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Congratulations

1. Congratulations

Congratulations on completing the course, you've covered a lot!

2. Inspection and validation

You started off by learning how to inspect and validate data,

3. Aggregation

before performing aggregation and calculating summary statistics!

4. Address missing data

You saw how to check for missing values.

5. Address missing data

You then identified strategies to deal with it, including dropping missing values, and imputation!

6. Analyze categorical data

You discovered how to create categories from strings,

7. Apply lambda functions

use lambda functions to conditionally calculate summary statistics based on categories and add values into the original DataFrame,

8. Handle outliers

and deal with outliers!

9. Patterns over time

You progressed to examining relationships, including patterns over time,

10. Correlation

correlation between variables,

11. Distributions

and interpreting distributions!

12. Cross-tabulation

In the final chapter you learned the benefits of cross-tabulation,

13. pd.cut()

generated new features using pd-dot-cut,

14. Data snooping

and saw the impact of data snooping!

15. Generating hypotheses

You finished by identifying the limits of EDA and the next step of the data science workflow, hypothesis testing.

16. Next steps

Now you understand EDA, you may wish to explore some courses that build on the concepts in this course, such as the steps involved in hypothesis testing, or supervised learning, which is a form of machine learning!

17. Congratulations!

We hope you've enjoyed the course and feel confident in performing exploratory data analysis going forward!