Import data

# excel file
data <- read_excel("../00_data/MyData.xlsx")
data_min <- data %>%
    filter(Goals %% 1 == 0) %>%
    select(Opponent, Shots, `Shots on goal`)

data_min
## # A tibble: 18 × 3
##    Opponent                                              Shots `Shots on goal`
##    <chr>                                                 <dbl>           <dbl>
##  1 vs New England Pilgrims                                   5               2
##  2 @ University of New England Nor'easters                  10               4
##  3 @ Babson Beavers                                          6               4
##  4 vs SUNY-Plattsburgh Cardinals                             3               0
##  5 @ New England Pilgrims                                    4               2
##  6 vs Worcester State Lancers                               10               4
##  7 vs Framingham State Rams                                  0               0
##  8 @ Salem State Univ.                                       6               1
##  9 vs Trinity Bantams                                        8               3
## 10 @ UMass Dartmouth Corsairs                                6               3
## 11 vs Westfield State Owls                                   9               4
## 12 @ Hamilton Continentals                                   4               3
## 13 @ Williams Ephs                                           7               4
## 14 @ Rivier University Raiders                               3               0
## 15 vs Fitchburg State Falcons                                8               7
## 16 @ Worcester State Lancers                                 5               2
## 17 vs Massachusetts College of Liberal Arts Trailblazers     6               3
## 18 @ Anna Maria Amcats                                       9               6

Pivoting

long to wide form

data_wide <- data_min %>%
    pivot_wider(names_from = Shots,
                values_from = `Shots on goal`)

data_wide
## # A tibble: 18 × 10
##    Opponent                  `5`  `10`   `6`   `3`   `4`   `0`   `8`   `9`   `7`
##    <chr>                   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
##  1 vs New England Pilgrims     2    NA    NA    NA    NA    NA    NA    NA    NA
##  2 @ University of New En…    NA     4    NA    NA    NA    NA    NA    NA    NA
##  3 @ Babson Beavers           NA    NA     4    NA    NA    NA    NA    NA    NA
##  4 vs SUNY-Plattsburgh Ca…    NA    NA    NA     0    NA    NA    NA    NA    NA
##  5 @ New England Pilgrims     NA    NA    NA    NA     2    NA    NA    NA    NA
##  6 vs Worcester State Lan…    NA     4    NA    NA    NA    NA    NA    NA    NA
##  7 vs Framingham State Ra…    NA    NA    NA    NA    NA     0    NA    NA    NA
##  8 @ Salem State Univ.        NA    NA     1    NA    NA    NA    NA    NA    NA
##  9 vs Trinity Bantams         NA    NA    NA    NA    NA    NA     3    NA    NA
## 10 @ UMass Dartmouth Cors…    NA    NA     3    NA    NA    NA    NA    NA    NA
## 11 vs Westfield State Owls    NA    NA    NA    NA    NA    NA    NA     4    NA
## 12 @ Hamilton Continentals    NA    NA    NA    NA     3    NA    NA    NA    NA
## 13 @ Williams Ephs            NA    NA    NA    NA    NA    NA    NA    NA     4
## 14 @ Rivier University Ra…    NA    NA    NA     0    NA    NA    NA    NA    NA
## 15 vs Fitchburg State Fal…    NA    NA    NA    NA    NA    NA     7    NA    NA
## 16 @ Worcester State Lanc…     2    NA    NA    NA    NA    NA    NA    NA    NA
## 17 vs Massachusetts Colle…    NA    NA     3    NA    NA    NA    NA    NA    NA
## 18 @ Anna Maria Amcats        NA    NA    NA    NA    NA    NA    NA     6    NA

