Import two related datasets from TidyTuesday Project.
game_goals <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-03/game_goals.csv')## Rows: 49384 Columns: 25
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (7): player, age, team, at, opp, location, outcome
## dbl (17): season, rank, game_num, goals, assists, points, plus_minus, penal...
## date (1): date
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.season_goals <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-03/season_goals.csv')## Rows: 4810 Columns: 23
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (9): position, hand, player, years, status, season, team, league, headshot
## dbl (14): rank, total_goals, yr_start, age, season_games, goals, assists, po...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Describe the two datasets:
Data1: Season Goals
Data 2: Game Goals
set.seed(1972)
season_goals_small <- season_goals %>% select(rank, player, total_goals) %>% sample_n(10)
game_goals_small <- game_goals %>% select(rank, player, goals) %>% sample_n(10)Describe the resulting data:
How is it different from the original two datasets? 1 row compared to 10 in original small data sets
season_goals_small %>% inner_join(game_goals_small, by = c("rank"))## # A tibble: 1 × 5
## rank player.x total_goals player.y goals
## <dbl> <chr> <dbl> <chr> <dbl>
## 1 32 Stan Mikita 541 Wayne Gretzky 0Describe the resulting data:
How is it different from the original two datasets? 5 columns as opposed to 3. 10 rows
season_goals_small %>% left_join(game_goals_small, by = c("rank"))## # A tibble: 10 × 5
## rank player.x total_goals player.y goals
## <dbl> <chr> <dbl> <chr> <dbl>
## 1 49 Brian Bellows 485 <NA> NA
## 2 160 Ed Olczyk 342 <NA> NA
## 3 135 Miroslav Satan 363 <NA> NA
## 4 32 Stan Mikita 541 Wayne Gretzky 0
## 5 4 Brett Hull 741 <NA> NA
## 6 156 Jonathan Toews 343 <NA> NA
## 7 237 Mike Fisher 278 <NA> NA
## 8 230 Dick Duff 283 <NA> NA
## 9 212 Jason Pominville 293 <NA> NA
## 10 77 Brian Propp 425 <NA> NADescribe the resulting data:
How is it different from the original two datasets? 5 columns as opposed to 3. 10 rows
season_goals_small %>% right_join(game_goals_small, by = c("rank"))## # A tibble: 10 × 5
## rank player.x total_goals player.y goals
## <dbl> <chr> <dbl> <chr> <dbl>
## 1 32 Stan Mikita 541 Wayne Gretzky 0
## 2 17 <NA> NA Alex Ovechkin 0
## 3 24 <NA> NA Brendan Shanahan 0
## 4 53 <NA> NA Anze Kopitar 0
## 5 70 <NA> NA Dino Ciccarelli 0
## 6 27 <NA> NA Mark Messier 0
## 7 52 <NA> NA Jaromir Jagr 1
## 8 72 <NA> NA Patrick Kane 1
## 9 27 <NA> NA John Tavares 0
## 10 53 <NA> NA Corey Perry 0Describe the resulting data:
How is it different from the original two datasets? 5 columns as opposed to 3. 19 rows instead of 10
season_goals_small %>% full_join(game_goals_small, by = c("rank"))## # A tibble: 19 × 5
## rank player.x total_goals player.y goals
## <dbl> <chr> <dbl> <chr> <dbl>
## 1 49 Brian Bellows 485 <NA> NA
## 2 160 Ed Olczyk 342 <NA> NA
## 3 135 Miroslav Satan 363 <NA> NA
## 4 32 Stan Mikita 541 Wayne Gretzky 0
## 5 4 Brett Hull 741 <NA> NA
## 6 156 Jonathan Toews 343 <NA> NA
## 7 237 Mike Fisher 278 <NA> NA
## 8 230 Dick Duff 283 <NA> NA
## 9 212 Jason Pominville 293 <NA> NA
## 10 77 Brian Propp 425 <NA> NA
## 11 17 <NA> NA Alex Ovechkin 0
## 12 24 <NA> NA Brendan Shanahan 0
## 13 53 <NA> NA Anze Kopitar 0
## 14 70 <NA> NA Dino Ciccarelli 0
## 15 27 <NA> NA Mark Messier 0
## 16 52 <NA> NA Jaromir Jagr 1
## 17 72 <NA> NA Patrick Kane 1
## 18 27 <NA> NA John Tavares 0
## 19 53 <NA> NA Corey Perry 0Describe the resulting data:
How is it different from the original two datasets? 3 columns 1 row opposed to 10
season_goals_small %>% semi_join(game_goals_small, by = c("rank"))## # A tibble: 1 × 3
## rank player total_goals
## <dbl> <chr> <dbl>
## 1 32 Stan Mikita 541Describe the resulting data:
How is it different from the original two datasets? 3 colums 9 rows compared to 10
season_goals_small %>% anti_join(game_goals_small, by = c("rank"))## # A tibble: 9 × 3
## rank player total_goals
## <dbl> <chr> <dbl>
## 1 49 Brian Bellows 485
## 2 160 Ed Olczyk 342
## 3 135 Miroslav Satan 363
## 4 4 Brett Hull 741
## 5 156 Jonathan Toews 343
## 6 237 Mike Fisher 278
## 7 230 Dick Duff 283
## 8 212 Jason Pominville 293
## 9 77 Brian Propp 425