A Complete Guide To Survival Analysis In Python, part 2 - KDnuggets

In the first article of this three-part series, we saw the basics of the Kaplan-Meier Estimator. Now, it's time to implement the theory we discussed in the first part. It gives us information about the data types and the number of rows in each column that has null values. It's very important for us to remove the rows with a null value for some of the methods in survival analysis. It gives us some statistical information like the total number of rows, mean, standard deviation, minimum value, 25th percentile, 50th percentile, 75th percentile, and maximum value for each column in our dataset.