Why Use Bar Plots?

Bar plots are one of the most common ways to visualize categorical data. They help us quickly:

• Compare counts or frequencies of categories;

• Visualize group-wise summaries (like average price per fuel type);

• Understand relationships between two categorical variables using grouped or stacked bars.

Whether you're showing the number of cars by fuel type or comparing transmission modes across fuels, bar plots make categorical comparisons clear and intuitive.

Bar Plot Syntax in ggplot2

ggplot(data = df, aes(x = category)) +
  geom_bar()

• If only x is provided, geom_bar() automatically counts the number of observations;

• If y is also provided, you need to add stat = "identity" to use actual values.

Example: Count of Cars by Fuel Type

ggplot(df, aes(x = fuel)) + 
  geom_bar(fill = "lightblue", color = "red") +
  labs(title = "Car Distribution by Fuel Type", x = "Fuel Type", y = "Count") +
  theme_minimal()

This plot shows the number of cars available for each type of fuel.