pandas Analytics for Excel Users
57mAdvanced2023-07-24
Authors
Madecraft
Full-Service Learning Content Company
George Mount
Course details
Python comes with its own built-in software library for data manipulation and analysis. It’s called pandas, and it’s an extremely fast and powerful open-source tool that lets you analyze data more efficiently—right from a spreadsheet in Microsoft Excel.
Learn the basics of pandas analytics in this course designed specifically for Excel users, following advice from instructor and Excel MVP George Mount. Get up and running with your first moves in pandas, summarizing and visualizing data, working with rows and columns, cleaning data, and working with dates and times. Along the way, practice your skills using real-world data with an end-to-end analysis drawn from baseball.
Learn the basics of pandas analytics in this course designed specifically for Excel users, following advice from instructor and Excel MVP George Mount. Get up and running with your first moves in pandas, summarizing and visualizing data, working with rows and columns, cleaning data, and working with dates and times. Along the way, practice your skills using real-world data with an end-to-end analysis drawn from baseball.
Skills covered
pandasSpreadsheetsMicrosoft ExcelData AnalysisData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceMicrosoftOne-Off
Concepts
0. Introduction
- 01 - Python and Excel for analytics
1. First Steps with pandas
- 02 - Why pandas for analytics
- 03 - Using pandas DataFrames
2. Summarizing and Visualizing Data in Pandas
- 04 - Printing and exploring DataFrames
- 05 - pandas plotting basics
3. Working with Rows and Columns
- 06 - Adding calculated columns
- 07 - Renaming and dropping columns
- 08 - Sorting rows
- 09 - Filtering rows
4. Cleaning Data
- 10 - Aggregating a DataFrame
- 11 - Merging two DataFrames
- 12 - Working with missing values
- 13 - Reshaping a DataFrame
5. Working with Dates and Times
- 14 - Aggregating by time period
- 15 - Creating window functions
6. Practice Your Skills
- 16 - Practicing with real data
Conclusion
- 17 - Continuing your Python journey