/Data-Analysis-Using-Python-

Using Python to perform data wrangling, EDA to assess the medical cost people have spent with respect to their age, gender and body mass index.

Primary LanguageJupyter Notebook

Work in Repl.it

{Analysis on the Medical Cost per Person in United States}

Project Link:

https://youtu.be/aLZfYIxQAE4

The dashboard is located in the tableau package

Description

Our interest is to assess the medical cost people have spent with respect to their age, gender and body mass index. An application that uses these statistics would be insurance companies to make calculations for insurance costs of medical plans. We are interested in multiple variables in our dataset, age, bmi, childrens, smoker in correlation with their medical cost. We will be focusing on medical cost as our primary variable with relation to other variables. We can calculate the mean medical cost for certain age groups, and compare the medical costs between men and women. There are many inspirations and questions to assess from this data set and it is certainly possible to make an user dashboard.

Dataset

Our dataset has 7 columns and more than 1338 rows of tuples. We are intested in analyzing the following variables: 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; 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. The dataset is retrieved from Kaggle.com to explain the cost of a sample of USA population Medical Insurance Cost based on some attributes depicted on "Content".