Basically, numpy arrays don't have have access to append(). If we look into documentation, we need to use np.append(array), where array is the values to be appended.

import numpy as np

arr = np.array([1,2,3,47,1,0,2])

np.append(arr, 4)

Other answers explain that numpy arrays do not have an .append() method and point to numpy.append. Using numpy.append, however, is bad practice because it creates a new array each time. A better solution is to create one numpy and fill it during the for loop (see end of answer).

An even better solution would make use of numpy's broadcasting. That's a core feature of numpy, and it's what helps make numpy fast.

import numpy as np

with open('expFcn0.txt') as f:
    lines = f.readlines()
    x = np.array([float(line.split()[0]) for line in lines])
    y = np.array([float(line.split()[1]) for line in lines])

M = np.log(y) / x

You can also look into numpy.loadtxt to read the file into a numpy array directly.

How to fill a numpy array in a for loop:

import numpy as np

with open('expFcn0.txt') as f:
    lines = f.readlines()
    x = [float(line.split()[0]) for line in lines]
    y = [float(line.split()[1]) for line in lines]

M = np.zeros(181)
for i in range(181):
    a = np.log(y[i])/x[i]
    print(a)
    M[i] = a

vstack is a numpy function which takes only a single argument in the form of a tuple . You need to call it and assign the output to your variable. So instead of
g.vstack((temp_g,g))
use
g=np.vstack((temp_g,g))