Lab4

FG Stats by Position
Position	Count	Minimum	Average	Maximum
Forward	4	50.9	54.25	59.1
Guard	4	46.6	52.90	58.0
Center	4	40.8	50.85	59.9

code:

# Installing and loading required packages

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

library(tidyverse)
library(gtExtras)

# Installing and loading required packages

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

library(tidyverse)
library(gtExtras)

# 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)

FG_Average <- mean(FG_Percentage)

basketball_players <- basketball_players %>%
  mutate(
    FG_Category = case_when(
      FG_Percentage < FG_Average ~ "Below average",
      FG_Percentage == FG_Average ~ "Average",
      FG_Percentage > FG_Average ~ "Above average",
      .default = "Error"
    )
  )

# Making the table

Player_table <- gt(basketball_players) %>%
  tab_header("Player positions and FG stats") %>%
  cols_align(align = "left") %>%
  gt_theme_538

# Showing the table

Player_table

Summary <- basketball_players %>% 
  group_by(Position) %>% 
  summarize(Count = n(),
            Minimum = min(FG_Percentage),
            Average = (round(mean(FG_Percentage),2)),
            Maximum = max(FG_Percentage)) %>% 
  arrange(desc(Average))

# Making the table

Summary_table <- gt(Summary) %>%
  tab_header("FG Stats by Position") %>%
  cols_align(align = "left") %>%
  gt_theme_538

# Showing the table

Summary_table