Lab 4

Basketball Team Data

Player Stats by Position
Position	Count	Minimum	Average	Maximum
Forward	4	50.9	54.2	59.1
Guard	4	46.6	52.9	58.0
Center	4	40.8	50.8	59.9

Code:

# ----------------------------------------------------------
# Installing required packages
# ----------------------------------------------------------

if (!require("tidyverse"))
  install.packages("tidyverse")
if (!require("gt"))
  install.packages("gt")

library(tidyverse)
library(gt)

# ----------------------------------------------------------
# Specify made-up data for 12 players
# and turn it into a data frame
# Note: I used ChatGPT to help generate this data
# ----------------------------------------------------------

Player <- c(
  "Player 1",
  "Player 2",
  "Player 3",
  "Player 4",
  "Player 5",
  "Player 6",
  "Player 7",
  "Player 8",
  "Player 9",
  "Player 10",
  "Player 11",
  "Player 12"
)

Position <- c(
  "Guard",
  "Center",
  "Center",
  "Guard",
  "Forward",
  "Center",
  "Forward",
  "Guard",
  "Center",
  "Forward",
  "Guard",
  "Forward"
)

FG_Percentage <- c(58.0,
                   44.9,
                   40.8,
                   46.6,
                   59.1,
                   57.8,
                   53.9,
                   52.8,
                   59.9,
                   53.1,
                   54.2,
                   50.9)

basketball_players <- data.frame(Player, Position, FG_Percentage)

# ----------------------------------------------------------
# Displaying the table
# ----------------------------------------------------------

basketball_players_table <- gt(basketball_players) %>%
  tab_header(title = "Player stats by position") %>%
  cols_align(align = "left")

basketball_players_table

# ----------------------------------------------------------
# Display table summarizing field goal stats by position 
# ----------------------------------------------------------

Summary_FG_Percentage <- basketball_players %>% 
  group_by(Position) %>% 
  summarise(Count=n(),
            Minimum = min(FG_Percentage),
            Average = round(mean(FG_Percentage),1), 
            Maximum = max(FG_Percentage)) %>% 
  arrange(desc(Average))

# ----------------------------------------------------------
# Redisplaying table summarizing field goal stats by position 
# ----------------------------------------------------------

Summary_FG_Percentage_Table <- gt(Summary_FG_Percentage) %>% 
  tab_header(title = "Player Stats by Position") %>% 
  cols_align(align = "left")

Summary_FG_Percentage_Table