To round out your exploration of data science in Python, in this course, you'll work with the pandas DataFrame—one of the most prominent data structures in data science. You'll create DataFrames, load and save data, analyze data, and slice and filter data in DataFrames. Then, you'll manipulate, modify, and plot DataFrame data. Lastly, you'll work with specialized plotting libraries Matplotlib and Seaborn to create common types of plots and format those plots so they are visually appealing and optimal for analysis.
Python Data Science: pandas, Matplotlib, and Seaborn
Python Data Science: pandas, Matplotlib, and Seaborn
This course is part of Using Data Science Tools in Python Specialization
Instructor: Bill Rosenthal
Access provided by Alliance University
Gain insight into a topic and learn the fundamentals.
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
In this course, you will manage, analyze, manipulate, modify, and visualize pandas DataFrames; and visualize data with Matplotlib and Seaborn.
Skills you'll gain
- Python Programming
- Data Analysis
- Scatter Plots
- NumPy
- Data Science
- Data Visualization
- Graphing
- Box Plots
- Software Development
- Pandas (Python Package)
- Seaborn
- Computer Programming
- Jupyter
- Plot (Graphics)
- Data Transformation
- Matplotlib
- Data Manipulation
- Data Visualization Software
- Computer Programming Tools
- Data Processing
Details to know
Shareable certificate
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Assessments
1 assignment
Taught in English
Recently updated!
January 2026
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This course is part of the Using Data Science Tools in Python Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 4 modules in this course
While NumPy serves as the foundation of your data science tasks, you may instead work directly with the more user-friendly library called pandas, which builds on NumPy. Or, you may find it beneficial to work with both. In either case, as with NumPy, you'll want to begin by managing your data within pandas structures and then analyze that data for useful insights.
What's included
1 reading6 plugins
The pandas libraries provides many tools for changing data to meet your needs. It also provides basic plotting functionality for the analysis and/or presentation of data. In this lesson, you'll transform and visualize your data in multiple ways.
What's included
5 plugins
Although you did some simple plotting with pandas directly, you'll likely need to get more detailed with your visualizations. Matplotlib is the most common plotting library in Python®, and you'll use it to generate visualizations that help you tell a story with your data. Likewise, you'll use the Seaborn library, which is built on Matplotlib, to help you streamline your plotting efforts.
What's included
7 plugins
You'll wrap things up and then validate what you've learned in this course by taking an assessment.
What's included
1 reading1 assignment1 plugin
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