### Development setup commands for sdvplotR

Source: https://sdvplotr.sportsdataverse.org/CONTRIBUTING.html

Install required R packages and run the standard devtools workflow (load_all, test, document, check). Requires R >= 4.1.

```r
# R >= 4.1
install.packages(c("devtools", "roxygen2", "testthat", "pkgdown", "styler", "lintr"))
devtools::load_all()
devtools::test()
devtools::document()
devtools::check()
```

--------------------------------

### Install sdvplotR using pak

Source: https://sdvplotr.sportsdataverse.org/index.html

Recommended installation method for the R package sdvplotR. Installs the pak package if not already available, then installs sdvplotR from GitHub.

```r
if (!requireNamespace("pak", quietly = TRUE)) {
  install.packages("pak")
}
pak::pak("sportsdataverse/sdvplotR")
```

--------------------------------

### Setup: Load libraries and get team abbreviations

Source: https://sdvplotr.sportsdataverse.org/articles/leaderboard-dashboards.html

Loads required packages (sdvplotR, ggplot2, dplyr, gt) and retrieves valid team abbreviations for NFL, NBA, and CFB using sdv_teams().

```r
library(sdvplotR)
library(ggplot2)
library(dplyr)
library(gt)

# Get valid team abbreviations
nfl_teams <- sdv_teams("nfl")$abbr
nba_teams <- sdv_teams("nba")$abbr
cfb_teams <- sdv_teams("cfb")$abbr

```

--------------------------------

### gt_sdv_wordmarks example

Source: https://sdvplotr.sportsdataverse.org/reference/gt_sdv_wordmarks.html

Creates a gt table with team wordmarks for NFL teams. The example is wrapped in \donttest{} and requires the gt package.

```r
# \donttest{
library(gt)
df <- data.frame(team = c("KC", "BUF", "SF"), wins = c(14, 13, 12))
df |>
  gt() |>
  gt_sdv_wordmarks(columns = "team", league = "nfl")



  team
      | wins
      
---|---  

| 14  

| 13  

| 12  
# }

```

--------------------------------

### Load gt and create subset data for gt_spotlight examples

Source: https://sdvplotr.sportsdataverse.org/reference/gt_spotlight.html

Loads the gt package and creates a subset of the sdv_example_standings data containing NFC North and NFC West teams with selected columns. This data is used in all subsequent examples.

```r
library(gt)

nfc <- subset(
  sdv_example_standings, division %in% c("NFC North", "NFC West"),
  c(team_name, wins, losses, conference_rank)
)
```

--------------------------------

### Install development version of sdvplotR from GitHub

Source: https://sdvplotr.sportsdataverse.org/index.html

Installs the development version of sdvplotR from GitHub.

```r
remotes::install_github("sportsdataverse/sdvplotR")
```

--------------------------------

### Install sdvplotR from R-universe

Source: https://sdvplotr.sportsdataverse.org/index.html

Alternative installation method for the R package sdvplotR using binary builds from R-universe.

```r
install.packages("sdvplotR", repos = c("https://sportsdataverse.r-universe.dev", "https://cloud.r-project.org"))
```

--------------------------------

### sdv_leagues() example with output

Source: https://sdvplotr.sportsdataverse.org/reference/sdv_leagues.html

Example call to sdv_leagues() showing the returned sorted character vector of league keys, including 'aaf', 'cfb', 'mlb', 'nfl', 'wnba', and others.

```r
sdv_leagues()
#>  [1] "aaf"           "ahl"           "cfb"           "cricket"      
#>  [5] "echl"          "mbb"           "milb"          "mlb"          
#>  [9] "nba"           "nbagl"         "ncaa_baseball" "ncaa_mhockey" 
#> [13] "ncaa_softball" "ncaa_whockey"  "nfl"           "nhl"          
#> [17] "ohl"           "phf"           "pwhl"          "qmjhl"        
#> [21] "soccer"        "ufl"           "usfl"          "ushl"         
#> [25] "wbb"           "whl"           "wnba"          "xfl"          
```

