input: Write a python function to find anomalies in a dataset based on z-scores.
  assert findAnomaly(np.array([[1, 2], [2, 3], [10, 10]])) == [np.array([10, 10])]
  assert findAnomaly(np.array([[1, 1], [1, 1], [1, 1]])) == []
  assert findAnomaly(np.array([[5, 5], [5, 5], [100, 100]])) == [np.array([100, 100])]
output: import numpy as np
  
  def findAnomaly(data):
      z_scores = np.abs((data - np.mean(data, axis=0)) / np.std(data, axis=0))
      threshold = 3  # Common threshold for z-score anomaly detection
      anomalies = data[np.any(z_scores > threshold, axis=1)]
      return [anomaly for anomaly in anomalies]