Matplotlib
Matplotlib is the grandfather of python visualization packages. It is extremely powerful but with that power comes complexity.强大但相对复杂
Seaborn
Seaborn is a visualization library based on matplotlib. It seeks to make default data visualizations much more visually appealing. It also has the goal of making more complicated plots simpler to create. It does integrate well with pandas.和pandas完美配合，使可视化更引人注目，而且简单几步便可绘制复杂图形。
ggplot
ggplot is similar to Seaborn in that it builds on top of matplotlib and aims to improve the visual appeal of matplotlib visualizations in a simple way. It diverges from seaborn in that it is a port of ggplot2 for R. Given this goal, some of the API is non-pythonic but it is a very powerful
Bokeh
Bokeh is different from the prior 3 libraries in that it does not depend on matplotlib and is geared toward generating visualizations in modern web browsers.不同于前三种，不是基于matplotlib，用于web浏览器上的可视化工具。
Pygal
Pygal is used for creating svg charts. If the proper dependencies are installed, you can also save a file as a png. The svg files are pretty useful for easily making interactive charts. I also found that it was pretty easy to create unique looking and visually appealing charts with this tool.画矢量图
Plot.ly
Plot.ly is differentiated by being an online tool for doing analytics and visualization. It has robust API’s and includes one for python. Browsing the website, you’ll see that there are lots of very rich, interactive graphs. Thanks to the excellent documentation, creating the bar chart was relatively simple.一款在线可视化工具，配套文档完善。