1. Data Analysis > 
  2. Exploratory Data Analysis with pandas > 
  3. Next Steps

Next Steps

The next chapter will dive into cleaning data with pandas. Before proceeding, if you would like to further your understanding of pandas, here are some of our favorite resources.

  1. pandas Documentation: 10 minutes to pandas
  2. pandas Documenation: Intro to data structures
  3. pandas Documentation: Indexing and selecting data
  4. Kaggle: EDA with Pandas
  5. NumPy Documentation
Oct 1, 2021
LaunchCode

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    • 1. About LaunchCode Courses
      • 2. Our Approach to Learning Data Analysis
        • 3. Introduction to Data
          • 4. Introduction to Excel and Spreadsheets
            • 7. SQL Part 1: Introduction and Azure Data Studio
              • 8. SQL Part 2: String and Date Functions
                • 9. SQL Part 3: Joins
                  • 10. SQL Part 4: Subqueries, CTEs, UNION, INTERSECT, EXCEPT
                    • 11. SQL Part 5: Schemas and CRUD Operations
                      • 12. How Programs Work
                        • 13. How to Write and Run Code
                          • 14. Data and Variables
                            • 15. Making Decisions with Conditionals
                              • 16. Loops
                                • 17. Collections
                                  • 18. Functions are at Your Beck and Call
                                    • 19. Exploratory Data Analysis with pandas
                                      • Reading
                                        • Exercises: EDA with pandas
                                        • Studio: EDA with pandas
                                        • Next Steps
                                      • 20. Cleaning Data with Pandas
                                        • 21. Data Manipulation
                                          • 22. Data Visualization with Python
                                            • 23. Databases with Python and pandas
                                              • 24. Tableau Part 1: Intro to Visualization
                                                • 25. Tableau Part 2: Data Preparation
                                                  • 26. Tableau Part 3: Calculations, Parameters and Relationships
                                                    • 27. Tableau Part 4: Stories and Dates
                                                      • GA: Graded Assignments
                                                        • INSTL. Installations
                                                          • Appx. Appendices

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