Learn how to choose, design, and optimize data visualizations for 2D graphic design. Discover tips and examples to create visual stories that inform, persuade, and inspire.

2D image space methods are processing methods applied after the volumetric data are projected and rendered into the 2D image space, such as 2D filtering, tone mapping and compositing. In the ...

Matplotlib integrates seamlessly with other Python data science libraries like NumPy, scikit-learn, and pandas. Features: Supports 2D plotting, including line charts, scatter plots, bar charts, ...

Learn how to make the most of Observable JavaScript and the Observable Plot library, including a step-by-step guide to eight basic data visualization tasks in Plot.

It enables visualization of scalar, vector and tensor data in 2D and 3D. It can act as an alteranate to Matlab or Pylab for plotting and visualizing 3D data using NumPy via the mlab module. It can ...

Get trained to use our commercial 2D, 3D, and 4D visualization and analysis packages that support sophisticated and time-saving workflows for data quantification. Or, consult with us on general ...

Data visualization in VR and AR could be the next big use case for the technologies. It's early days, ... 2D scatter plots typically contain only two or three metrics.

2D image space methods are processing methods applied after the volumetric data are projected and rendered into the 2D image space, such as 2D filtering, tone mapping and compositing. In the ...