application_vnd.jupyter.stderr_output_1.png
from statsmodels.graphics.tsaplots import plot_acf

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

df = pd.read_csv('/kaggle/input/demand-forecast-abal2/demand_forecast.csv', parse_dates=['date'])
df

def plot_autocorrelation(store_num, item_num, lag=50):
    filtered_df = df[(df['store'] == store_num) & (df['item'] == item_num)]

for store_num in range(1, 3):
    for item_num in range(12, 17):
        plot_autocorrelation(store_num, item_num, 21)