Business Problem: We all know that Health care is very important domain in the market. It is directly linked with the life of the individual; hence we have to be always be proactive in this particular domain. Money plays a major role in this domain, because sometime treatment becomes super costly and if any individual is not covered under the insurance then it will become a pretty tough financial situation for that individual. The companies in the medical insurance also want to reduce their risk by optimizing the insurance cost, because we all know a healthy body is in the hand of the individual only. If individual eat healthy and do proper exercise the chance of getting ill is drastically reduced. Goal & Objective: The objective of this exercise is to build a model, using data that provide the optimum insurance cost for an individual. You have to use the health and habit related parameters for the estimated cost of insurance File: Data.csv Target variable: insurance_cost

below are the questions

Univariate analysis (distribution and spread for every continuous attribute, distribution of data in categories for categorical ones)
b) Bivariate analysis (relationship between different variables , correlations)
a) Removal of unwanted variables(if applicable)
b) Missing Value treatment(if applicable)
d) Outlier treatment(if required)
e) Variable transformation (if applicable)
f) Addition of new variables(if required)
4) Business insights from EDA	4
a) Is the data unbalanced? If so, what can be done? Please explain in the context of the business
b) Any business insights using clustering (if applicable)
c) Any other business insights