Python: Visuals

Intro

Python is considered a great programming language due to the ease of access and use for new programmers. As part of this easy use, python has access to a plethora of aids to help programmers visualize their code, particularly regarding data visuals.

What's a Data Visual?

Some readers may think that data visuals would be things like a webpage or maybe even the console printouts as a way to see a programmer's code. However, data visuals in this article refer to visuals like graphs (line, bar, etc...) or information charts.

Why Use Data Visuals?

Now, some beginner programmers may wonder why a little graph would be helpful to visualize data and the answer to that is quite simple. Oftentimes a programmer is going to have variables that do not have hard-coded values or have variables that will change over the code's runtime. With these cases it is difficult to mentally process what these values should be or what these values would be at a specific point, which is where data visualizations come into play. Using a graph can be a great way to track how a value changes over time by providing a nifty image for a programmer or even a non-programmer to get data from. For example:

counter = 0
output = []
while counter < 10:
  counter += 1
  if counter % 2 == 0:
    output.append(counter * 2)
  else:
    output.append(counter * -2)
#What values will output have?

This example could likely be figured out with a little bit of work, but what about if the counter went until 20? Or 50? 100? What if the appended value had more complicated conditions or simply more conditionals to go through different operations? Tracking what each value is would be a nightmare that no console statement would help with simply because there is too much to sort through at that point. However, with a graph the code above can be seen as so:

(graph generated using the matplotlib module)
With this handy line graph it is now much easier to see how the values change with each iteration. This visual is very simplistic compared to most but it still shows information that can be useful to understanding the code values.

Visual Modules

Python can provide data visuals through some of its modules. The uses and complexity of these modules differs, VPython simply provides visuals related to 3-dimensional shapes whereas matplotlib is oriented to more 2-dimensional charts and graphs (though it does possess some 3-d graphs) that can be customized greatly.

Visual Programs

Another way to get visuals in python is through various coding applications and their add-ons. One example of this is Visual Python, an add-on for Jupyter Notebook (a python coding suite) that allows users to plug in modules and data examples into a file of code and show the results in tables and the like.

Closing

Python has access to many different data visuals that help programmers understand data within pieces of code. Whether it is through a module or an app's program, data visuals are an incredibly useful asset for any programmer.

useful Links

Matplotlib website
List of Commonly used visuals
Vpython documentation
Visual Python