Computing sliding mean to smooth curves

sliding_mean.py

import numpy as np

def sliding_mean(data_array, window=5):  
    data_array = np.array(data_array)  
    new_list = []  
    for i in range(len(data_array)):  
        indices = range(max(i - window + 1, 0),  
                        min(i + window + 1, len(data_array)))  
        avg = 0  
        for j in indices:  
            avg += data_array[j]  
        avg /= float(len(indices))  
        new_list.append(avg)  
          
    return np.array(new_list)