Time Series plot

TS Visualization

auto_cor = sales.groupby("Date")["Weekly_Sales"].sum()
auto_cor = pd.DataFrame(auto_cor)
auto_cor.columns = ["y"]

# Adding the lag of the target variable from 1 steps back up to 52 (due to a seasonality at the end of the year)
for i in range(1, 53):
    auto_cor["lag_{}".format(i)] = auto_cor.y.shift(i)

# Compute autocorrelation of the series and its lags
lag_corr = auto_cor.corr()
lag_corr = lag_corr.iloc[1:,0]
lag_corr.columns = ["corr"]
order = lag_corr.abs().sort_values(ascending = False)
lag_corr = lag_corr[order.index]

# Plot the Autocorrelation
plt.figure(figsize=(12, 6))
lag_corr.plot(kind='bar')
plt.grid(True, axis='y')
plt.title("Autocorrelation")
plt.hlines(y=0, xmin=0, xmax=len(lag_corr), linestyles='dashed')