Python in Excel For The Real World by Leila Gharani

Python in Excel For The Real World by Leila Gharani – Access Immediately

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Python in Excel For The Real World by Leila Gharani

What’s Inside

These lessons weren’t generated by AI.

They came from real-world experience. From years of teaching professionals how to solve problems with Excel.

This is built for professionals that use Excel, with a clear path to learn Python in Excel.

Along the way, you’ll pick up new advanced analysis techniques that will set you apart from your peers. And yes, you’ll learn Python too! Plus it will be a ton of fun.

Section 1: Getting Started with Python in Excel

• Welcome! What You’ll Learn in Python for Excel
• How to Use the Platform for Best Learning Experience
• How to Check If You Have Python in Excel
• What is Python?
• Warm up: Inputting Python Code
• Download Files & Cheat Sheets
• Looking for a Specific Topic? Use the Transporter!

Section 2: Advanced Data Analysis for Python Beginners

• Your First Python Formula – Is THIS Even Possible?!
• How Python in Excel Works (Behind the Scenes Explained)
• How to Find Valid Python Function Parameters
• Build a Quick Python-Powered Dashboard in Excel
• Bonus Tip – Use a Swarmplot to Spot Outliers Instantly
• Free vs. Premium Python in Excel: What’s the Difference?
• 💪 Challenge: Finding the Slowest with a Violin Plot
• Use AI to Help with Python – Copilot & ChatGPT
• 🎯 Quiz – Python Basics in Excel
• 📝 Key Takeaways from Your First Look at Python in Excel

Section 3: Core Python Skills for Working in Excel

• What are DataFrames? (plus describe them)
• How to Find What You Need in Pandas (value_counts, mean, etc.)
• Naming Your DataFrames and Column Shortcuts
• Why Knowing Objects, Methods & Properties Saves You Hours
• Python Rules You Need to Know: Return Values, Order etc.
• Python Editor Tips – References, Help & More
• Connect to External Data in Python – Excel Files, CSV, etc.
• 💪 Challenge: Import Data From a CSV into a DataFrame
• ✅ Solution: Import Data From a CSV into a DataFrame
• Keyboard Shortcuts to Work Faster with Python in Excel
• 🎯 Quiz – DataFrames & Pandas
• 📝 Key Takeaways – Core Python Skills

Section 4: Real-World Data Fixes With Python

• Excel Can’t Fix These Dates… But Python Can
• Extract Info From Dates – Quarter, Leap Year, Custom etc.
• Turn Columns into Rows with melt (Unpivot)
• Group and Summarize with groupby
• 💪 Challenge: Grouping to Find the Top Complaint (External Data)
• ✅ Solution: Grouping to Find the Top Complaint (External Data)
• Grouping Data by Year, Quarter, Month, Week
• Create Pivot-Like Summaries with pivot_table
• 📝 Key Takeaways – Data Fixes

Section 5: Half-Time Tactics for Python in Excel

• Do Cells Go Inside or Outside Parentheses?
• 🎯 Quiz – Python Logic and Referencing
• Filter Data with Just One Line in Python
• How to Add Calculated Columns to DataFrames
• Create Conditional Columns – The Python Way to Write IF
• 💪 Challenge: Conditional Logic Tested
• ✅ Solution: Conditional Logic Tested
• 📝 Key Takeaways – Filtering and Adding Columns

Section 6: Smarter Charting with Python in Excel

• Seaborn vs. Matplotlib – What Excel Users Should Know
• Bar Charts: Excel vs. Python – When to Use Each Tool
• Font Size Fixes – Making Python Charts Easier to Read
• Customizing Charts with Matplotlib (and AI)
• Smart Charts That Aggregate Automatically (Seaborn)
• 💪 Challenge: Time Tracking Analysis (External Data)
• ✅ Solution: Time Tracking Analysis (External Data)
• 💪 Bonus Challenge: Daily Averages Breakdown
• ✅ Bonus Solution: Daily Averages Breakdown
• Switch Charts with a Drop-Down – No VBA Needed
• Custom Visuals Inside Cells (Bullet Charts with Python)
• 🎯 Quiz – Charting with Python
• 📝 Key Takeaways – Smarter Charting