--------------------------------

### Load libraries and define helpers for season selection

Source: https://sdvplotr.sportsdataverse.org/articles/leaderboard-mlb.html

Sets up the environment and defines helper functions: `live()` wraps API calls to return NULL on error, `unavailable()` formats a note, and `standings_for()` fetches standings or returns NULL before opening day. It then determines the season, checks availability, and builds a status message using the MLB Stats API calendar.

```r
library(sdvplotR)
library(dplyr, warn.conflicts = FALSE)
library(ggplot2)
library(gt)

today <- Sys.Date()
current <- as.integer(format(today, "%Y")) # the season runs inside one calendar year

# A live API call, or NULL when the API does not answer: one bad week then shows
# a note in place of a table instead of failing the whole site build
live <- function(expr) tryCatch(expr, error = function(e) NULL)
unavailable <- function(what, ok) {
  if (ok) "" else sprintf("*%s were unavailable when this page was built on %s; they return next week.*", what, today)
}

# A season's standings from the MLB Stats API, or NULL before opening day: the
# API answers with no rows for a season it has no standings for, or with every
# team on zero games
standings_for <- function(season) {
  table <- live(baseballr::mlb_standings(season = season, league_id = "103,104"))
  if (NROW(table) == 0 || max(table$team_records_games_played) == 0) NULL else table
}

season <- current
raw_standings <- standings_for(season)
if (is.null(raw_standings)) {
  season <- current - 1
  raw_standings <- standings_for(season)
}
# last season always has standings, so none for either season means the API did not answer
available <- !is.null(raw_standings)
leaders_ok <- FALSE

# The Stats API's calendar for the current season: when its regular season and
# postseason end
calendar <- live(baseballr::mlb_seasons(sport_id = 1))
regular_end <- as.Date(as.character(calendar$regular_season_end_date[calendar$season_id == current]))
post_end <- as.Date(as.character(calendar$post_season_end_date[calendar$season_id == current]))
games_per_team <- if (available) round(median(raw_standings$team_records_games_played)) else NA
if (!available) {
  status <- "the MLB Stats API did not answer when this page was built, so this week's tables and chart are missing; they return next week."
  through <- ""
} else if (season < current) {
  status <- sprintf(
    "the offseason, so this is the final %d regular season; the %d season has no games yet.",
    season, current
  )
  through <- "final regular season"
} else if (length(regular_end) == 1 && today <= regular_end) {
  status <- sprintf("the %d season to date, about %d games per team.", season, games_per_team)
  through <- paste("through", games_per_team, "games")
} else if (length(post_end) == 1 && today <= post_end) {
  status <- sprintf("the final %d regular season; the postseason is under way.", season)
  through <- "final regular season"
} else {
  status <- sprintf("the offseason, so this is the final %d regular season.", season)
  through <- "final regular season"
}
```

--------------------------------

### Apply locally installed font with gt_set_font

Source: https://sdvplotr.sportsdataverse.org/reference/gt_set_font.html

Use gt_set_font with from_google_font = FALSE to apply a font that is already installed on the system. The example uses Helvetica on the nfc_south table.

```r
gt(nfc_south) |> gt_set_font("Helvetica", from_google_font = FALSE)
```

--------------------------------

### Example: geom_sdv_wordmarks with NFL teams

Source: https://sdvplotr.sportsdataverse.org/reference/geom_sdv_wordmarks.html

Creates a ggplot2 plot with wordmarks for the first eight NFL teams. Uses sdv_teams() to get team abbreviations, sets width to 0.12, and adds labels with nudge_y. The example is wrapped in \donttest{}.

```r
# \donttest{
library(sdvplotR)
library(ggplot2)

team_abbr <- sdv_teams("nfl")$abbr[1:8]

df <- data.frame(
  a = rep(1:4, 2),
  b = sort(rep(1:2, 4), decreasing = TRUE),
  teams = team_abbr
)

ggplot(df, aes(x = a, y = b)) +
  geom_sdv_wordmarks(aes(team = teams), league = "nfl", width = 0.12) +
  geom_label(aes(label = teams), nudge_y = -0.20, alpha = 0.5) +
  scale_x_continuous(expand = expansion(add = 0.5)) +
  theme_void()
}
```

--------------------------------

### Load sdvplotR and set up plotting environment

Source: https://sdvplotr.sportsdataverse.org/articles/cookbook-colors-themes.html

Initial setup for using sdvplotR. Loads the package and required libraries for plotting.

```r
library(sdvplotR)
library(ggplot2)
library(dplyr)
```

