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_
