Coding Challenge: Kaplan-Meier Survival Analysis

Problem Statement:

Your task is to perform Kaplan-Meier survival analysis on a dataset containing cancer patient information. The dataset includes details such as patient demographics, dates of diagnosis, treatment received, and outcomes.

Challenge:

-Load the dataset from a CSV file or any suitable data format. -Preprocess the data as necessary. -Perform Kaplan-Meier survival analysis to estimate the survival function for the dataset. -Calculate the survival probabilities over time using the Kaplan-Meier estimator. -Plot the result including the censored subjects.

Bonus Task:

-Conduct subgroup analyses by stratifying the data based on most relevant attributes and calculate survival probabilities for each subgroup. Justify your approach.

Dataset Information:

-Patient ID: Unique identifier for each patient, presented in a fancier format. -Date of Birth: The date of birth of each patient. -Age: The age of each patient at the time of diagnosis. -Gender: The gender of each patient. -Date of Diagnosis: The date when each patient was diagnosed with the medical condition. -Date of Death: The date of death of each patient, if applicable. -Date of Last Follow-Up: The date of the last follow-up for each patient. -Date of Admission: The date of admission to the hospital, if applicable. -Date of Discharge: The date of discharge from the hospital, if applicable. -Disease Stage: The stage of the disease diagnosed in each patient. -Treatment Received: The type of treatment received by each patient. -Comorbidities: Any additional medical conditions present in each patient. -Smoking Status: The smoking status of each patient. -Family History: Any family history of the medical condition in each patient. -Vital Signs: The vital signs (e.g., blood pressure) recorded for each patient.