Section 7: Level up Tactics

• Python Functions (The Blueprint for Reusable Code)
• Bar Chart Function to Include Data Labels
• Mastering if, else – Conditional Logic in Python
• F-Strings in Python – Combining Text & Numbers Easily
• Combine Data Easily with concat
• 💪 Challenge: Combine & Summarize by Region Dropdown
• ✅ Solution: Combine & Summarize by Region Dropdown
• Importing Python Libraries (Word Cloud Example)
• (Don’t Skip) Core Python Library – Everything Starts Here
• Data Structures – The Key That Makes Everything Work
• 🎯 Quiz – Level Up
• 📝 Key Takeaways – Level Up Tactics

Section 8: Seaborn for Smarter Decisions (Project)

• Start Here: Project Overview & Data Reshape
• Bar Chart Toggle with Checkbox (Smart Python Trick)
• Trends Over Time with relplot (Multiple Charts)
• boxplot & stripplot – Spot Outliers and Variability
• catplot – One Line, Many Charts
• pairplot – Discover Hidden Data Connections
• Correlation, Heatmap, and lmplot – Explore Relationships
• 💪 Challenge: How Do Meetings Affect Productivity?
• ✅ Solution: How Do Meetings Affect Productivity?
• 📝 Key Takeaways – Reveal Insights with Seaborn Visuals

Section 9: Time Series & Forecasting

• Create Dynamic Rolling Averages in Excel with Python
• Exponential Smoothing: A Better Way to Spot Trends
• Calculate Growth Rates in Python
• Plot Multiple Charts in One: Growth + Sales (w/ Copilot & ChatGPT)
• Forecast Trends with Holt-Winters (Exponential Smoothing)
• Forecast with ARIMA (include Seasonality)
• Which Forecasting Model to Choose? (Plus More Resources)
• 📝 Key Takeaways – Time Series & Forecasting

Section 10: Machine Learning

• Machine Learning in Excel – What You Need to Know First
• Anomaly Detection with Isolation Forest
• Smarter Anomaly Detection with Isolation Forest (Using Context)
• Clustering with K-Means (Find Natural Segments)
• 💪 Challenge: Which Salaries Raise Red Flags?
• ✅ Solution: Which Salaries Raise Red Flags?
• 🎯 Quiz – Machine Learning & Anomaly Detection
• 📝 Key Takeaways – Machine Learning

BONUS 1: Python Vs. Power Query

• Power Query vs Python to Clean Data
• Python Cleaning Functions that Beat Power Query
• Cleaning data with Python
• Python vs. Excel vs. Power Query – Which One Wins?

BONUS 2: CoPilot & ChatGPT

• Tips for using Copilot
• Tips for using Chatgpt
• AI Prompt Pack

BONUS 3: Code Book

• The Copy-Paste Code Book

Wrap-up 

• Closing – where python fits in

Who This Is For

This course is designed for Excel power users who are ready to take their skills to the next level.

You’ve probably heard the buzz about Python in Excel, but maybe you’re unsure what it actually does—or whether it’s worth your time. The good news? You don’t need any programming background. Not even Python basics.

Here’s who this course is perfect for:

• You’re already strong in Excel, but you’ve hit its limits and it slows you down.

• You’ve seen “Python in Excel” mentioned, but aren’t sure how it truly helps.

• You’ve tried learning Python before but got stuck—whether on setup, syntax, or just too many confusing options.

• You work in analysis, reporting, or operations and want to cut through the messy, repetitive parts of your workflow.

• You’re not aiming to become a developer—you just want practical solutions that save time and make your work clearer.

Even if you don’t plan to use Python daily, this course shows you exactly where it makes a real difference—and how to use it directly inside the tool you already trust: Excel.

If Excel is your go-to, this training gives you an advantage. Not because you must use Python, but because you’ll finally know when it’s the smarter choice.