--------------------------------

### Setup: Load libraries and set output directory

Source: https://sdvplotr.sportsdataverse.org/articles/workflows.html

Loads sdvplotR, ggplot2, dplyr, and gt, and sets a temporary output directory. Companion packages are called with pkg:: as needed. Exports go to the temporary directory; point this at your own folder.

```r
library(sdvplotR)
library(ggplot2)
library(dplyr)
library(gt)

# Companion packages, called with pkg:: below:
# nflfastR / nflreadr (NFL), cfbfastR + cfbseedR (CFB), hoopR (NBA, MBB),
# wehoop (WNBA, WBB), baseballr (MLB), fastRhockey (NHL), oddsapiR (odds)

# Exports go to a temporary directory; point this at your own folder
out_dir <- tempdir()
```

--------------------------------

### Add image to ggplot title with ggtitle_image()

Source: https://sdvplotr.sportsdataverse.org/reference/ggtitle_image.html

Loads sdvplotR and ggplot2, filters example standings for NFL, creates a scatter plot, and adds a title image using ggtitle_image() with theme_title_image() for styling. Requires the ggtext package to be installed; the example is wrapped in \donttest{}.

```R
# \donttest{
library(sdvplotR)
library(ggplot2)

nfl <- subset(sdv_example_standings, league == "nfl")
p <- ggplot(nfl, aes(x = points_for, y = points_against)) +
  geom_point() +
  labs(
    title = "This Title will be overwritten",
    subtitle = "Points scored and allowed, 2025 regular season"
  )

if (requireNamespace("ggtext", quietly = TRUE)) {
  p +
    ggtitle_image(
      title_image = "SEA",
      title = "Seattle Seahawks Analysis",
      image_height = 20,
      image_side = "left",
      league = "nfl"
    ) +
    theme_title_image(size = 20, hjust = 0.5)
}

# }
```

--------------------------------

### Setup: Load libraries and set theme

Source: https://sdvplotr.sportsdataverse.org/articles/mbb-viz.html

Loads sdvplotR, ggplot2, dplyr, tidyr, and gt, then sets season, label, source note, and a common ggplot2 theme for all visualizations.

```r
library(sdvplotR)
library(ggplot2)
library(dplyr)
library(tidyr)
library(gt)

season <- 2026 # the 2025-26 season: hoopR names a season by the year it ends
label <- "2025-26"
source_note <- "Data: hoopR (ESPN) | Viz: sdvplotR"

theme_set(
  theme_minimal(base_size = 12) +
    theme(
      plot.title = element_text(face = "bold"),
      plot.title.position = "plot",
      plot.caption = element_text(color = "grey40", size = 8),
      plot.caption.position = "plot",
      panel.grid.minor = element_blank()
    )
)
```

--------------------------------

### gt_set_font("Helvetica", from_google_font = FALSE)

Source: https://sdvplotr.sportsdataverse.org/reference/gt_set_font.html

Sets the font for a gt table to a locally installed font. The example applies Helvetica to the nfc_south table.

```APIDOC
## gt_set_font

### Description
Sets the font for a gt table. This example uses a locally installed font (Helvetica) by setting `from_google_font = FALSE`.

### Usage
```r
gt(nfc_south) |> gt_set_font("Helvetica", from_google_font = FALSE)
```

### Arguments
- **font** (character) - Required - The name of the font to use.
- **from_google_font** (logical) - Optional - Whether the font is from Google Fonts. Default is `TRUE`; set to `FALSE` to use a locally installed font.

### Value
A `gt_tbl` object with the font applied.

### Example
```r
gt(nfc_south) |> gt_set_font("Helvetica", from_google_font = FALSE)
```

### Notes
- The example uses the `nfc_south` data frame, which contains team statistics.
- The resulting table displays columns: team_name, wins, losses, ties, win_pct, points_for, points_against.
```

--------------------------------

### Create a gt table with dark theme and logos using gt_sdv_logos() and gt_theme_midnight()

Source: https://sdvplotr.sportsdataverse.org/articles/cookbook-colors-themes.html

Builds a gt table of the top five WNBA teams by scoring margin, using gt_sdv_logos() to add logos and gt_theme_midnight() for the dark theme. The table's background matches the chart's background from the previous example.

```R
dark |>
  arrange(desc(diff), team) |>
  head(5) |>
  select(team, pf, pa, diff) |>
  gt() |>
  gt_sdv_logos(columns = team, league = "wnba") |>
  fmt_number(columns = c(pf, pa, diff), decimals = 1) |>
  cols_label(team = "", pf = "Scored", pa = "Allowed", diff = "Margin") |>
  tab_header(title = "The WNBA's best margins, 2026") |>
  gt_theme_midnight()
```

