Is this course suitable for beginners?

Yes! This course is ideal for beginners who want to learn how to manipulate DataFrames.

What is meant by data manipulation in Python?

When we talk about data manipulation, we’re referring to the process of organizing data to make it easier to analyze. In Python, pandas is an open-source library used for data analysis and manipulation.

Is Python good for data manipulation?

Yes, Python is a great language for every stage of data analysis, including data manipulation. There are many Python libraries that can help users organize and visualize their data. Specifically, the pandas library is good for data manipulation.

What is the difference between NumPy and pandas?

pandas can be used to analyze and manipulate all kinds of data, whereas NumPy is primarily used for numerical calculations.

Will I receive a certificate at the end of the course?

Yes, you will receive a certificate of completion once you’ve finished the course, and it will automatically appear on your profile.

What kind of datasets are used in this course?

In this course, you’ll get hands-on experience manipulating real-world datasets, such as Walmart sales figures and global temperature time series.

How long does it take to complete this course?

The course should take about four hours to complete.

Data Manipulation with pandas Course

Name: Data Manipulation with pandas
Rating: 4.807775198938992 (12064 reviews)

Data Manipulation with pandas

BasicSkill Level

4.8+

12,064 reviews

Updated 09/2025

Learn how to import and clean data, calculate statistics, and create visualizations with pandas.

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Course Description

Discover Data Manipulation with pandas

With this course, you’ll learn why pandas is the world's most popular Python library, used for everything from data manipulation to data analysis. You’ll explore how to manipulate DataFrames, as you extract, filter, and transform real-world datasets for analysis.

With pandas, you’ll explore all the core data science concepts. Using real-world data, including Walmart sales figures and global temperature time series, you’ll learn how to import, clean, calculate statistics, and create visualizations—using pandas to add to the power of Python.

Work with pandas Data to Explore Core Data Science Concepts

You’ll start by mastering the pandas basics, including how to inspect DataFrames and perform some fundamental manipulations. You’ll also learn about aggregating DataFrames, before moving on to slicing and indexing.

You’ll wrap up the course by learning how to visualize the contents of your DataFrames, working with a dataset that contains weekly US avocado sales.

Learn to Manipulate DataFrames

By completing this pandas course, you’ll understand how to use this Python library for data manipulation. You’ll have an understanding of DataFrames and how to use them, as well as be able to visualize your data in Python.

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What you'll learn

Identify methods to import, inspect, and subset pandas DataFrames using functions like .head(), .info(), and .loc[].
Differentiate between aggregation techniques using .groupby() and pivot tables for grouped statistics.
Recognize how to modify DataFrames by adding new columns, setting indexes, and handling missing values.
Define common visualization types in pandas, including bar, line, scatter, and histogram plots.
Assess when to use Boolean masking, sorting, and slicing techniques for efficient data selection.

Prerequisites

Intermediate Python

Transforming DataFrames

Let’s master the pandas basics. Learn how to inspect DataFrames and perform fundamental manipulations, including sorting rows, subsetting, and adding new columns.