pandas Essential Training

Discover how to work with the pandas library and tools for data analysis and data structuring.

Introduction

• Welcome to pandas

1. Technical Setup

• Using Google Colab
• What is pandas?
• Using pandas
• Reading tabular data into pandas

2. Fundamentals of Working with pandas

• Get an overview of the data and displaying it
• Select a Series (column)
• Challenge: Fundamentals
• Solution: Fundamentals
• Python lists and dictionaries
• Rename a Series (or column)
• Remove a Series (column) or row
• Filtering rows for a single condition
• Filter rows for multiple conditions
• Using String methods
• Sorting a DataFrame or Series

3. Intermediate pandas Techniques

• Working with data types (dtype)
• Memory usage of dtypes
• Defining dtypes when you read in a file
• Python functions
• Working with indexes
• Being productive in pandas: My best practices
• Creating Series and DataFrames
• Working with dates
• Combining DataFrames
• Combining datasets
• Working with missing data
• Removing missing data
• Working with duplicates
• Validating data
• Updating the dtypes
• Combine the datasets

4. Visualizations

• Plotting data
• Working with colormaps and seaborn
• Working with groupby
• Reshaping data: Stacking, unstacking, and MultiIndex
• Challenge: Visualizations
• Solution: Visualizations
• Creating your own colormaps

5. Learning Recap

• Final challenge: Recap
• Solution: Recap

Conclusion

• Your next steps in pandas