Activity#3

plot(cars)

install.packages("tidyverse")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.3'
## (as 'lib' is unspecified)

#Load the mtcars dataset (built into R)
data_mtcars <- mtcars

#View the first few rows to understand the data
head(data_mtcars)

#Convert 'am' (transmission type) and 'cyl' (number of cylinders) to factors for categorical plotting
data_mtcars$am <- as.factor(data_mtcars$am)
data_mtcars$cyl <- as.factor(data_mtcars$cyl)

head(data_mtcars)

library(ggplot2)
#Create a scatter plot of car weight vs. miles per gallon, colored by cylinder count
ggplot(data_mtcars, aes(x = wt, y = mpg, color = cyl)) +
  geom_point() + #Add points to the plot
  labs(title = "Miles Per Gallon vs Weight", x = "Weight (1000 lbs)", y = "Miles Per Gallon") # Add plot labels

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(ggplot2)

#Create a line graph of ordered mpg by the row number
data_mtcars_line <- data_mtcars %>% mutate(index = row_number())

ggplot(data_mtcars_line, aes(x = index, y = mpg)) +
  geom_line() +
  labs(
    title = "Miles Per Gallon by Index",
    x = "Index",
    y = "Miles Per Gallon"
  )

#Create a horizontal bar chart of the average horsepower grouped by cylinder count
hp_by_cyl <- data_mtcars %>% group_by(cyl) %>% summarize(avg_hp = mean(hp)) # Calculate average horsepower for each cylinder group

ggplot(hp_by_cyl, aes(y = cyl, x = avg_hp)) +
  geom_bar(stat = 'identity') + # Create bars based on the calculated averages
  labs(title = "Average HP by Cylinder Count", y = "Cylinder Count", x = "Average Horsepower") # Add plot labels

library(dplyr)
library(tidyr)
library(ggplot2)

# Create a stacked bar chart of average mpg, disp, hp, and wt grouped by cyl
bar_data_mtcars <- data_mtcars %>%
  group_by(cyl) %>%
  summarize(
    mpg = mean(mpg),
    disp = mean(disp),
    hp = mean(hp),
    wt = mean(wt)
  ) %>%
  pivot_longer(
    cols = c(mpg, disp, hp, wt),
    names_to = "Measurement",
    values_to = "Average"
  )

ggplot(bar_data_mtcars, aes(x = factor(cyl), fill = Measurement, y = Average)) +
  geom_bar(stat = "identity") +
  labs(
    title = "Average Measurements by Cylinder Count",
    x = "Cylinder Count",
    y = "Average Measurement"
  )

```