1. Question 1

Elina wants summary statistics (count, mean, std). What should she use?

• ❌ head()

• ❌ tail()

• ✅ describe()

• ❌ summary()

Explanation:

df.describe() gives summary statistics for numerical columns.

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2. Question 2

Pearson correlation close to zero means:

• ❌ Mean of data near zero

• ❌ Uncertainty between variables

• ❌ Minimal deviation

• ✅ Two variables are not correlated

Explanation:

Correlation ≈ 0 → no linear relationship.

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3. Question 3

Reshape data so one variable becomes rows and another becomes columns:

• ❌ merge()

• ❌ groupby()

• ✅ pivot()

• ❌ pcolor()

Explanation:

pivot() reshapes long data → wide format with rows vs columns.

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4. Question 4

Result of:

• ❌ Averages body-style variable

• ❌ Writes mean value of each body-style price to the dataframe (wording unclear)

• ❌ Averages price for all body labels

• ✅ It averages the price for each body style.

Explanation:

Groupby + mean computes mean price for each body-style category.

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5. Question 5

No clear trend between peak RPM and price means:

• ✅ Weak or no correlation

• ❌ Strong negative

• ❌ Uncertain

• ❌ Strong positive

Explanation:

Scattered values without trend → very low correlation.

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🧾 Summary Table

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