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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/python-for-data-visualization
课程评论：没有评论
课程名称：Python 数据可视化 课程概述：“一图胜千言”，这是我们耳熟能详的表达。在处理日益庞大的数据集时尤其如此。数据可视化在小规模和大规模数据的表示中起着至关重要的作用。数据科学家的关键技能之一是能够以引人入胜的方式讲述故事，视觉化数据和发现。学习如何利用软件工具进行数据可视化将使您能够提取信息，更好地理解数据，并做出更有效的决策。 本课程的主要目标是教您如何将初看似毫无意义的数据，以人们易于理解的形式呈现出来。我们将使用Python中的多个数据可视化库，如Matplotlib、Seaborn和Folium，通过多种技术来展示数据。 限时优惠：订阅费用为每月39美元，可访问评分材料并获得证书。 课程大纲： 1. **数据可视化工具介绍**：学习数据可视化的基本概念及最佳实践，了解Matplotlib的历史和架构，并进行基础绘图。 2. **基础和专业可视化工具**：使用Matplotlib创建多种图形，如面积图、直方图、条形图、饼图、箱线图和散点图。 3. **高级可视化与地理空间数据**：学习高级可视化工具和Seaborn库，创建回归图，使用Folium进行地理空间数据可视化，包括制作地图和生成色块图。 4. **使用Plotly和Dash创建仪表板**：探索仪表板的优势，学习使用Plotly和Dash库创建互动图表。 5. **最终项目与考试**：将所学技能应用于分析历史汽车销售数据，利用数据可视化技术完成最终作业，并参与同伴评审及最终考试。 通过本课程，您将掌握数据可视化的核心技能，能够将复杂数据转化为易于理解的图形，为数据分析提供支持。
Name:Introduction to Data Visualization Tools
Description:Data visualization is a way of presenting complex data in a form that is graphical and easy to understand. When analyzing large volumes of data and making data-driven decisions, data visualization is crucial. In this module, you will learn about data visualization and some key best practices to follow when creating plots and visuals. You will discover the history and the architecture of Matplotlib. Furthermore, you will learn about basic plotting with Matplotlib and explore the dataset on Canadian immigration, which you will use during the course. Lastly, you will analyze data in a data frame and generate line plots using Matplotlib.
Name:Basic and Specialized Visualization Tools
Description:Visualization tools play a crucial role in data analysis and communication. These are essential for extracting insights and presenting information in a concise manner to both technical and non-technical audiences. In this module, you will create a diverse range of plots using Matplotlib, the data visualization library. Throughout this module, you will learn about area plots, histograms, bar charts, pie charts, box plots, and scatter plots. You will also explore the process of creating these visualization tools using Matplotlib.
Name: Advanced Visualizations and Geospatial Data
Description:Advanced visualization tools are sophisticated platforms that provide a wide range of advanced features and capabilities. These tools provide an extensive set of options that help create visually appealing and interactive visualizations. In this module, you will learn about waffle charts and word cloud including their application. You will explore Seaborn, a new visualization library in Python, and learn how to create regression plots using it. In addition, you will learn about folium, a data visualization library that visualizes geospatial data. Furthermore, you will explore the process of creating maps using Folium and superimposing them with markers to make them interesting. Finally, you will learn how to create a Choropleth map using Folium.
Name: Creating Dashboards with Plotly and Dash
Description:Dashboards and interactive data applications are crucial tools for data visualization and analysis because they provide a consolidated view of key data and metrics in a visually appealing and understandable format. In this module, you will explore the benefits of dashboards and identify the different web-based dashboarding tools in Python. You will learn about Plotly and discover how to use Plotly graph objects and Plotly express to create charts. You will gain insight into Dash, an open-source user interface Python library, and its two components. Finally, you will gain a clear understanding of the callback function and determine how to connect core and HTML components using callback.
Name: Final Project and Exam
Description:The primary focus of this module is to practice the skills gained earlier in the course and then demonstrate those skills in your final assignment. For the final assignment you will analyze historical automobile sales data covering periods of recession and non-recession. You will bring your analysis to life using visualization techniques and then display the plots and graphs on dashboards. Finally, you will submit your assignment for peer review and you will review an assignment from one of your peers. To wrap up the course you will take a final exam in the form of a timed quiz.
"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. 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. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
