Project 2 - EDA on Vehicle Insurance Customer Data

Exploratory Data Analysis using Customer Vehicle Insurance

Subject:

Read the dataset and perform exploratory data analysis on the customer vehicle insurance to find different trends or patterns or relationships.

Description:

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 filina() 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 correlation between customer age and annual premium to find relationship.