kingdomscores

Welcome to our analysis of exam grades! In this thread, we’ll explore how visual elements like color and font can enhance understanding.

hey = read.csv('https://raw.githubusercontent.com/Kingtilon1/anexamp/main/Copy%20of%20KHC%20EXAM%20GRADES%20TRACKER%20-%20Sheet1%20(2).csv')

hey$EXAM.GRADE[is.na(hey$EXAM.GRADE) | hey$EXAM.GRADE == ""] <- 0
hey$EXAM.1.POINTS[is.na(hey$EXAM.1.POINTS) | hey$EXAM.1.POINTS == ""] <- 0

hey$EXAM.GRADE <- as.numeric(sub("%", "", hey$EXAM.GRADE))

Here’s a bar plot showing exam grades of students. Each bar represents a student’s exam score, color-coded by grade.

plot <- ggplot(hey, aes(x = NAMES, y = EXAM.GRADE, fill = EXAM.GRADE)) +
  geom_bar(stat = "identity") +
  labs(title = "Exam Grades",
       x = "Student Names",
       y = "Exam Points",
       fill = "Grade") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) 

print(plot)

Notice how different grades are represented by distinct colors. This color scheme makes it easy to identify the distribution of grades at a glance.

In addition to colors, font emphasis can also draw attention. We’ve used bold font for the title and axis labels, ensuring they stand out.