In this video, we’ll tackle a real-world scenario: calculating monthly sales commissions for sales representatives using Pandas in Python. We’ll walk through a complete workflow, from merging data sets and handling missing values to calculating commissions and exporting a final, shareable report.
Learn how to automate your sales commission reporting process with Python and Pandas. We’ll cover essential techniques for cleaning, transforming, and analyzing sales data, allowing you to generate accurate and insightful reports for your stakeholders. This tutorial provides a practical, step-by-step guide to calculating monthly sales commissions and exporting the results for easy sharing.
*Topics Covered:*
* Introduction to Sales Commission Calculation with Pandas
* Loading Sales Data and Sales Rep Data
* Merging Data Sets (`pd.merge()`)
* Handling Missing Commission Percentages (`fillna()`)
* Calculating Commission Earned (`assign()`)
* Extracting Sales Month from Sale Date
* Grouping and Aggregating Data (`groupby()`, `agg()`)
* Calculating Total Sales and Total Commission per Sales Rep
* Exporting the Final Report to CSV (`to_csv()`)
* Real-World Data Analysis Scenario for Sales Performance
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In upcoming videos, we’ll explore additional file formats and advanced data manipulation techniques. Stay tuned to master the full capabilities of Python Pandas!
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