EDA on Vehicle Insurance Customer Data
Exploratory Data Analysis is applied to investigate the data and summarize the key insights. This is done to provide basic understanding of the data. EDA for the given dataset can be done by following the steps below
1. Adding the column names to the dataset
2. Checking and Cleaning Data Quality:
- Generate a summary of count of all the null values column wise
- Drop Null values because central tendencies for id’s is not feasible.
- Replace all null values for numeric columns by mean.
- Null values for Categorical value by mode.
- Generate a summary of count of all the outliers column wise
- Replace all outlier values for numeric columns by mean.
- Remove white spaces
- Case correction(lower or upper, any one)
- Convert nominal data (categorical) into dummies
- Drop Duplicates (duplicated rows)
3. Create a Master table for future use.
4. Extracting following information from the master table:
- Gender wise average annual premium
- Age wise average annual premium
- Is your data balanced between the genders
- Vehicle age wise average annual premium.