EDA on Vehicle Insurance Customer Data
- Cleaned and analyzed customer data by handling missing and unusual values, removing extra spaces, and converting categorical variables into binary format for future modeling purposes.
- The project involved merging customer and policy tables to generate a master table. Relevant information such as average annual premiums by gender, age, and vehicle age was extracted from this table.
- Explored the correlation between a person’s age and annual premium using a correlation coefficient, which revealed if there was any relationship between the two variables.
- Technologies/concept:
Handled and cleaned null values using Pandas. Statistical analysis for finding the correlation coefficient.