comperes offers a
pipe (%>%) friendly set of tools for storing and
managing competition results (hereafter - results). This vignette
discusses following topics:
Understanding of competition is quite general: it is a set of games (abstract event) in which players (abstract entity) gain some abstract scores (typically numeric). The most natural example is sport results, however not the only one. For example, product rating can be considered as a competition between products as “players”. Here a “game” is a customer that reviews a set of products by rating them with numerical “score” (stars, points, etc.).
We will need the following packages:
Results in long format are stored in object of class
longcr. It is considered to be a tibble with
one row per game-player pair. It should have at least columns with names
“game”, “player” and “score”. For example:
cr_long_raw <- tibble(
game = c(1, 1, 1, 2, 2, 3, 3, 4),
player = c(1, NA, NA, 1, 2, 2, 1, 2),
score = 1:8
)To convert cr_long_raw into longcr object
use as_longcr():
cr_long <- as_longcr(cr_long_raw)
cr_long
#> # A longcr object:
#> # A tibble: 8 × 3
#> game player score
#> <dbl> <dbl> <int>
#> 1 1 1 1
#> 2 1 NA 2
#> 3 1 NA 3
#> 4 2 1 4
#> 5 2 2 5
#> 6 3 2 6
#> 7 3 1 7
#> 8 4 2 8By default, as_longcr() repairs its input by applying
set of heuristics to extract relevant data:
tibble(
PlayerRS = "a",
gameSS = "b",
extra = -1,
score_game = 10,
player = 1
) %>%
as_longcr()
#> as_longcr: Some matched names are not perfectly matched:
#> gameSS -> game
#> score_game -> score
#> # A longcr object:
#> # A tibble: 1 × 5
#> game player score PlayerRS extra
#> <chr> <dbl> <dbl> <chr> <dbl>
#> 1 b 1 10 a -1Results in wide format are stored in object of class
widecr. It is considered to be a tibble with
one row per game with fixed amount of players. Data should be organized
in pairs of columns “player”-“score”. Identifier of a pair should go
after respective keyword and consist only from digits. For example:
player1, score1, player2, score2. Order doesn’t matter.
Extra columns are allowed. Column game for game identifier is optional.
Example of correct wide format:
cr_wide_raw <- tibble(
player1 = c(1, 1, 2),
score1 = -(1:3),
player2 = c(2, 3, 3),
score2 = -(4:6)
)To convert cr_wide_raw into widecr object
use as_widecr():
cr_wide <- cr_wide_raw %>% as_widecr()
cr_wide
#> # A widecr object:
#> # A tibble: 3 × 4
#> player1 score1 player2 score2
#> <dbl> <int> <dbl> <int>
#> 1 1 -1 2 -4
#> 2 1 -2 3 -5
#> 3 2 -3 3 -6By default, as_widecr() also does repairing of its
input:
tibble(
score = 2,
PlayerRS = "a",
scoreRS = 1,
player = "b",
player1 = "c",
extra = -1,
game = "game"
) %>%
as_widecr()
#> as_widecr: Some matched names are not perfectly matched:
#> player -> player1
#> score -> score1
#> player1 -> player2
#> PlayerRS -> player3
#> scoreRS -> score3
#> as_widecr: Next columns are not found. Creating with NAs.
#> score2
#> # A widecr object:
#> # A tibble: 1 × 8
#> game player1 score1 player2 score2 player3 score3 extra
#> <chr> <chr> <dbl> <chr> <int> <chr> <dbl> <dbl>
#> 1 game b 2 c NA a 1 -1as_longcr() and as_widecr() do actual
conversion applied to widecr and longcr
objects respectively:
as_longcr(cr_wide)
#> # A longcr object:
#> # A tibble: 6 × 3
#> game player score
#> <int> <dbl> <int>
#> 1 1 1 -1
#> 2 1 2 -4
#> 3 2 1 -2
#> 4 2 3 -5
#> 5 3 2 -3
#> 6 3 3 -6
# Determines number of players in game as
# actual maximum number of players in games
as_widecr(cr_long)
#> # A widecr object:
#> # A tibble: 4 × 7
#> game player1 score1 player2 score2 player3 score3
#> <dbl> <dbl> <int> <dbl> <int> <dbl> <int>
#> 1 1 1 1 NA 2 NA 3
#> 2 2 1 4 2 5 NA NA
#> 3 3 2 6 1 7 NA NA
#> 4 4 2 8 NA NA NA NAcomperes expect data that can be a proper
input to as_longcr(), i.e. longcr object,
widecr object, or raw data aligned with long format.comperes is
to have three data frames:
game for game identifiers).player for player identifiers).