Given a DataFrame with multiple numeric columns, how can you use SciPy and Pandas together to find the column with the highest mean z-score?

hard📝 Application Q9 of 15

SciPy - Integration with Scientific Ecosystem

ACalculate z-scores for each column using scipy.stats.zscore, then find the column with max mean z-score.

BUse pandas mean() directly without z-score normalization.

CApply scipy.optimize to minimize z-score values.

DUse scipy.stats.ttest_ind between columns to find highest mean.

Step-by-Step Solution

Solution:

Step 1: Calculate z-scores per column
Use scipy.stats.zscore on DataFrame to standardize each column.
Step 2: Compute mean z-score per column and find max
Use pandas mean() on z-score DataFrame columns, then identify column with highest mean.
Final Answer:
Calculate z-scores for each column using scipy.stats.zscore, then find the column with max mean z-score. -> Option A
Quick Check:
zscore + mean + max column = Calculate z-scores for each column using scipy.stats.zscore, then find the column with max mean z-score. [OK]

Quick Trick: Standardize columns first, then compare means [OK]

Common Mistakes:

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