Description Usage Arguments Value Examples
This function generates creates a ranking of a variable 'column' summarizing by a variable 'by' using a function 'FUN'. The result of this function is a visualization with that information.
For reference on the scraped data columns information, please refer to the dataset description: https://github.com/UBC-MDS/rsketball/blob/master/dataset_description.md
For detailed use cases, please refer to the vignette: https://ubc-mds.github.io/rsketball/articles/rsketball-vignette.html
1 | nba_ranking(nba_data, column, by, top = 5, descending = TRUE, FUN = mean)
|
nba_data |
The tibble dataframe from the scraped nba data |
column |
The categorical column from the dataset to rank. Should be either "NAME", "TEAM" or "POS" |
by |
The column from the dataset to rank by. Should be the statistic numerical column of interest. If the column starts with a number (eg 3PA) or has a % character (eg FT%), format it with backticks "'". Refer to vignette for more examples on this. |
top |
The number of elements in the ranking. Defaults to 5. |
descending |
Boolean variable for the order of the ranking. TRUE if descending, FALSE otherwise. Defaults to True. |
FUN |
function to apply to the values. Defaults to the Mean function. |
ggplot visualization with the ranking
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | nba_data <- tibble::tibble(NAME = c("James", "Steph", "Bosh", "Klay", "Kobe"),
TEAM = c("MIA","GS","MIA","GS","LAL"),
POS = c("SF", "PG", "C", "SG", "SG"),
PTS = c(5,4,3,2,10),
TO = c(1,2,3,4,3))
# Find top 3 players for points (PTS) where higher is better
nba_ranking(nba_data,
column = NAME,
by = PTS,
top = 3,
descending = TRUE,
FUN = mean)
#' # Find top 2 teams for turnover (TO) where lower is better
nba_ranking(nba_data,
column = TEAM,
by = TO,
top = 2,
descending = FALSE,
FUN = mean)
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