Стандартное отклонение в каждой строке

import numpy as np
 
k = 1
while k == 1:
    rows = int(input("Input humber rows: "))
    cols = int(input("Input number cols: "))
    rand_min = int(input("Max number: "))
    rand_max = int(input("Min number: "))
 
    print("")
 
    print("Matrix:")
    matrix_f = []
    for i in range(rows):
        row = []
        for j in range(cols):
            rn = rand_min + (rand_max - rand_min) * np.random.rand()
            row.append(rn)
        matrix_f.append(row)
 
    text = ''
    for i in range(cols):
        for j in range(rows):
            text += ('{:.2f}'.format(matrix_f[j][i])) + " "
        text += "\n"
    print(text)
 
    print("Matrix transposition:")
    text = ''
    for j in range(rows):
        for i in range(cols):
            text += ('{:.2f}'.format(matrix_f[j][i])) + " "
        text += "\n"
    print(text)
 
    print("Exercise 1") #Стандартное отклонение
    print("Standard deviation in every line")
    text = ''
    for i in range(cols):
        for j in range(rows):
            text += ('{:.2f}'.format(matrix_f[j][i])) + " "
            x = np.std(matrix_f, axis=1)
        text += "- Std " + (str(x))
        text += "\n"
    print(text)
 
    print("Exercise 2")
    print("Min element")
 
    k = 101
    text = ''
    for i in range(cols):
        for j in range(rows):
            if i > j:
                if float(matrix_f[j][i]) < k:
                    k = float(matrix_f[j][i])
 
    text = ('{:.2f}'.format(k))
    print(text)
 
    k = int(input("\nTo continue 1\nExit - 0\n"))