How to Analyze and Manipulate Data Using Pandas in Python
In this session, you’ll learn how to analyze and manipulate data using Pandas, Python’s most widely used data analysis library. This lesson covers Pandas data structures, loading and inspecting data, filtering and sorting datasets, aggregating results, grouping data, and reshaping data for analysis.
You’ll learn how data analysts use Pandas to clean, explore, summarize, and transform datasets — the same workflows used in real-world data analytics and business analysis roles.
Key Takeaways
Understand what Pandas is and how it is used for data analysis
Learn the core Pandas data structures: DataFrames and Series
Learn how to load data into Pandas
Learn how to inspect datasets using .head(), .info(), .shape(), and .isnull()
Learn how to sort data using .sort_values()
Learn how to filter data using logical conditions
Learn how to calculate aggregates such as mean, median, max, and min
Learn how to group data using .groupby()
Learn how to pivot data using .pivot_table()
Learn how indexing, stacking, and unstacking work in Pandas
Chapters
00:00 Introduction to Pandas for data analysis
06:40 Pandas DataFrames and Series
18:30 Loading data into Pandas
32:10 Inspecting data with head, info, and shape
45:20 Identifying missing values with isnull
58:30 Sorting and filtering data
1:10:40 Aggregating data using mean, median, max, min
1:22:30 Grouping data with groupby
1:30:00 Pivoting data with pivot_table
1:35:00 Indexing, stacking, and unstacking
Q&A
Q: What is Pandas used for?
A: Pandas is used to load, clean, analyze, and manipulate structured data in Python.
Q: What is the difference between a DataFrame and a Series?
A: A DataFrame is a table-like structure, while a Series is a single column of data.
Q: Why do data analysts use Pandas?
A: Data analysts use Pandas to efficiently clean, explore, and summarize large datasets.
Q: What does groupby do in Pandas?
A: groupby allows you to aggregate data by categories and calculate metrics for each group.
Q: What is pivot_table used for in Pandas?
A: pivot_table reshapes data to summarize and analyze it across dimensions.
Learning Path
Learning Path
This video is part of the Python Foundations for Data Analysis (Beginner Learning Path).
🔗 Watch the full playlist here: • How to Analyze Data Using Python Libraries...
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