AI & MACHINE LEARNING PROGRAM • LEVEL 05 — DATA PREPARATION
Apply Standard Scaling with Python
Learn apply standard scaling with python with a short, executable Python example.
PROBLEM UNDERSTANDING
Input and expected output
No input required
[-1.225, 0.0, 1.225]
COMPLETE PYTHON PROGRAM
Complete Python implementation
values = [10, 20, 30] mean = sum(values) / len(values) std = (sum((x - mean) ** 2 for x in values) / len(values)) ** 0.5 print([round((x - mean) / std, 3) for x in values])
CURRENT STEP
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SELECTED LINE
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EXPECTED OUTPUT FOR THE SAMPLE
[-1.225, 0.0, 1.225]
PROGRAM EXPLANATION
Algorithm and explanation
- Initialize the sample values used to apply standard scaling.
- Process the data step by step using StandardScaler and Z-score.
- Display the result for apply standard scaling and compare it with the documented sample output.
This example of apply standard scaling processes the sample values in a controlled iteration. It demonstrates StandardScaler and Z-score and prints a deterministic result that can be checked against the sample output.
EFFICIENCY
Time and space complexity
O(n)
O(n)
DEBUGGING CHECKLIST
Common mistakes
For apply standard scaling, keep the data shape and value types consistent with StandardScaler.
Keep every dependent statement inside the correct indented Python block.
Check denominators, numeric ranges and rounding before comparing the calculated value.