Pandas Filtering & Subsetting Explained in 15 Minutes (With Real Data Science Example)

Learn how to filter and subset data in Pandas using Python with real examples.
In this tutorial, we explore DataFrame filtering using conditions, boolean indexing, .isin(), .iloc slicing, and column selection — essential skills every data scientist, analyst, and Python developer must master.

We build a realistic employee dataset and walk through multiple practical filtering techniques used in real data science workflows, including:
✔ Filtering rows using conditions (age greater than 25, salary greater than 100000)
✔ Combining multiple conditions with AND / OR logic
✔ Selecting rows using .isin() for multiple categories
✔ Subsetting columns in a DataFrame
✔ Using .iloc to slice rows and columns by index position
✔ Building a custom Python function that combines multiple filtering techniques

By the end of this tutorial, you will understand how professional data scientists filter and analyze datasets using Pandas efficiently.

This tutorial is perfect for:
• Python beginners
• Data science students
• Data analysts
• Machine learning engineers
• Anyone learning Pandas for data analysis

🧠 Topics Covered
- Pandas DataFrame filtering
- Boolean indexing in Pandas
- Pandas .isin() usage
- Pandas .iloc slicing
- Conditional filtering in Python
- DataFrame subsetting techniques
- Real-world data analysis example

Timestamps:
0:00 - Introduction: Why Filtering Matters
0:55 - The Basic Age Filter (numerical value filter)
2:21 - Filter the data based on the text value
3:20 - Multiple condition filter in the same subset
4:33 - Filter with Pipe-Operator (One of the condition needs to be True)
06:24 - Is In Function (Either one of the value in the list is available in the column)
07:55 - Slice the data only for two columns out of all 7 columns
08:55 - Index Location (df.iloc[:])
11:29 - Combine all the filter and slicing into one single function and return the final result
15:45 - Final Review and Adjustments

💻 Libraries Used
Python
Pandas
NumPy

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About Data Speaks:
Welcome to Data Speaks, where we simplify complex Data Science and AI concepts into actionable hands-on in-depth tutorials. My name is Ishwor, I have several years of hands-on experience as Data Scientist in the real world along with mentoring and teaching Data Science and AI in world's top university (MIT, John's Hopkins, University of AustinTexas)'s online Data Science and AI courses. My goal is to help you master Python, Machine Learning, and Data Analytics.
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