Dataset: Medical Cost Personal Datasets

About this Dataset

Medical Cost Personal Datasets

Context

Machine Learning with R by Brett Lantz is a book that provides an introduction to machine learning using R. As far as I can tell, Packt Publishing does not make its datasets available online unless you buy the book and create a user account which can be a problem if you are checking the book out from the library or borrowing the book from a friend. All of these datasets are in the public domain but simply needed some cleaning up and recoding to match the format in the book.

Content

Columns

age: age of primary beneficiary
sex: insurance contractor gender, female, male
bmi: Body mass index, providing an understanding of body, weights that are relatively high or low relative to height,
objective index of body weight (kg / m ^ 2) using the ratio of height to weight, ideally 18.5 to 24.9
children: Number of children covered by health insurance / Number of dependents
smoker: Smoking
region: the beneficiary's residential area in the US, northeast, southeast, southwest, northwest.
charges: Individual medical costs billed by health insurance

Acknowledgements

The dataset is available on GitHub here.

Inspiration

Can you accurately predict insurance costs?

Tables

Insurance

@kaggle.mirichoi0218_insurance.insurance

23.8 KB
1338 rows
7 columns


CREATE TABLE insurance (
  "age" BIGINT,
  "sex" VARCHAR,
  "bmi" DOUBLE,
  "children" BIGINT,
  "smoker" VARCHAR,
  "region" VARCHAR,
  "charges" DOUBLE
);