I'm trying to generate a text file merging two arrays I created, but when I try to do it a bigger array appears which is not the original one

Question

I have obtained the averaged amplitude in DB of a list of audio files and stored it into an array called D_AVG. Then I created an index array going from 0 to the number of values present in the D_AVG array. I want to join these two in order to get a text file with two vertical columns with the index and D_AVG arrays

When printing these two arrays individually, the correct values are printed, therefore correctly stored. However, when joining them and printing the joint columns, a lot of other numbers appear that are not in the original array. I don't know what is wrong, since I have done it for a single audio file and it works perfectly.

This is my current code:

import numpy as np
import matplotlib.pyplot as plt


pathAudio = 'C:\\Users\\..\\..\\..\\Audio_Project\\data\\audios'
files = librosa.util.find_files(pathAudio) 
n_fft = 2048

for y in files: 
    y , sr = librosa.load(y, sr = 44100)   
    S = librosa.stft(y, n_fft = n_fft, hop_length=n_fft//2)
    D = librosa.amplitude_to_db(np.abs(S),ref=np.max)
    D_AVG = np.mean(D, axis=1)
    index = np.array(range(1025))
    x = index
    y = D_AVG
    print(x)
    print(y)
    
    joint = np.column_stack((x,y))

When I print x and y, I get the following: correct result

But, if I print the joined array (joint variable), I get the following: incorrect

My code for a single file looks like this:

import librosa
import numpy as np
import matplotlib.pyplot as plt

file = 'C:...\\Audio_Project\\data\\audios\\recording_00.mp3'

#load the file
y , sr = librosa.load(file, sr=44100)
#short time fourier transform

#(n_fft and hop length determine frequency/time resolution)

n_fft = 2048
S = librosa.stft(y, n_fft = n_fft, hop_length=n_fft//2)

#convert to db
D = librosa.amplitude_to_db(np.abs(S),ref=np.max)

#average over file
D_AVG = np.mean(D, axis=1)

print(D_AVG)
index = np.array(range(1025))
print(index)

data = np.column_stack([index, D_AVG])
datafile_path = 'C:..\\Audio_Project\\prueba.txt'
 
np.savetxt(datafile_path, data, fmt=['%d','%d'])