Separating and Uniting

seperate

data_min %>% 
  separate(Opponent, into = c("Venue", "Team"), sep = 2) %>%
    mutate(Team = str_trim(Team, side = "left"),
           Venue = str_trim(Venue, side = "right"))
## # A tibble: 18 × 4
##    Venue Team                                              Shots `Shots on goal`
##    <chr> <chr>                                             <dbl>           <dbl>
##  1 vs    New England Pilgrims                                  5               2
##  2 @     University of New England Nor'easters                10               4
##  3 @     Babson Beavers                                        6               4
##  4 vs    SUNY-Plattsburgh Cardinals                            3               0
##  5 @     New England Pilgrims                                  4               2
##  6 vs    Worcester State Lancers                              10               4
##  7 vs    Framingham State Rams                                 0               0
##  8 @     Salem State Univ.                                     6               1
##  9 vs    Trinity Bantams                                       8               3
## 10 @     UMass Dartmouth Corsairs                              6               3
## 11 vs    Westfield State Owls                                  9               4
## 12 @     Hamilton Continentals                                 4               3
## 13 @     Williams Ephs                                         7               4
## 14 @     Rivier University Raiders                             3               0
## 15 vs    Fitchburg State Falcons                               8               7
## 16 @     Worcester State Lancers                               5               2
## 17 vs    Massachusetts College of Liberal Arts Trailblaze…     6               3
## 18 @     Anna Maria Amcats                                     9               6

untite two columns

data %>%
    unite(col = "Failed Shots", c(`Blocked shots`, `Missed shots`), sep = "/") %>%
    select(Opponent, `Failed Shots`, Shots, `Shots on goal`)
## # A tibble: 19 × 4
##    Opponent                                 `Failed Shots` Shots `Shots on goal`
##    <chr>                                    <chr>          <dbl>           <dbl>
##  1 vs New England Pilgrims                  3/0              5                 2
##  2 @ University of New England Nor'easters  2/4             10                 4
##  3 @ Babson Beavers                         0/2              6                 4
##  4 vs SUNY-Plattsburgh Cardinals            3/0              3                 0
##  5 @ New England Pilgrims                   2/0              4                 2
##  6 vs Worcester State Lancers               2/4             10                 4
##  7 vs Framingham State Rams                 0/0              0                 0
##  8 @ Salem State Univ.                      3/2              6                 1
##  9 vs Trinity Bantams                       5/0              8                 3
## 10 @ UMass Dartmouth Corsairs               3/0              6                 3
## 11 vs Westfield State Owls                  3/2              9                 4
## 12 @ Hamilton Continentals                  0/1              4                 3
## 13 @ Williams Ephs                          2/1              7                 4
## 14 @ Rivier University Raiders              3/0              3                 0
## 15 vs Fitchburg State Falcons               0/1              8                 7
## 16 @ Worcester State Lancers                3/0              5                 2
## 17 vs Massachusetts College of Liberal Art… 3/0              6                 3
## 18 @ Anna Maria Amcats                      2/1              9                 6
## 19 Average per game                         1.77/1.1         5.8               3
data %>%
    mutate(`Failed Shots` = `Blocked shots` + `Missed shots`) %>%
    select(Opponent, `Failed Shots`, Shots, `Shots on goal`)
## # A tibble: 19 × 4
##    Opponent                                 `Failed Shots` Shots `Shots on goal`
##    <chr>                                             <dbl> <dbl>           <dbl>
##  1 vs New England Pilgrims                            3      5                 2
##  2 @ University of New England Nor'easters            6     10                 4
##  3 @ Babson Beavers                                   2      6                 4
##  4 vs SUNY-Plattsburgh Cardinals                      3      3                 0
##  5 @ New England Pilgrims                             2      4                 2
##  6 vs Worcester State Lancers                         6     10                 4
##  7 vs Framingham State Rams                           0      0                 0
##  8 @ Salem State Univ.                                5      6                 1
##  9 vs Trinity Bantams                                 5      8                 3
## 10 @ UMass Dartmouth Corsairs                         3      6                 3
## 11 vs Westfield State Owls                            5      9                 4
## 12 @ Hamilton Continentals                            1      4                 3
## 13 @ Williams Ephs                                    3      7                 4
## 14 @ Rivier University Raiders                        3      3                 0
## 15 vs Fitchburg State Falcons                         1      8                 7
## 16 @ Worcester State Lancers                          3      5                 2
## 17 vs Massachusetts College of Liberal Art…           3      6                 3
## 18 @ Anna Maria Amcats                                3      9                 6
## 19 Average per game                                   2.87   5.8               3