'(s)11,', r'1', data)
data = re.sub(r'RPIs(d+)', r'n1', data)
data = re.sub(r'(#)s', r'n1', data)
print(re.sub(r'd+s(d+)', r'n1', data))