An NBA dataset contains records about players, teams, games, seasons, drafts, or performance statistics. These datasets turn basketball questions into practical exercises in data wrangling, visualization, and statistical analysis. section 1.0 section 2.7
Common analytical uses include:
- Importing and exploring first-round draft-pick records from the 2000–2009 amateur drafts. section 2.2
- Cleaning box-score records by removing official names, deduplicating games, checking score integrity, and selecting relevant variables. section 9.3
- Joining team statistics by team and season to compare wins, scoring, point differential, and playoff outcomes. section 14.2.5
- Standardizing scoring-leader statistics to account for rule changes, playing styles, and other changes across eras. section 19.0
Importing a draft dataset
Read a CSV into R with `draft <- read_csv("draft.csv")`, then check its dimensions with `dim(draft)`. The illustrated dataset contains 293 rows and 26 columns before further wrangling. section 2.2
draft <- read_csv("draft.csv")
Use the executable import example to begin working with an NBA dataset in R. section 2.2