--------------------------------

### Create a preview grid of gt themes with gt_theme_preview

Source: https://sdvplotr.sportsdataverse.org/reference/gt_theme_preview.html

Builds a data frame from sdv_example_standings and passes it to gt_theme_preview with three themes. The output is a browsable grid of preview tables, one per theme, captioned with the theme name.

```r
nfl <- subset(
  sdv_example_standings, league == "nfl",
  c(team_name, wins, losses, win_pct)
)
gt_theme_preview(
  nfl,
  themes = c("gt_theme_sdv", "gt_theme_kenpom", "gt_theme_athletic")
)
```

--------------------------------

### Apply gt_theme_drench to a gt table

Source: https://sdvplotr.sportsdataverse.org/reference/gt_theme_drench.html

Creates a gt table from a subset of the sdv_example_standings data and applies the drench theme. The example includes a conditional block that runs only in interactive sessions with webshot2 and Chrome installed.

```r
library(gt)
southwest <- subset(
  sdv_example_standings, division == "Southwest",
  c(team_name, wins, losses, win_pct:points_against)
)
gt(southwest) |> gt_theme_drench()
```

```r
if (FALSE) { # interactive() && rlang::is_installed("webshot2") && isTRUE(file.exists(chromote::find_chrome()))
```

--------------------------------

### Load libraries and set up season, conference, and output directory

Source: https://sdvplotr.sportsdataverse.org/articles/recipe-cfb-conference-table.html

Loads sdvplotR, gt, and dplyr, then sets the season to 2025, conference to "Big Ten", and creates a temporary output directory for exports. Use your own folder in practice.

```r
library(sdvplotR)
library(gt)
library(dplyr, warn.conflicts = FALSE)

season <- 2025
conference <- "Big Ten"
out_dir <- tempfile("sdvplotR-recipe-") # where the exports go; use your own folder
dir.create(out_dir)
```

--------------------------------

### Create bar chart with scale_x_sdv and theme_x_sdv

Source: https://sdvplotr.sportsdataverse.org/reference/theme_sdv.html

Loads sdvplotR and ggplot2, gets NFL team abbreviations, creates a data frame with random values, and plots a bar chart with custom x-axis scale and theme. The plot is only rendered if ggtext is installed.

```R
# \donttest{
library(sdvplotR)
library(ggplot2)

team_abbr <- sdv_teams("nfl")$abbr[1:8]

df <- data.frame(
  random_value = runif(length(team_abbr), 0, 1),
  teams = team_abbr
)

if (requireNamespace("ggtext", quietly = TRUE)) {
  ggplot(df, aes(x = teams, y = random_value)) +
    geom_col(width = 0.5) +
    scale_x_sdv(league = "nfl") +
    theme_minimal() +
    theme_x_sdv()
}

# }
```

--------------------------------

### Setup libraries and directories for WBB standings recipe

Source: https://sdvplotr.sportsdataverse.org/articles/recipe-wbb-conference-standings.html

Loads sdvplotR, gt, and dplyr, sets the season to 2026 (2025-26), conference to SEC, and creates an output directory using tempfile().

```r
library(sdvplotR)
library(gt)
library(dplyr, warn.conflicts = FALSE)

season <- 2026 # the 2025-26 season, named by the year it ends
conference <- "SEC"
out_dir <- tempfile("sdvplotR-recipe-") # where the exports go; use your own folder
dir.create(out_dir)
```

--------------------------------

### plotly: helper function to create logo images

Source: https://sdvplotr.sportsdataverse.org/articles/cookbook-interactive.html

Defines a helper function that builds a list of plotly layout images from team names and positions. It uses sdv_logo_url() to get the logo URLs and positions each image in data units. This function is used in the subsequent plotly examples.

```R
logo_images <- function(teams, x, y, sport, sizex, sizey = sizex, xref = "x", yref = "y") {
  urls <- sdv_logo_url(teams, league = sport)
  lapply(seq_along(urls), function(i) {
    list(
      source = urls[i], xref = xref, yref = yref, x = x[i], y = y[i],
      sizex = sizex, sizey = sizey, xanchor = "center", yanchor = "middle", layer = "above"
    )
  })
}
```

