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  • Udemy-The Complete Pandas Bootcamp 2020 Data Science with Python

    1. Home
    2. Courses
    3. Data Science Courses
    4. pandas
    5. 3. Pandas Basics (DataFrame Basics I)
    • 1. Getting Started
    • 2. PART 1 PANDAS FROM ZERO TO HERO (BUILDING BLOCKS)
    • 3. Pandas Basics (DataFrame Basics I)
    • 4. Pandas Series and Index Objects
    • 5. DataFrame Basics II
    • 6. Manipulating Elements in a DataFrame Slice Important, know the Pitfalls!
    • 7. DataFrame Basics III
    • 8. Visualization with Matplotlib
    • 9.PART 2 FULL DATA WORKFLOW A-Z
    • 10. Importing Data
    • 11. Cleaning Data
    • 12. Merging, Joining, and Concatenating Data
    • 13. GroupBy Operations
    • 14. Reshaping and Pivoting DataFrames
    • 15. Data Preparation and Feature Creation
    • 16. Advanced Visualization with Seaborn
    • 17. PART 3 COMPREHENSIVE PROJECT CHALLENGE
    • 18. PART 4 MANAGING TIME SERIES DATA WITH PANDAS
    • 19. Time Series Basics
    • 20. Time Series Advanced Financial Time Series
    • 21.WHATS NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE
    • 22. APPENDIX PYTHON BASICS, NUMPY and STATISTICS
    • 23. Python Basics
    • 24. The Numpy Package
    • 25. Statistical Concepts
    • 26. Download .py files
    • 27. Whats next
    • 3. Pandas Basics (DataFrame Basics I)

      • 1. Create your very first Pandas DataFrame (from csv) Page
      • 2. Pandas Display Options and the methods head() & tail() Page
      • 3. First Data Inspection Page
      • 4. Built-in Functions, Attributes and Methods with Pandas Page
      • 5. Make it easy TAB Completion and Tooltip Page
      • 7. Explore your own Dataset Coding Exercise 1 (Intro) Page
      • 8. Explore your own Dataset Coding Exercise 1 (Solution) Page
      • 9. Selecting Columns Page
      • 10. Selecting one Column with the dot notation Page
      • 11. Zero-based Indexing and Negative Indexing Page
      • 12. Selecting Rows with iloc (position-based indexing) Page
      • 13. Slicing Rows and Columns with iloc (position-based indexing) Page
      • 15. Selecting Rows with loc (label-based indexing) Page
      • 16. Slicing Rows and Columns with loc (label-based indexing) Page
      • 18. Indexing and Slicing with reindex() Page
      • 19. Summary, Best Practices and Outlook Page
      • 21. Coding Exercise 2 (Intro) Page
      • 22. Coding Exercise 2 (Solution) Page
      • 23. Advanced Indexing and Slicing (optional) Page
    ◄2. PART 1 PANDAS FROM ZERO TO HERO (BUILDING BLOCKS)4. Pandas Series and Index Objects►
    • pandas
    • 1. Getting Started
    • 2. PART 1 PANDAS FROM ZERO TO HERO (BUILDING BLOCKS)
    • 3. Pandas Basics (DataFrame Basics I)
    • 4. Pandas Series and Index Objects
    • 5. DataFrame Basics II
    • 6. Manipulating Elements in a DataFrame Slice Important, know the Pitfalls!
    • 7. DataFrame Basics III
    • 8. Visualization with Matplotlib
    • 9.PART 2 FULL DATA WORKFLOW A-Z
    • 10. Importing Data
    • 11. Cleaning Data
    • 12. Merging, Joining, and Concatenating Data
    • 13. GroupBy Operations
    • 14. Reshaping and Pivoting DataFrames
    • 15. Data Preparation and Feature Creation
    • 16. Advanced Visualization with Seaborn
    • 17. PART 3 COMPREHENSIVE PROJECT CHALLENGE
    • 18. PART 4 MANAGING TIME SERIES DATA WITH PANDAS
    • 19. Time Series Basics
    • 20. Time Series Advanced Financial Time Series
    • 21.WHATS NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE
    • 22. APPENDIX PYTHON BASICS, NUMPY and STATISTICS
    • 23. Python Basics
    • 24. The Numpy Package
    • 25. Statistical Concepts
    • 26. Download .py files
    • 27. Whats next
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