In the information age, vast amounts of data are generated every moment. Some data visualizations that simplify complexity, are intuitive and elegant, and even evoke a sense of wonder, not only complement high-level research outcomes but also help the authors enhance their understanding of the data, gain more valuable insights, and add value to research results, making it easier to attract the attention of reviewers and readers.On the path of advancing data visualization, everyone has likely experienced creating ordinary or even somewhat ugly charts using Excel’s built-in chart features. As research capabilities and aesthetics improve, especially after seeing the works of experts, data visualization has started to receive our attention, with tools gradually transitioning from office-level to professional-level. In research scenarios, the massive data and complex computational requirements, along with the professional and exquisite presentation of charts, demand higher standards from the tools we choose.
Looking at the journey of data visualization, Python visualization is a powerful tool that is both new and highly functional. Once you conquer this peak, ordinary data visualization scenarios will not be too challenging for you, such as the chart below ⬇
This image, created using global low-order geoid data at high latitudes, features a reasonable color scheme that allows readers to quickly and intuitively understand the information being conveyed. Such a chart can impressively enhance presentations or academic papers.It is well-known that Python is a highly sought-after programming language in recent years, one that can help you secure multiple job offers once you learn it. In fact, Python also possesses powerful automation and data processing capabilities, boasts a vast library of free graphics and packages, supports personalized graphic creation, and even provides more opportunities and advantages for researchers in the upcoming era of artificial intelligence.
Such a powerful tool is likely to attract more people who are interested in it than those who are willing to learn it. Fears of not being able to learn programming, concerns about the time required to get started, and the perception that data processing is cumbersome, etc., can lead us to continue to “observe” rather than make the decision to “invest.”
To overcome these difficulties and invest time effectively, we strongly recommend everyone to learn this course on Python Data Visualization, taught by a geophysics PhD who is skilled in data visualization and passionate about researching high-level journal paper illustration methods—the scholar Jiutian, who will guide you step by step from zero to using Python for data visualization in academic papers. This Python course, explained by research scholars, is grounded in research scenarios and does not overly emphasize complex programming, making it easier for researchers to get started and master.Recently, the instructor added 4 new Python data visualization examples. This update also explains some new auxiliary drawing software, combining various types of graphic elements and interacting with some third-party libraries. The difficulty has increased, but the entire tutorial is easy to understand and beginner-friendly, allowing you to easily acquire new skills!
Why Use Python for Data Visualization?
1. High Efficiency and High Quality Python can achieve an effective workflow that integrates data processing and chart creation; it also supports outputting high-quality vector graphics and various formats required by journals. 2. Personalized Editing Freedom Python can freely and quickly visualize data according to the user’s personalized needs; given Python’s open-source and free nature and ease of use, it has a vast library of free functions and resources, allowing users to easily find similar codes and modify them as needed to meet various personalized requirements. 3. Easy to Get Started Python’s syntax is concise and intuitive, with strong readability and a low threshold for entry; mastering some basic syntax can open the door to Python data visualization. 4. Lightweight Files The files in the data visualization process only need to be recorded as text files, making it easy to manage and save various program codes, configuration files, and documentation (this is what is known as “version control”). The following images are all illustrations created using Python by the scholar Jiutian, who has 8 years of experience in Python visualization:
The stunning illustrations above are just a small showcase of the capabilities of Python visualization tools. I believe that in the future, we will increasingly see various experts showcasing their skills using Python data visualization tools in high-level journals.
Now, let’s learn the course Python Data Visualization taught by Dr. Jiutian, who has 8 years of Python experience. Jiutian will guide you step by step in coding, helping zero-based learners get started and improve, achieving progress from “zero” to advanced visualization skills; the course will detail the drawing methods for over 40 case images (some of which are selected from illustrations in high-quality published journal papers), combining theory with practice to help everyone master this “skill” of Python visualization.Python drawing, achieve high-scoring SCI!
Five Learning Modules | 40+ Cases | Step-by-Step Coding
Limited Time Offer: 269 Yuan
Course Price: 359 Yuan
Activity Time: July 17-22, 2024
Click the card below for details ▼▼▼
Course Preview
(Preview video) Recommended to watch on Wi-Fi*Friendly Reminder: Due to WeChat’s video size limit, this video is a compressed version. To view a clearer version of the preview lesson, you can click the mini-program card to watch more “preview lessons” in the course directory!
Target Audience
● Researchers who wish to improve the quality of their research illustrations● Those with no foundation in Python visualization and those hoping to advance● Python data visualization enthusiasts
Course Features
In-depth and Easy to Understand | Start from basic knowledge and gradually increase the course difficulty, making it effortless for beginners;Easy to Get Started | The instructor personally codes step by step, helping you understand the meaning of each line of code to quickly get started;High Quality and Practical | The course uses top journal illustrations as case studies, combining practical explanations for strong applicability;Learn and Practice | Each section leaves room for exercises and code, helping students consolidate what they have learned;
Python drawing, achieve high-scoring SCI!
Five Learning Modules | 40+ Cases | Step-by-Step Coding
Limited Time Offer: 269 Yuan
Course Price: 359 Yuan
Activity Time: July 17-22, 2024
Click the card below to view the course ▼▼▼Class Location: Mugge Classroom WeChat Official AccountCourse Format: Recorded course, learn anytimeConsult Teaching AssistantWeChat of the assistant: mugexuemei
(Assistant working hours: Monday to Friday 9:00-18:00)