--------------------------------

### Call sdv_versions() to show data versions

Source: https://sdvplotr.sportsdataverse.org/reference/sdv_versions.html

Returns a list with package, index_version, index_source, manifest_rows, and manifest_source. The example output shows index_source and manifest_source as 'live'.

```r
sdv_versions()
```

```r
sdv_versions()
#> $package
#> [1] "0.1.0"
#> 
#> $index_version
#> [1] "0aeef853ec2b"
#> 
#> $index_source
#> [1] "live"
#> 
#> $manifest_rows
#> [1] 44462
#> 
#> $manifest_source
#> [1] "live"
#> 
```

--------------------------------

### Example: Apply gt_theme_midnight to a gt table

Source: https://sdvplotr.sportsdataverse.org/reference/gt_theme_midnight.html

Creates a gt table from the NFC West subset of sdv_example_standings and applies the midnight theme. The output is a rendered table with team statistics.

```r
library(gt)
nfc_west <- subset(
  sdv_example_standings, division == "NFC West",
  c(team_name, wins:points_against)
)
gt(nfc_west) |> gt_theme_midnight()
```

```text
  team_name
      | wins
      | losses
      | ties
      | win_pct
      | points_for
      | points_against
      
---|---|---|---|---|---|---  
Seattle Seahawks
| 14
| 3
| 0
| 0.824
| 483
| 292  
Los Angeles Rams
| 12
| 5
| 0
| 0.706
| 518
| 346  
San Francisco 49ers
| 12
| 5
| 0
| 0.706
| 437
| 371  
Arizona Cardinals
| 3
| 14
| 0
| 0.176
| 355
| 488  
```

--------------------------------

### sdv_teams("nfl") example with output

Source: https://sdvplotr.sportsdataverse.org/reference/sdv_teams.html

Call sdv_teams with the "nfl" league key to get a data frame of NFL teams. The output shows the first 13 rows of the resulting data frame, including columns for league, team_id, abbr, name, short_name, location, program, conference_id, conference, color_primary, and color_secondary.

```r
sdv_teams("nfl")
#>    league team_id abbr                  name short_name      location program
#> 1     nfl       1  ATL       Atlanta Falcons    Falcons       Atlanta     pro
#> 2     nfl      10  TEN      Tennessee Titans     Titans     Tennessee     pro
#> 3     nfl      11  IND    Indianapolis Colts      Colts  Indianapolis     pro
#> 4     nfl      12   KC    Kansas City Chiefs     Chiefs   Kansas City     pro
#> 5     nfl      13   LV     Las Vegas Raiders    Raiders     Las Vegas     pro
#> 6     nfl      14   LA      Los Angeles Rams       Rams   Los Angeles     pro
#> 7     nfl      15  MIA        Miami Dolphins   Dolphins         Miami     pro
#> 8     nfl      16  MIN     Minnesota Vikings    Vikings     Minnesota     pro
#> 9     nfl      17   NE  New England Patriots   Patriots   New England     pro
#> 10    nfl      18   NO    New Orleans Saints     Saints   New Orleans     pro
#> 11    nfl      19  NYG       New York Giants     Giants      New York     pro
#> 12    nfl       2  BUF         Buffalo Bills      Bills       Buffalo     pro
#> 13    nfl      20  NYJ         New York Jets       Jets      New York     pro
#> 14    nfl      21  PHI   Philadelphia Eagles     Eagles  Philadelphia     pro
#> 15    nfl      22  ARI     Arizona Cardinals  Cardinals       Arizona     pro
#> 16    nfl      23  PIT   Pittsburgh Steelers   Steelers    Pittsburgh     pro
#> 17    nfl      24  LAC  Los Angeles Chargers   Chargers   Los Angeles     pro
#> 18    nfl      25   SF   San Francisco 49ers      49ers San Francisco     pro
#> 19    nfl      26  SEA      Seattle Seahawks   Seahawks       Seattle     pro
#> 20    nfl      27   TB  Tampa Bay Buccaneers Buccaneers     Tampa Bay     pro
#> 21    nfl      28  WAS Washington Commanders Commanders    Washington     pro
#> 22    nfl      29  CAR     Carolina Panthers   Panthers      Carolina     pro
#> 23    nfl       3  CHI         Chicago Bears      Bears       Chicago     pro
#> 24    nfl      30  JAX  Jacksonville Jaguars    Jaguars  Jacksonville     pro
#> 25    nfl      33  BAL      Baltimore Ravens     Ravens     Baltimore     pro
#> 26    nfl      34  HOU        Houston Texans     Texans       Houston     pro
#> 27    nfl       4  CIN    Cincinnati Bengals    Bengals    Cincinnati     pro
#> 28    nfl       5  CLE      Cleveland Browns     Browns     Cleveland     pro
#> 29    nfl       6  DAL        Dallas Cowboys    Cowboys        Dallas     pro
#> 30    nfl       7  DEN        Denver Broncos    Broncos        Denver     pro
#> 31    nfl       8  DET         Detroit Lions      Lions       Detroit     pro
#> 32    nfl       9   GB     Green Bay Packers    Packers     Green Bay     pro
#>    conference_id                   conference color_primary color_secondary
#> 1        nfl:nfc National Football Conference       #a71930         #000000
#> 2        nfl:afc American Football Conference       #4495d2         #d50a0a
#> 3        nfl:afc American Football Conference       #002c5f         #a5acaf
#> 4        nfl:afc American Football Conference       #e31837         #ffb612
#> 5        nfl:afc American Football Conference       #000000         #a5acaf
#> 6        nfl:nfc National Football Conference       #003594         #ffd100
#> 7        nfl:afc American Football Conference       #008e97         #f58220
#> 8        nfl:nfc National Football Conference       #4f2683         #ffc62f
#> 9        nfl:afc American Football Conference       #002244         #c60c30
#> 10       nfl:nfc National Football Conference       #d3bc8d         #000000
#> 11       nfl:nfc National Football Conference       #0b2265         #a71930
#> 12       nfl:afc American Football Conference       #00338d         #c60c30
#> 13       nfl:afc American Football Conference       #003f2d         #000000
```

