44 Powerful Notebooks

This collection of Jupyter Notebooks empowers data engineers and analysts to tackle difficult data problems quickly. Each notebook is designed to give you a comprehensive view of how to solve some of the most complex data problems out there using the lightning-fast Polars library.

Lifetime Updates

This power pack is in the expansion phase. Throughout the next several months you’ll see more Jupyter Notebooks appear in the power pack. Your purchase today includes lifetime updates to new resources at no additional cost. You can check for updates on your downloads page. 

Contents

• add_business_days.ipynb

• Anti Join.ipynb

• Appending DataFrames.ipynb

• business_day_count.ipynb

• Case Conventions.ipynb

• Cleaning Job Application Data.ipynb

• Cross Join.ipynb

• Date & Time Conversions.ipynb

• Day Expressions.ipynb

• Epoch Expressions.ipynb

• Expressions & Contexts.ipynb

• Find & Replace.ipynb

• from_pandas.ipynb

• implode.ipynb

• Inner Join.ipynb

• json_normalize.ipynb

• Left Join.ipynb

• Map CSV Files to SQL Server.ipynb

• Month Expressions.ipynb

• Obscuring Sensitive Data.ipynb

• Query Optimization.ipynb

• read_clipboard.ipynb

• read_csv.ipynb

• read_database.ipynb

• read_excel.ipynb

• read_json.ipynb

• read_ndjson.ipynb

• read_ods.ipynb

• Reading Multiple CSV Files at Once.ipynb

• Regular Expressions (regex).ipynb

• scan_csv.ipynb

• schemas.ipynb

• Strings To Decimals.ipynb

• Strings To Integers.ipynb

• Time Zone Expressions.ipynb

• to_pandas.ipynb

• Validating Job Application Data.ipynb

• when-then-otherwise.ipynb

• Write to SQLite DB.ipynb

• write_csv.ipynb

• write_excel.ipynb

• write_json.ipynb

• write_ndjson.ipynb

• Year Expressions.ipynb