Created
April 2, 2024 16:37
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Clase 17 : Series de tiempo (EPC)
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# Gráfico de correlograma | |
def plot_correlogram(x, lags=None, title=None): | |
lags = min(10, int(len(x)/5)) if lags is None else lags | |
fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(14, 8)) | |
x.plot(ax=axes[0][0], title='Time Series') | |
x.rolling(21).mean().plot(ax=axes[0][0], c='k', lw=1) | |
q_p = np.max(q_stat(acf(x, nlags=lags), len(x))[1]) | |
stats = f'Q-Stat: {np.max(q_p):>8.2f}\nADF: {adfuller(x)[1]:>11.2f}' | |
axes[0][0].text(x=.02, y=.85, s=stats, transform=axes[0][0].transAxes) | |
probplot(x, plot=axes[0][1]) | |
mean, var, skew, kurtosis = moment(x, moment=[1, 2, 3, 4]) | |
s = f'Mean: {mean:>12.2f}\nSD: {np.sqrt(var):>16.2f}\nSkew: {skew:12.2f}\nKurtosis:{kurtosis:9.2f}' | |
axes[0][1].text(x=.02, y=.75, s=s, transform=axes[0][1].transAxes) | |
plot_acf(x=x, lags=lags, zero=False, ax=axes[1][0]) | |
plot_pacf(x, lags=lags, zero=False, ax=axes[1][1]) | |
axes[1][0].set_xlabel('Lag') | |
axes[1][1].set_xlabel('Lag') | |
fig.suptitle(title, fontsize=14) | |
sns.despine() | |
fig.tight_layout() | |
fig.subplots_adjust(top=.9) | |
# Unit Root Test | |
def test_unit_root(df): | |
return df.apply(lambda x: f'{pd.Series(adfuller(x)).iloc[1]:.2%}').to_frame('p-value') | |
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