standardize-column — Shopify case

Shopify-inspired forecasting pipeline combines numerical features collected from merchants with different units and scales. You need to standardize a feature using its mean and standard deviation so the training pipeline receives a consistent representation.

Standardise one feature: subtract its mean and divide by its population standard deviation. A constant feature is mapped to zeros.

Implement solve(x).

Returns. Return a float NumPy vector with mean $00$ and standard deviation $11$ (or all zeros for a constant input).

Examples

Example 1

Input:

solve([1, 2, 3])

Output:

[-1.224745, 0.0, 1.224745]

Example 2

Input:

solve([4.0, 4.0, 4.0])

Output:

[0.0, 0.0, 0.0]