Here it is described how Google Chart fits better than Matplotlib in some situations.Matplotlib, as its name say, comes from Matlab, so the syntax is also very similar. However, it arises from the need to represent data within a Python environment in a few lines of code. The pyplot API is used to create the figures and everything works with the integration of the matplotlib library.
Most Python users are used to representing data with Matplotlib.
“Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.”
Matplotlib, as its name say, comes from Matlab, so the syntax is also very similar. However, it arises from the need to represent data within a Python environment in a few lines of code. The pyplot API is used to create the figures and everything works with the integration of the matplotlib library. Using Matplotlib is the simplest way when the data is produced by a Python script and needs to be represented instantly on a single machine.
However, there are some situations in which it is necessary to represent the results within a web page, in a static or even dynamic way. In this way interaction with the viewer is also facilitated, since he will only have to access a certain domain from his browser. Integrating Matplotlib into a page written in HTML is achievable, but there is a better alternative and it is called Google Chart.
A Web service is an application capable of making machines communicate via the HTTP protocol. For this, as we said before, with Google Chart you have the possibility to provide visualizations to anyone through HTML pages.
Data visualization is the graphical representation of data in a graph, chart or other visual formats. It shows relationships of the data with images.
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So here is my first blog regarding the data visualization with matplotlib in python. In this article we will cover the basic of the visualization with matplotlib.