Another Bayesian_Model which needs edited

bayesian_model3.py

df_hpd = pd.DataFrame(atts.stats()['95% HPD interval'], 
                      columns=['hpd_low', 'hpd_high'], 
                      index=teams.team.values)
df_median = pd.DataFrame(atts.stats()['quantiles'][50], 
                         columns=['hpd_median'], 
                         index=teams.team.values)
df_hpd = df_hpd.join(df_median)
df_hpd['relative_lower'] = df_hpd.hpd_median - df_hpd.hpd_low
df_hpd['relative_upper'] = df_hpd.hpd_high - df_hpd.hpd_median
df_hpd = df_hpd.sort_index(by='hpd_median')
df_hpd = df_hpd.reset_index()
df_hpd['x'] = df_hpd.index + .5


fig, axs = plt.subplots(figsize=(10,4))
axs.errorbar(df_hpd.x, df_hpd.hpd_median, 
             yerr=(df_hpd[['relative_lower', 'relative_upper']].values).T, 
             fmt='o')
axs.set_title('HPD of Attack Strength, by Team')
axs.set_xlabel('Team')
axs.set_ylabel('Posterior Attack Strength')
_= axs.set_xticks(df_hpd.index + .5)
_= axs.set_xticklabels(df_hpd['index'].values, rotation=45)