Easier data analysis in Python with pandas (video series)

This blog about series of videos was created by Kevin Markham. Kevin is a data science educator and the founder of Data School. He specializes in Python and machine learning. He has hundreds of hours of experience as a data science classroom instructor, and thousands of hours of experience developing high-quality data science educational materials.

Data science for beginners!

If you're working with data in Python, learning pandas will make your life easier! He loves teaching pandas, and so he created a video series targeted at beginners. New videos are released every Tuesday, and he'll create at least 30 videos.

About the video series

You don't need to have any pandas experience to benefit from this series, but you do need to know the basics of Python.

In each video, he answers a question from one of his students using a real dataset. Since he has posted the data online, and pandas can read files directly from a URL, you can follow along with every video at home!

Every video in the series is embedded below. 

There's also a well-commented IPython/Jupyter notebook containing the code from every video, and a GitHub repository containing all of the datasets.


List of videos (as of June 14)

  1. What is pandas? (Introduction to the Q&A series) (6:24) 
  2. How do I read a tabular data file into pandas? (8:54) 
  3. How do I select a pandas Series from a DataFrame? (11:10) 
  4. Why do some pandas commands end with parentheses (and others don't)? (8:45) 
  5. How do I rename columns in a pandas DataFrame? (9:36) 
  6. How do I remove columns from a pandas DataFrame? (6:35) 
  7. How do I sort a pandas DataFrame or a Series? (8:56) 
  8. How do I filter rows of a pandas DataFrame by column value? (13:44) 
  9. How do I apply multiple filter criteria to a pandas DataFrame? (9:51) 
  10. Your pandas questions answered! (9:06) 
  11. How do I use the "axis" parameter in pandas? (8:33) 
  12. How do I use string methods in pandas? (6:16) 
  13. How do I change the data type of a pandas Series? (7:28) 
  14. When should I use a "groupby" in pandas? (8:24) 
  15. How do I explore a pandas Series? (9:50) 
  16. How do I handle missing values in pandas? (14:27) 
  17. What do I need to know about the pandas index? (Part 1) (13:36) 
  18. What do I need to know about the pandas index? (Part 2) (10:38) 
  19. How do I select multiple rows and columns from a pandas DataFrame? (21:46) 
  20. When should I use the "inplace" parameter in pandas? (10:18) 
  21. How do I make my pandas DataFrame smaller and faster? (coming June 21) 
  22. How do I use pandas with scikit-learn to create Kaggle submissions? (coming June 28)

Check out the 22 videos, here. For more articles about pandas, click here

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