Intro to Data Science · Visualization · Lesson 7 of 12
Scatter Plots for Relationships
Concept
Scatter Plots for Relationships
Scatter plots reveal whether two numeric variables are related, and how strongly.
By the end of this lesson
- Explain the core idea behind Scatter Plots for Relationships.
- Predict output before running a change.
- Test one realistic and one unusual input.
- Use the result to make the next decision.
How to study this page
- 1. Read one concept.
- 2. Change the example.
- 3. Run, compare, and explain.
- 4. Complete the challenge below.
ExampleRunnable
plt.scatter(df["hours_studied"], df["score"])
plt.xlabel("Hours studied")
plt.ylabel("Score")Self-check before continuing
Without looking at the example, describe what changes when you modify one input in Scatter Plots for Relationships. Then reopen the editor and prove your explanation with a small test.
You are ready to continue when you can predict, test, and explain the result.
Your turn
Describe what an upward-sloping scatter plot would suggest about the two variables.
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