Intro to Data Science · Analysis · Lesson 11 of 12
Correlation
Concept
Correlation
corr() measures how strongly two numeric columns move together, from -1 for opposite to 1 for the same direction.
By the end of this lesson
- Explain the core idea behind Correlation.
- 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
correlation = df["hours_studied"].corr(df["score"])
print(correlation)Self-check before continuing
Without looking at the example, describe what changes when you modify one input in Correlation. 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
Explain what a correlation close to 0 would mean between two columns.
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Console