Modify and import as numpy.ndarray a txt file in python To import the data contained into the file my_file.txt that have the form:

Label[0] = 0.980252
Label[1] = -nan
Label[2] = -nan
Label[3] = -nan
Label[4] = 0.664706
Label[5] = -nan
Label[6] = -nan
Label[7] = -nan
Label[8] = -nan
Label[9] = -nan
Label[10] = -nan
Label[11] = 0.800183
Label[12] = -nan
Label[13] = -nan
Label[14] = -nan
Label[15] = 0
Mean Data = 15


I wrote the following code:

import numpy as np

with open('myfile.txt', 'r') as file_txt_original:
    data = file_txt_original.read()

    data = data.replace('Mean data', '-1')
    data = data.replace('Label[', '')
    data = data.replace(']', '')
    data = data.replace(' = ', ', ')

    file_txt_original.close()

with open('new_file.txt', 'w') as file_txt_copy:

    file_txt_copy.write(data)
    file_txt_copy.close()

my_array = np.loadtxt('new_file.txt', delimiter=',')


It works but this to me seems still quite an tricky solution... Any suggestion to improve this code without doing so many replacement or without saving an additional structure?
You can concatenate the replace strings after you open the file, it will give better visibility

data = file_txt_original.read()
.replace('Mean data', '-1')
.replace('Label[', '')
.replace(']', '')
.replace(' = ', ', ')