Input array containing numerical values.
result: Returns an array of Z-score normalized values. Each value is computed as: (value - mean) / standard deviation.
Notes: - If the standard deviation is zero (i.e., all values are the same), the function could return NaN due to division by zero. To prevent this, a small epsilon (e.g., 1e-6) should be added to the denominator. - Be mindful of floating-point precision issues when dealing with very large or very small values. - In practical settings (e.g., finance, trading models), using rolling mean and standard deviation might be preferable instead of computing them on the entire dataset.
Summary: Computes the Z-score normalization of an input array. Each element is transformed to represent how many standard deviations it is from the mean. This helps standardize data with different magnitudes or units.