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Visualizing a sugar content dataset

In this exercise, you will create a 1-dimensional scatter plot of 25 soft drink sugar content measurements. The aim is to visualize distinct clusters in the dataset as a first step towards identifying candidate decision boundaries.

The dataset with 25 sugar content measurements is stored in the sugar_content column of the data frame df, which has been preloaded for you.

This exercise is part of the course

Support Vector Machines in R

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Exercise instructions

  • Load the ggplot2 package.
  • List the variables in dataframe df.
  • Complete the scatter plot code. Using the df dataset, plot the sugar content of samples along the x-axis (at y equal to zero).
  • Write ggplot() code to display sugar content in df as a scatter plot. Can you spot two distinct clusters corresponding to high and low sugar content samples?

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Load ggplot2
___

# Print variable names
___

# Plot sugar content along the x-axis
plot_df <- ggplot(data = __, aes(x = ___, y = ___)) + 
    geom_point() + 
    geom_text(aes(label = sugar_content), size = 2.5, vjust = 2, hjust = 0.5)

# Display plot
plot_df
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