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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-visualization-in-python-using-matplotlib-and-seaborn/
课程评论：没有评论
**课程名称：** Python数据可视化：Matplotlib与Seaborn **课程概述：** 本课程是一门以项目为导向的Seaborn数据可视化课程。您将学习如何使用Seaborn——一个受Matplotlib启发的高级Python数据可视化库——创建快速、交互式的数据可视化图表。课程将引导您探索内置的Gapminder数据集，并制作交互式、适用于出版级别的图表，以增强数据分析能力。 在数据科学领域，清晰、引人入胜的数据呈现是关键技能之一。学习数据可视化工具能帮助您从数据中提取信息，更深入地理解数据，并做出更有效的决策。本课程的主要目标是教会您如何将看似无意义的数据转化为易于理解的形式。我们将重点使用 **Matplotlib**、**Seaborn** 和 **Folium** 这几个Python数据可视化库。 **学习收获：** * 掌握使用Seaborn创建多样化、高质量数据可视化的技巧。 * 能够利用Matplotlib和Seaborn进行数据探索和分析。 * 学会制作交互式、可用于报告和发表的图表。 * 提升从数据中讲故事的能力，以更直观、有吸引力的方式呈现分析结果。 * 了解如何使用Folium进行地理空间数据可视化。 * 能够将原始数据转化为有意义的洞察。
"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data.Welcome to this project-based course on Data Visualization with seaborn. In this project, you will create quick and interactive data visualizations with seaborn: a high-level data visualization library in Python inspired by matplotlib. You will explore the various features of the in-built Gapminder dataset, and produce interactive, publication-quality graphs to augment analysis.One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions. The main goal of this Data Visualization with Python course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium.
