all_data = pd.read_csv('data2.csv')
mu = np.array([all_data.mean(0)])
sigma = np.array([np.std(all_data,axis=0)])
print(all_data.shape)
print(mu.shape)
print(sigma.shape)

(all_data.values - mu)/sigma

pd.DataFrame((all_data.values - mu)/sigma, columns=all_data.columns, index=all_data.index)

all_data = pd.DataFrame(np.random.randint(0,9,(5,5)))
>>> all_data
   0  1  2  3  4
0  5  7  1  8  6
1  5  8  0  3  0
2  8  2  0  1  6
3  5  8  7  7  0
4  4  6  0  2  5

mu = np.array([all_data.mean(0)])
sigma = np.array([np.std(all_data,axis=0)])

>>> mu
array([[5.6, 2. , 4. , 4.4, 7.6]])
>>> sigma
array([[1.62480768, 1.26491106, 3.40587727, 2.41660919, 0.48989795]])

>>> pd.DataFrame((all_data.values - mu)/sigma, columns=all_data.columns, index=all_data.index)
          0         1        2         3          4
0 -0.369274  3.952847 -0.88083  1.489691  -3.265986
1 -0.369274  4.743416 -1.17444 -0.579324 -15.513435
2  1.477098  0.000000 -1.17444 -1.406930  -3.265986
3 -0.369274  4.743416  0.88083  1.075888 -15.513435
4 -0.984732  3.162278 -1.17444 -0.993127  -5.307228