How about python for visual data analysis?

Of course it's good. As a widely used programming language, python's third-party libraries are rich in extensions and provide many efficient and simple data visualization packages, which can be used directly. Here I briefly introduce three of them, namely matplotlib, seaborn and pyecharts. Interested friends can try:

Old brand tool matplotlib

This is a very famous visualization tool in python. I believe that many friends who have done visualization are very familiar with matplotlib, which is professional, powerful, fully functional and rich in expansion. Almost all kinds of charts you can think of can be easily handled by matplotlib, from common bar charts, pie charts and line charts to complex animations, three-dimensional charts and custom charts. There are many kinds and complete codes. If you want to visualize the data and draw professional charts for display, you can use matplotlib, and the effect is very good:

Seaborn in compact package

This is also a very good python visualization package. Based on the development of matplotlib, the complex parameters and calls of matplotlib are simplified and encapsulated, which is more convenient to use and easier to use. Common scatter charts, graphs, bar charts, pie charts, heat charts, box charts and violin charts all involve depth. The demonstration is rich, the code is complete and the official tutorial is detailed. If you want to draw a professional and powerful picture quickly,

Easy to use pyelography

Friends who have used echarts should be very familiar with pyecharts. Python just encapsulates and calls echarts. With the powerful data visualization function of echarts, pyecharts can also easily draw various charts, common bar charts, pie charts, scatter charts, curves, complex maps, tree charts, K-line charts, dashboards, geographical maps, three-dimensional charts and so on. Pyelography is easy to do. It is professional, powerful, beautiful and easy to use. If you want to draw simple and generous charts and display them based on web pages, you can use pyecharts, and the effect is very good:

Now, let's share these three good python visualization libraries. In fact, there are many other bags that can be used directly, such as ggplot and bokeh, which are also very good. As long as you have a certain python foundation and are familiar with relevant codes and examples, you will soon be able to master it. There are also related tutorials and materials on the Internet, which are very detailed. You can search if you are interested. I hope the content shared above is helpful to you. You are also welcome to comment on the message.