How Does Data Visualization Work With Python Using Matplotlib?

Data visualization’s primary role is to help non-technical people consume and understand large quantities of data. When presented properly, it helps draw actionable conclusions more easily and readily.

Matplotlib is the most popular Python module (or library) to make plots and visualizations. Since it’s the first ever Python visualization library, a number of other visualization tools are built and extended from it, for example, Seaborn, Astropy, mplfinance, PyART, etc.

Not every decision-maker in an organization has the necessary technical skills to understand vast amounts of data. Data visualization, therefore, helps leaders make more informed decisions to further their organizations’ progress.

Matplotlib is a collection of different visualization functions that work like MATLAB under the hood.

Python has an extensive collection of data visualization tools with domain-specific packages like Seaborn for statistical graphics, Cartopy for geospatial data processing, DNA features viewer, WCSAxes for plotting astronomical data, etc.

Python is the go-to programming language for any type of data analysis since it’s easy to learn and fast to implement. The Python script is intuitive and easy to read which makes it the best choice for a visualization tool.