Program_04

Develop a script in R to produce a bar graph displaying the frequency distribution of categorical data in a given dataset, grouped by a specific variable, using ggplot2.

library(ggplot2)

Step 1: Load the Datatset.

We use the built-in mtcars dataset, which contains information about different car models.

data <- mtcars
head(data)

                   mpg cyl disp  hp drat    wt  qsec vs am gear carb
Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

Explanation

• The mtcars dataset includes various car specifications.

• We will analyze the number of cylinders (cyl) and group by the number of gears (gear).

Step 2: Convert Numeric Data to Categorical

Since cyl (no.of cyclinders) and gear (no.of gears) are numerical, we convert theminto factors

data$cyl <- as.factor(data$cyl)
data$gear <-as.factor(data$gear)

Why Convert to factors?

ggplot2 traets factors as categories, making it easy to group and visualize.

Step 3: Create a Bar Graph

We now create a bar plot to show the frequency distribution of cyl, grouped by gear.

ggplot(data, aes(x=cyl,fill=gear)) +
  geom_bar(position = "dodge") +
  labs(title = "Frequenncy of Cyclinders Grouped by Gear Type",
       x = "number of cyclinder",
       y = "count",
       fill = "Gears") + 
  theme_minimal()