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Python in Excel Tutorial - How to Group with Pandas in Excel (ESSENTIAL SKILL FOR DATA ANALYSIS!)

WHY DID I MAKE THIS VIDEO? I’m working on a machine-learning project that runs entirely in Python in Excel. The analysis hinges on the grouping method .shift(), which is far less common than other pandas-in-Excel techniques. Rather than drop a random “.shift() only” clip, I built a broader Excel Python tutorial that walks beginners through every core grouping function—so you’ll never feel out of context when “groupby magic” shows up again. GOALS OF THIS EXCEL PYTHON GUIDE: 1. Introduce the essential pandas grouping concepts that power real-world python data analysis in Excel. 2. Show the doors that .groupby() unlocks—and the many directions you can take when using Python with Excel for data exploration. 3. Lay a foundation for future videos, so you’re not “a fish out of water” whenever grouped calculations reappear. 4. Cover the DataFrame-manipulation helpers you’ll most often pair with grouping—perfect for excel python beginners learning to type Python directly into a cell. SECTIONS OF THIS PYTHON EXCEL TUTORIAL: All sections use the groupby() function in conjunction with one of the with the following grouping functions: 1. .agg() – Pivot-table-style summaries (one row per group). (0:09) 2. .transform() – Keep original rows while broadcasting group-level metrics to every record. (5:00) 3. .apply() – Run any function per group; return a DataFrame, Series, or scalar. (10:36) 4. .filter() – Exclude entire groups that fail a rule. (15:40) 5. .shift() – Offset values for lead/lag time-series work. (23:05) FUNCTIONS COVERED: • xl() load sheet data as DataFrames inside Excel (true excel-python integration) • .groupby() form reusable group objects • .agg() pivot-style reports • .transform() broadcast totals back to each row • .apply() + custom top_products() using .nlargest() flexible top-N analytics • .filter() + len() rule-based group removal • .shift() row-wise lag within each group • .sort_values() primary / secondary ordering before a shift • .rename() quick header refresh • pd.concat() horizontally glue DataFrames • .reset_index(drop=True) spill clean results to the grid VIDEO TIMESTAMPS: 00:09 Use case for .agg(): pivot-table reporting (one row per group) 00:31 Demo-data overview (product database) 00:50 Load an Excel file with xl() 01:37 Build a group object with .groupby() 02:55 Why Excel can’t “spill” a group object 03:20 Create a pivot-style report with .agg() (single metric) 04:25 Move spilled output to another sheet location 04:35 Pivot-style report with .agg() (multiple metrics) 05:00 Use case for .transform(): broadcast totals 06:02 Demo-data overview for .transform() 06:15 Reusing the group object 07:05 Broadcast aggregates via .transform() 08:15 What a pandas Series is (in Excel) 09:19 Add a new column from a Series 09:45 Build calculated columns in place 10:16 Why formatting numbers in Excel is faster 10:36 Use case for .apply() 11:05 When to pick .apply() vs .transform() vs .agg() 11:25 Demo-data overview for .apply() 11:49 Reusing the group object again 12:39 Write a custom function for .apply() 13:30 Any DataFrame-level function works inside .apply() 13:35 Intro to .nlargest() 14:10 Top-3-revenue report per group via .apply() 14:26 ⚠️ Current Python-in-Excel bug with .apply() 15:13 Hide spilled indexes 15:40 Why & how to use .filter() 16:15 Prep the group object for filtering 17:24 Custom function for .filter() 17:59 Hide index column when spilling 18:28 Format values in Excel—not Python 18:33 Mechanics of .shift() on a single DataFrame 21:43 Mechanics of .shift() on groups 23:05 Dataset overview for .shift() demo 23:12 Real-world use case for .shift() + groups 24:28 Sort values before shifting 26:00 Shift grouped data with .shift() 26:31 Rename multiple headers with a dict 28:00 Concatenate DataFrames with pd.concat() 29:15 Calculate percent change 30:11 Drop indexes with .reset_index(drop=True) 📂 Download the demo file: https://www.spreadsheetwranglers.com/... If you’re using Python to automate Excel for the first time, check out my other python in Excel examples to master the fundamentals: ▶️ Channel:    / @learnpythoninexcel   🎥 My tutorial on DataFrame extraction basics pairs nicely with this python in excel tutorial. You can view it via this link:    • Python In Excel – Basic Data Frame Extract...   Whether you’re searching for how to use Python in Excel, a quick python for Excel demo, or a complete excel-python tutorial on groupby, this intro video shows practical, beginner-friendly workflows you can start applying today—no advanced setup required. Dive in and see how easily you can use Python in Excel to group, summarize, and analyze data with the power of pandas! If you found this video interesting please consider subscribing, giving it a thumbs up, or dropping me a line in the comments. Thank you for tuning in! -Dan