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
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Python Data Science: pandas, Matplotlib, and Seaborn
本课程是 Using Data Science Tools in Python 专项课程 的一部分
位教师：Bill Rosenthal
包含在 中
您将学到什么
In this course, you will manage, analyze, manipulate, modify, and visualize pandas DataFrames; and visualize data with Matplotlib and Seaborn.
您将获得的技能
- Data Transformation
- Jupyter
- Data Analysis
- Python Programming
- Graphing
- Software Development
- Data Science
- Matplotlib
- Data Manipulation
- Data Visualization Software
- Scatter Plots
- Data Visualization
- Computer Programming
- Box Plots
- Pandas (Python Package)
- Seaborn
- Computer Programming Tools
- Plot (Graphics)
- Data Processing
- NumPy
要了解的详细信息
可分享的证书
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最近已更新！
January 2026
作业
1 项作业
授课语言：英语（English）
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积累特定领域的专业知识
本课程是 Using Data Science Tools in Python 专项课程 专项课程的一部分
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该课程共有4个模块
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.
涵盖的内容
1篇阅读材料6个插件
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.
涵盖的内容
5个插件
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.
涵盖的内容
7个插件
You'll wrap things up and then validate what you've learned in this course by taking an assessment.
涵盖的内容
1篇阅读材料1个作业1个插件
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