Visualizations in notebooks
Use visualizations in your notebooks to present data visually to help identify patterns, gain insights, and make decisions.
Many of your favorite open source visualization libraries, such as matplotlib, are pre-installed on Watson Studio. All you have to do is import them. See Import preinstalled libraries and packages.
You can easily install other visualization libraries and packages. See Install custom or third-party libraries and packages.
You can use these IBM visualization libraries and tools:
- PixieDust helper library: Create graphs with a one-word command and then explore them with an integrated UI instead of code. Run Scala code within Python notebooks. Try in a notebook.
- Brunel: Create interactive graphs with simple code. Try in a notebook.
- SPSS models: Create interactive tables and charts to help you evaluate and improve a predictive analytics model created with SPSS machine learning algorithms. Try in a notebook.
You can use the following visualization libraries in Scala notebooks: