R Notebook

plot(cars)

# The R-Programming plots faster and less complicated than python. 

install.packages("tidyverse")

trying URL 'http://rspm/default/__linux__/noble/latest/src/contrib/tidyverse_2.0.0.tar.gz'
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The downloaded source packages are in
    ‘/tmp/RtmpKyGgKR/downloaded_packages’

library(tidyverse)

# 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)

# The datatype double was changed and updated by the pull head command.

# 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 = "Weight vs. Miles Per Gallon", x = "Weight (1000 lbs)", y = "Miles Per Gallon") # Add plot labels

#The current scatterplot x AXIx is currently by weight which should be altered. 

# 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

# We should edit miles per gallon vs Cylinder instead of weight. Cylinder on the x axis. and H ave the Weight of the vehicle as the colors. 

#Create a line graph of ordered mpg by the row number.
data_mtcars_line <- data_mtcars %>% mutate(index = row_number()) #add index column so we can plot it

ggplot(data_mtcars_line, aes(x = index, y = mpg)) +
  geom_line() + # add a line to the plot
  labs(title = "Miles Per Gallon by Index", x = "Index", y = "Miles Per Gallon") # add plot labels

# 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

# The Cylinder vs the horsepower shows exact data

```{r}

Error: attempt to use zero-length variable name

# Here we have a better chart graph the cylinder is on the x axis creating better data and measurement is on the y asis.