plt.ylabel("Probability of person's death") #Cumulative density with confidence interval: kmf.confidence_interval_cumulative_density_ #Plot cumulative density with confidence interval: confidence_cumulative_density = kmf.confidence_interval_cumulative_density_ plt.plot(kmf.confidence_interval_cumulative_density_["KM_estimate_lower_0.95"],label="Lower") plt.plot(kmf.confidence_interval_cumulative_density_["KM_estimate_upper_0.95"],label="Upper") plt.title("Cumulative Density With Confidence Interval") plt.xlabel("Number of days") plt.ylabel("Cumulative Density") plt.legend() #Find cumulative density at a specific time: kmf.cumulative_density_at_times(times=1022) #Conditional median time to event of interest: kmf.conditional_time_to_event_ #Conditional median time left for event: median_time_to_event = kmf.conditional_time_to_event_ plt.plot(median_time_to_event,label="Median Time left") plt.title("Medain time to event") plt.xlabel("Total days") plt.ylabel("Conditional median time to event") plt.legend() #Hazard function: from lifelines import NelsonAalenFitter
km.confidence_interval_cumulative_density_ #plot cumulative density with confidence interval conf_cum_density = km.confidence_interval_cumulative_density_ plt.plot(km.confidence_interval_cumulative_density_["KM_estimate_lower_0.95"], label="Lower") plt.plot(km.confidence_interval_cumulative_density_["KM_estimate_upper_0.95"], label="Upper") plt.title("Cumulative Density With Confidence Interval") plt.xlabel("Number of days") plt.ylabel("Cumulative Density") plt.legend() plt.show() #cumulative density at a specific time: print(km.cumulative_density_at_times(times=1022)) #Conditional median time to event of interest print(km.conditional_time_to_event_) #Hazard function: from lifelines import NelsonAalenFitter #Create an object of NelsonAalenFitter: naf = NelsonAalenFitter() #Fit our data into the object: naf.fit(data["time"], event_observed=data["dead"]) #Print the cumulative hazard: naf.cumulative_hazard_