stationarity_stock.py

def tsplot(y, lags=None, figsize=(12, 7), syle='bmh'):
    
    if not isinstance(y, pd.Series):
        y = pd.Series(y)
        
    with plt.style.context(style='bmh'):
        fig = plt.figure(figsize=figsize)
        layout = (2,2)
        ts_ax = plt.subplot2grid(layout, (0,0), colspan=2)
        acf_ax = plt.subplot2grid(layout, (1,0))
        pacf_ax = plt.subplot2grid(layout, (1,1))
        
        y.plot(ax=ts_ax)
        p_value = sm.tsa.stattools.adfuller(y)[1]
        ts_ax.set_title('Time Series Analysis Plots\n Dickey-Fuller: p={0:.5f}'.format(p_value))
        smt.graphics.plot_acf(y, lags=lags, ax=acf_ax)
        smt.graphics.plot_pacf(y, lags=lags, ax=pacf_ax)
        plt.tight_layout()
        
tsplot(data.CLOSE, lags=30)

# Take the first difference to remove to make the process stationary
data_diff = data.CLOSE - data.CLOSE.shift(1)

tsplot(data_diff[1:], lags=30)