Python in Excel: Working with pandas DataFrames
1h 48mIntermediate2024-04-11
Authors
Felix Zumstein
Course details
Python and Excel are both some of the most popular “programming languages”, especially for data analytics/data science. Combined, they are even more powerful. In this course, author and Excel expert Felix Zumstein explains how to work with pandas DataFrames in Excel. pandas DataFrames are the backbone of every Python-based data analysis in Excel. Get a thorough introduction to DataFrames. Learn how to turn different sources—such as an Excel range, an Excel table, or a Power Query—into a DataFrame. Find out why and when it makes sense to use a DataFrame, as opposed to native Excel features like Power Query, Pivot Tables, or VLOOKUP formulas. Use a practical dataset to explore the basics of working with DataFrames, including an index, headers, filtering data, dropping duplicates, adding a new column, combining two DataFrames, and re-indexing. Plus, take a quick look at time series and visualizations.
Skills covered
pandasSpreadsheetsMicrosoft ExcelPythonData AnalysisProgramming LanguagesData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceMicrosoftSoftware DevelopmentOne-Off
Concepts
Introduction
- Python in Excel and pandas DataFrames
- What you should know
- About Python in Excel
Introduction to pandas
- Hello World
- pandas DataFrame and Series
- Data selection
- Calculations, vectorization, and empty cells
- Row filtering
- Manipulating DataFrames
- Python editor and magic commands
Data Analysis
- Data cleaning
- Working with text data
- Combining DataFrames
- Data aggregation
- Plotting
Time Series Analysis
- Introduction to time series
- Time series analysis with pandas DataFrames
- Shifting and percentage changes
- Comparing time series
- Resampling and correlation
- Case study - Sales dashboard
Conclusion
- The next steps for learning more about Python in Excel