--------------------------------

### Map team colors to data rows with sdv_team_colors()

Source: https://sdvplotr.sportsdataverse.org/articles/cookbook-colors-themes.html

Uses sdv_team_colors() to add primary and secondary color columns to a data frame of NHL team statistics, then plots them with identity scales. The example uses fastRhockey::load_nhl_team_box() and shows the resulting head() output. Note that unresolved teams get NA and white secondary colors may disappear on white backgrounds.

```R
nhl_games <- fastRhockey::load_nhl_team_box(season) |>
  as.data.frame() |>
  filter(substr(game_id, 5, 6) == "02") # 02 = regular season

nhl_teams <- nhl_games |>
  summarise(gf = mean(goals), ga = mean(goals_against), .by = team_abbrev) |>
  arrange(desc(gf), team_abbrev) |>
  mutate(
    primary = unname(sdv_team_colors("nhl", team_abbrev)),
    secondary = unname(sdv_team_colors("nhl", team_abbrev, which = "secondary"))
  )
head(nhl_teams, 5)
#>   team_abbrev       gf       ga primary secondary
#> 1         COL 3.682927 2.243902 #860038   #005ea3
#> 2         CAR 3.609756 2.719512 #e30426   #000000
#> 3         PIT 3.573171 2.963415 #000000   #fdb71a
#> 4         TBL 3.536585 2.609756 #003e7e   #ffffff
#> 5         BUF 3.512195 2.695122 #00468b   #fdb71a

ggplot(nhl_teams, aes(x = gf, y = ga)) +
  geom_point(aes(fill = primary, colour = secondary), shape = 21, size = 6, stroke = 1.5) +
  ggrepel::geom_text_repel(aes(label = team_abbrev), size = 2.5, point.size = 6, seed = 1) +
  scale_fill_identity() +
  scale_colour_identity() +
  scale_y_reverse() +
  labs(
    title = "NHL goals for and against per game, 2025-26",
    x = "Goals for per game", y = "Goals against per game (reversed)",
    caption = "Data: fastRhockey::load_nhl_team_box()"
  ) +
  theme_minimal()
```

