When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Seaborn Python: Visualize & Analyze Data Distributions

本课程是 Seaborn Python Data Visualization & Analysis 专项课程的一部分

位教师：EDUCBA

包含在中

了解更多

1个模块

深入了解一个主题并学习基础知识。

3 小时完成

灵活的计划

自行安排学习进度

1个模块

深入了解一个主题并学习基础知识。

3 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Analyze and visualize univariate and bivariate data distributions in Seaborn.
Build regression-based visualizations to model and interpret relationships.
Customize statistical plots using hue, facet grids, and styling for insights.

您将获得的技能

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

4 项作业

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Seaborn Python Data Visualization & Analysis 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有1个模块

This intermediate-level course is designed to help learners analyze, visualize, and interpret data distributions using the powerful Seaborn library in Python. Building upon foundational knowledge of data visualization, the course takes a hands-on approach to explore univariate and bivariate distributions, apply linear and polynomial regression models, and demonstrate advanced statistical plots such as KDE plots, pairplots, jointplots, and lmplots.

Through structured lessons and guided coding examples, learners will gain practical experience in crafting insightful visualizations that enhance exploratory data analysis. Emphasis is placed on understanding the relationship between variables and how these relationships can be effectively communicated using Seaborn’s built-in functions. By the end of the course, learners will be able to: • Identify key distribution types and the appropriate plots to represent them. • Construct regression-based visualizations to model complex relationships. • Customize multivariate visualizations using hue, facet grids, and plot styling. • Evaluate patterns and trends in data using statistical plotting techniques. This course is ideal for aspiring data analysts, data scientists, and Python developers looking to advance their data storytelling and statistical graphics capabilities using Seaborn.

单元详情

This module delves into intermediate-level data visualization techniques using the Seaborn library in Python. It focuses on building upon basic plotting knowledge by introducing the concepts of univariate and bivariate distributions, linear regression models, and multi-variable visualizations. Learners will gain practical experience with statistical graphics such as KDE plots, pairplots, and jointplots, enabling them to analyze and communicate insights from complex datasets. The module emphasizes hands-on plotting strategies that enhance data exploration and visual storytelling.