Project 2 - EDA on Vehicle Insurance Customer Data

In this project we need, pandas module to store and perform various operations on the data set.

Read the data:

1. The customer details and the customer vehicle insurance policy details are read and
converted to a pandas dataframe using read_csv().

Prepare the data:

2. Check the data frame to understand the different types of data(categorical and
numerical) present in each column.

Clean the data:

3. The dataframe must be checked for missing values using isnull() or fillna() and outliers
using first quartile and third quartile, so they can be treated either by removing or
replacing with a mean or median of the respective column.
4. Remove extra white spaces or correct the cases for each column data.

Analyze the data:

5. After cleaning the data, customer and customer insurance details can be analyzed using
aggregate functions like group by(), mean(), so we can find any patterns among the different data.
6. Check for the correlation between customer age and annual premium to find the
relationship if it is a positive or negative or no relationship.