Introduction
Welcome to pandas
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1. Technical Setup
Using Google Colab
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What is pandas?
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Using pandas
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Reading tabular data into pandas
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2. Fundamentals of Working with pandas
Get an overview of the data and displaying it
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Select a Series (column)
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Challenge: Fundamentals
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Solution: Fundamentals
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Python lists and dictionaries
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Rename a Series (or column)
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Remove a Series (column) or row
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Filtering rows for a single condition
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Filter rows for multiple conditions
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Using String methods
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Sorting a DataFrame or Series
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3. Intermediate pandas Techniques
Working with data types (dtype)
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Memory usage of dtypes
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Defining dtypes when you read in a file
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Python functions
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Working with indexes
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Being productive in pandas: My best practices
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Creating Series and DataFrames
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Working with dates
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Combining DataFrames
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Combining datasets
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Working with missing data
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Removing missing data
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Working with duplicates
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Validating data
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Updating the dtypes
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Combine the datasets
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4. Visualizations
Plotting data
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Working with colormaps and seaborn
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Working with groupby
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Reshaping data: Stacking, unstacking, and MultiIndex
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Challenge: Visualizations
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Solution: Visualizations
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Creating your own colormaps
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5. Learning Recap
Final challenge: Recap
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Solution: Recap
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Conclusion
Your next steps in pandas
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Glossary_pandas_Essential_Training.zip
(64 KB)