Name: Decoding Medical Costs: Analyzing Insurance Data
Creator: Kaggle
License: https://opendatacommons.org/licenses/pddl/1.0/

About this Dataset

Decoding Medical Costs: Analyzing Insurance Data

Context:

This dataset contains 1,338 rows and 7 columns about health insurance details.
It includes demographic features like age, gender, area, and smoker status, along with health factors such as BMI and number of children.
The target variable is charges, representing the medical insurance cost for each individual.
This dataset is often used to analise how lifestyle, health, and personal characteristics influence insurance expenses.

Feature Distribution:

age → Ranges from 18 to 64 years, showing the age of the insured person.

sex → Two categories: male and female.

bmi → Body Mass Index, ranges from about 15 to 53, indicating health/weight status.

children → Number of dependents covered by the insurance, from 0 to 5.

smoker → Two categories: yes (smoker) and no (non-smoker).

region→ Four categories: northeast, northwest, southeast, southwest.

charges → Medical insurance cost billed to the individual, ranging from around $1,000 to over $60,000.

Tables

Insurance

@kaggle.saadaliyaseen_decoding_medical_costs_analyzing_insurance_data.insurance

24.54 kB
1,338 rows
7 columns

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