這是我的資料：
game_id team opponent steals assists
<int> <chr> <chr> <chr> <chr>
1 401468360 Spurs Warriors 6 18
2 401468360 Warriors Spurs 9 35
3 401468358 Clippers Rockets 6 25
4 401468358 Rockets Clippers 11 20
5 401468359 Hawks Bucks 4 23
6 401468359 Bucks Hawks 4 21
7 401468356 Thunder Celtics 4 21
8 401468356 Celtics Thunder 15 25
9 401468357 Suns Heat 9 22
10 401468357 Heat Suns 6 3
如何以以下格式獲取此資料？
game_id team opponent team_steals opp_assists team_assists opp_steals
<int> <chr> <chr> <int> <chr> <chr> <chr>
1 401468360 Spurs Warriors 6 9 18 35
2 401468358 Clippers Rockets 6 11 25 20
3 401468359 Hawks Bucks 4 4 23 21
4 401468356 Thunder Celtics 4 15 21 25
9 401468357 Suns Heat 9 6 22 23
我嘗試了幾種pivot_wider無濟于事的變體。我什至不確定該功能是否能完成我所尋求的。
uj5u.com熱心網友回復：
library(dplyr)
dat %>%
right_join(dat, by = c("game_id", "team" = "opponent", "opponent" = "team"),
suffix = c("_team", "_opponent")) %>%
distinct(game_id, .keep_all = TRUE)
#> game_id team opponent steals_team steals_opponent assists_team assists_opponent
#> 1 401468360 Spurs Warriors 6 9 18 35
#> 2 401468358 Clippers Rockets 6 11 25 20
#> 3 401468359 Hawks Bucks 4 4 23 21
#> 4 401468356 Thunder Celtics 4 15 21 25
#> 5 401468357 Suns Heat 9 6 22 3
uj5u.com熱心網友回復：
是這樣的：
library(dplyr)
library(tidyr)
df %>%
group_by(game_id) %>%
rename(team_steals = steals) %>%
mutate(opp_steals = lead(team_steals)) %>%
rename(team_assists = assists) %>%
mutate(opp_assists = lead(team_assists)) %>%
drop_na()
game_id team opponent team_steals team_assists opp_steals opp_assists
<int> <chr> <chr> <int> <int> <int> <int>
1 401468360 Spurs Warriors 6 18 9 35
2 401468358 Clippers Rockets 6 25 11 20
3 401468359 Hawks Bucks 4 23 4 21
4 401468356 Thunder Celtics 4 21 15 25
5 401468357 Suns Heat 9 22 6 3
uj5u.com熱心網友回復：
與一些資料整理一起使用的選項pivot_wider可能如下所示：
library(dplyr, w = FALSE)
library(tidyr)
dat |>
group_by(game_id) |>
mutate(foo = c("team", "opp"), across(c(team, opponent), first)) |>
ungroup() |>
tidyr::pivot_wider(names_from = foo, values_from = c(steals, assists), names_glue = "{foo}_{.value}")
#> # A tibble: 5 × 7
#> game_id team opponent team_steals opp_steals team_assists opp_assists
#> <int> <chr> <chr> <int> <int> <int> <int>
#> 1 401468360 Spurs Warriors 6 9 18 35
#> 2 401468358 Clippers Rockets 6 11 25 20
#> 3 401468359 Hawks Bucks 4 4 23 21
#> 4 401468356 Thunder Celtics 4 15 21 25
#> 5 401468357 Suns Heat 9 6 22 3
資料
dat <- structure(list(game_id = c(
401468360L, 401468360L, 401468358L,
401468358L, 401468359L, 401468359L, 401468356L, 401468356L, 401468357L,
401468357L
), team = c(
"Spurs", "Warriors", "Clippers", "Rockets",
"Hawks", "Bucks", "Thunder", "Celtics", "Suns", "Heat"
), opponent = c(
"Warriors",
"Spurs", "Rockets", "Clippers", "Bucks", "Hawks", "Celtics",
"Thunder", "Heat", "Suns"
), steals = c(
6L, 9L, 6L, 11L, 4L, 4L,
4L, 15L, 9L, 6L
), assists = c(
18L, 35L, 25L, 20L, 23L, 21L, 21L,
25L, 22L, 3L
)), class = "data.frame", row.names = c(
"1", "2",
"3", "4", "5", "6", "7", "8", "9", "10"
))
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