ai buzzwords come and go, new machine learning trends explode and fade, but some things remain consistent, and one of them is the narrative power of good data visualization.
Presenting data-backed insights through visual means remains a critical skill for data professionals, and we love exploring the essential details that make charts, diagrams, and infographics come together. We find it equally valuable to delve into the fundamentals as well as staying up to date with recent tools and novel approaches. This week we feature some great articles that cover the entire spectrum between these poles: If you were planning to deepen and broaden your visualization skills in 2024, you're in the right place. Let us begin.
- Visualization 101: Choosing the best visualization type
A solid foundation in design strategy is key when it comes to creating effective images. Maria MansurovaGoogle's playbook on different data visualization use cases and how to adapt your approach based on your end goals is as solid a resource as you'll find if you're taking your first steps into this domain. - Declarative versus imperative layout
The path from a gorgeous vision in your head to the final product on your screen is filled with numerous intermediate steps, many (if not most) of which come in the form of code. Lee VaughanThe explanation of how plotting works in Python is essential reading for anyone who wants to understand what visualization tools look like inside and how to choose the right one accordingly.
- Viewing Everest Expeditions
For a generous dose of visual inspiration, don't miss Karla HernandezThe step-by-step tutorial, which guides us through the entire process of creating an elegant, multi-layered and highly effective infographic. The topic at hand may be mountaineering, but the principles Karla describes are valuable regardless of the project she is working on. - Viewing routes on interactive maps with Python: Part 1
Apps like Google Maps have been ubiquitous for so long that we almost take them for granted; Carlos J. UribeThe practical guide highlights the complexity behind creating maps, but also shows that visualizing rich geospatial data is within reach if the right tools are used in a simplified way.
