Project Title - US AUTOMOBILE INSURANCE DATA ANALYSIS.

TODO - Write some introduction about your project here: describe the dataset, where you got it from, what you're trying to do with it, and which tools & techniques you're using. You can also mention about the course Data Analysis with Python: Zero to Pandas, and what you've learned from it.

This course project is a data analysis on the US AUTOMOBILE INSURANCE. the data set is made up of 1000 rows and 40 columns which was obtained from kaggle datasets. am trying to figure out the minimum premium amount a person is willing to pay to be insured giving a particular car model, the distribution of people of certain educational level who seek automobile insurance, and also to find out the compare the number of males and females who seek auto_mobile insurance. I will also be looking at how premium payments affects total claim of a person and also look at how policy deductibility affects how much a premium a person pays.

Throughout the course I Will be making use of python libraries on data manipulation such as pandas, numpy and visualization tools such as matplotlib and and seaborn. All this tools and technique has been made handy through the online course on Data Analysis with python : Zero to pandas: https://jovian.ai/learn/data-analysis-with-python-zero-to-pandas .

Downloading the Dataset

TODO - This is the first step in data analysis, at this step am downloading a kaggle data set is csv format. the main data I will be using is stored in as 'insurance_claims.csv' found in the directory './automobile-insurance'. This data was collected from an Insurance company in the US.
The is downloaded by firt installing the jovian opendatasets library and following the series of codes below.

Let's begin by downloading the data, and listing the files within the dataset.