input: Write a function to perform PCA transformation using sklearn.
  assert pca_transformation([[1, 2], [3, 4], [5, 6]]).shape == (3, 2)
  assert pca_transformation([[1, 0], [0, 1], [1, 1]]).shape == (3, 2)
  assert pca_transformation([[1, 1, 1], [2, 2, 2], [3, 3, 3]]).shape == (3, 1)
output: def pca_transformation(data):
      from sklearn.decomposition import PCA
      import numpy as np
      
      data = np.array(data)
      pca = PCA(n_components=min(data.shape[0], data.shape[1]))
      transformed_data = pca.fit_transform(data)
      
      return transformed_data