A simple advertising adstock transformation in Python

# Written By  : Sarbadal Pal
# Narrative   : A simple advertising adstock transformation.
# Credit: http://stackoverflow.com/questions/14372880/simple-examples-of-filter-function-recursive-option-specifically

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# Define Adstock Rate
adstock_rate = 0.50

# Create Data
advertising = [117.913, 120.112, 125.828, 115.354, 177.090, 141.647, 137.892, 0.000, 0.000, 0.000, 0.000, 
               0.000, 0.000,   0.000,   0.000,   0.000,   0.000, 158.511, 109.385, 91.084, 79.253, 102.706, 
               78.494, 135.114, 114.549, 87.337, 107.829, 125.020, 82.956, 60.813, 83.149, 0.000, 0.000, 
               0.000, 0.000, 0.000, 0.000, 129.515, 105.486, 111.494, 107.099, 0.000, 0.000, 0.000, 
               0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000]

def adstocked_advertising(adstock_rate=0.5, advertising=advertising):
    
    adstocked_advertising = []
    for i in range(len(advertising)):
        if i == 0: 
            adstocked_advertising.append(advertising[i])
        else:
            adstocked_advertising.append(advertising[i] + adstock_rate * adstocked_advertising[i-1])            
    return adstocked_advertising
            
adstocked_advertising = adstocked_advertising(adstock_rate=0.5, advertising=advertising)

fig, ax = plt.subplots(figsize=(10,5), dpi=100)
plt.subplots_adjust(left=0.2, bottom=None, right=None, top=None, wspace=None, hspace=None)
ax.spines['left'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)

ax.yaxis.grid(b=False, which='major', color='gray', linestyle='--')

ax.set_ylim([0, 1.3*max(adstocked_advertising)])

bar = ax.bar(np.arange(len(advertising)), advertising, width=0.8, color='gray', alpha=0.7, label='Actual Ad')
line = ax.plot(np.arange(len(advertising)), adstocked_advertising, 
               marker='o', markersize=3, linestyle='-', linewidth=2, color='blue', alpha=0.7, label='Ad Stock')

ax.set_xlabel('Time')
ax.set_ylabel('Adstock & Advertising')
#ax.set_title('advertising adstock transformation')

ax.annotate("Advertising Adstock Transformation", (np.mean(np.arange(len(advertising))), 315),
            verticalalignment='bottom', horizontalalignment='center',
            fontsize=15, color='#681963')
ax.set_xticks(np.arange(len(advertising)))
ax.set_xticklabels(labels=np.arange(len(advertising)), minor=False, fontsize=7, rotation=90)
ax.legend(loc='center right')  
plt.show()