--------------------------------

### sdv_colorway() usage example

Source: https://sdvplotr.sportsdataverse.org/reference/sdv_colorway.html

Example usage of sdv_colorway() with a plotly bar chart, applying team colors for the NFL teams KC and BUF. The example is wrapped in a requireNamespace check for plotly.

```R
# \donttest{
if (requireNamespace("plotly", quietly = TRUE)) {
  plotly::plot_ly(type = "bar") |> sdv_colorway("nfl", c("KC", "BUF"))
}


# }
```

--------------------------------

### Load required libraries

Source: https://sdvplotr.sportsdataverse.org/articles/delay_tables.html

Loads the necessary packages for the examples: sdvplotR, gt, gtExtras, and dplyr.

```r
library(sdvplotR)
library(gt)
library(gtExtras)
library(dplyr)
```

--------------------------------

### Install sdvplotR from CRAN

Source: https://sdvplotr.sportsdataverse.org/index.html

Installs the released version of sdvplotR from CRAN once it is available.

```r
install.packages("sdvplotR")
```

--------------------------------

### Install JavaScript/TypeScript sdvplot packages

Source: https://sdvplotr.sportsdataverse.org/index.html

Install the npm packages @sportsdataverse/sdvplot, @sportsdataverse/sdvtables, and @sportsdataverse/sporty.

```bash
npm install @sportsdataverse/sdvplot @sportsdataverse/sdvtables @sportsdataverse/sporty
```

--------------------------------

### Load libraries and set up output directory

Source: https://sdvplotr.sportsdataverse.org/articles/recipe-mlb-run-differential.html

Loads required packages (sdvplotR, ggplot2, dplyr, patchwork) and creates a temporary output directory for exports. Replace the output directory with your own folder.

```r
library(sdvplotR)
library(ggplot2)
library(dplyr, warn.conflicts = FALSE)
library(patchwork)

season <- 2026
out_dir <- tempfile("sdvplotR-recipe-") # where the exports go; use your own folder
dir.create(out_dir)
```

--------------------------------

### Load libraries, set season, and fetch play-by-play

Source: https://sdvplotr.sportsdataverse.org/articles/leaderboard-cfb-weekly.html

Sets up the environment, determines the current season (stepping back if data is unavailable), and defines a function to load play-by-play with error handling. Uses cfbfastR::load_cfb_pbp() and handles NULL returns.

```R
library(sdvplotR)
library(dplyr, warn.conflicts = FALSE)
library(ggplot2)
library(gt)

today <- Sys.Date()
# Week 0 is in late August, so before then the calendar points at last season
current <- as.integer(format(today, "%Y")) - (format(today, "%m") < "08")

# A season's play-by-play, or NULL when it is not published: load_cfb_pbp() errors
# for a season past cfbfastR's most recent one, and warns and returns no rows for
# one whose file is not up yet
play_by_play <- function(season) {
  pbp <- tryCatch(suppressWarnings(cfbfastR::load_cfb_pbp(season)), error = function(e) NULL)
  if (NROW(pbp) == 0) NULL else pbp
}

season <- current
pbp <- play_by_play(season)
if (is.null(pbp)) {
  season <- current - 1
  pbp <- play_by_play(season)
}
stopifnot(!is.null(pbp))

# A live API call, or NULL when the API does not answer: one bad week then shows
# a note instead of failing the whole site build
live <- function(expr) tryCatch(expr, error = function(e) NULL)

# CollegeFootballData.com's schedule (a live API: set CFBD_API_KEY, a free key)
schedule <- live(cfbfastR::load_cfb_schedules(season))
schedule_ok <- NROW(schedule) > 0
if (schedule_ok) {
  played <- schedule |>
    filter(completed) |>
    arrange(start_date, game_id)
  week <- max(played$week[played$season_type == "regular"])
  left <- filter(schedule, !completed)
} else {
  week <- max(pbp$week)
}
if (!schedule_ok) {
  status <- sprintf(
    "the %d season through week %d. CollegeFootballData.com's schedule was unavailable when this page was built, so records are missing this week; they return next week.",
    season, week
  )
  through <- paste("through week", week)
} else if (any(left$season_type == "regular")) {
  status <- sprintf("the %d season through week %d.", season, week)
  through <- paste("through week", week)
} else if (nrow(left) > 0) {
  status <- sprintf("the %d regular season is final; bowls and the playoff are under way.", season)
  through <- "regular season and finished bowls"
} else {
  status <- sprintf("the offseason, so this is the final %d season, bowls and playoff included.", season)
  through <- "final"
}
```