Python Visualizations & Animations

 

Python Visualizations & Animations

Python Visualization Tutorials

Data visualization is graphical representation of data.

This technique is used in pretty much every field in business because there is always some     type of   data or statistic to interpret.

You can see the big picture, as well as smallest details more conveniently with visualization.            It transforms numbers and relations to trends, colors, shapes and correlations.

Since programming is so powerful and it brings function and automation capabilities it makes sense that visualization is a big practice in Python also.

Data Visualization

Visualization is a term with multiple meanings. Although it refers to the similar phenomenon that     stimulates the same visual sensory in the brain, visualization can mean imagining something that’s currently not present. This usage is more common in psychology.

Visualization is often used to mean visualization of data in more technical or business related fields   such as coding, research, science, finance etc.

Data Visualization Examples

Visualization can be done in many forms using Python. The range can start from traditional     line, bar and scatter charts to more modern charts like hexbin and pcolor and even animated charts!

Stacked Chart Visualization Example with Python Matplotlib

You can find interesting tutorials about Python Animations like below in this visualization     series.

Hexbin Chart created with Matplotlib
Visualization with Pcolor Chart (Matplotlib)
We will demonstrate the usage of FuncAnimation function from matplotlib.animation        module to animate many different charts. Below you can see an animated line chart example.

Matplotlib Animations

Line Chart Animation (Matplotlib)

Plotly Tutorials with Python

Plotly is a very intuitive charting library in Python. It’s a very high level approach to beautiful visualizations but it can also be highly customized if need be.

Where Plotly truly shines is Plotly visualizations are really beautiful straight off the bat, it is open-source and also website friendly.

Map Chart Created with Plotly and Mapbox using Python

Thanks to native support of JavaScript technology Plotly outputs can be images, javascript or html making it 100% browser friendly.

How to Install Plotly

pip install plotly
or
pip3 install plotly
A simple visualization created with Plotly

Matplotlib Tutorials with Python

Matplotlib is a less high-level data visualization library but it can be the backbone                     of a sophisticated charting application because of its very detailed and adjustable nature.         But beware, low-level coding also means writing more code even for very basic             charting structures. Which can be very useful or painful depending on what you need.

In fact there are more user friendly libraries that are built on matplotlib for Python                     such as Seaborn which allows achieving very beautiful end results with very little code.

Matplotlib is known as the fundamental data visualization library for Python.

How to Install Matplotlib

Matplotlib is a native Python library so it doesn’t require separate installation.

Visualization Resources

For additional resources you can check out websites of main data visualization libraries.     Here are a few that come to mind:


No comments:

Post a Comment