Time Series Analysis, Data Science, Python, Weather, Statistics.
distribution') ax2 = fig.add_subplot(212) prob = stats.probplot(df_d.t2m_box, dist=stats.norm, plot=ax2) ax2.set_title('Probplot after Box-Cox transformation') plt.tight_layout() Image by author. If you are going to use the transformed time series for ML modeling, don’t forget to apply reverse