Python Project - EDA on Vehicle Insurance Customer Data

A company has customer data that contains customer details and customer policy datac that contains the policy details of the customer.

The company intends to offer some discount in premium for certain customers. To do that they ask their Data scientist team to get some information. Hence, following tasks Data scientist team has decided to perform

• Checking and Cleaning Data quality by generating summary of count of null values and outliers, dropping null values, replacing null values and outliers for numeric data by mean, replacing null value for categorical data by mode, removing white spaces, case correction, converting nominal data (categorical) into dummies for future modeling use and dropping duplicates.
• Getting information for gender wise average annual premium, vehicle age wise average annual premium, age wise average annual premium, checking if the data is balanced between the genders.
• Finding correlation between person age and annual premium.

Python library used: Pandas