/7.2/guide-tags/visualization/Recent content in Visualization on Kinetica DocsHugo -- gohugo.ioen/7.2/guides/quickstart-guide/Mon, 01 Jan 0001 00:00:00 +0000/7.2/guides/quickstart-guide/Install Kinetica There are several different options for installing Kinetica Enterprise or Kinetica in AWS. However, to get started within minutes (and for free) we recommend either of the following two routes: Kinetica Cloud Free: This is a free managed version with 10 GB of storage, which is hosted in the cloud. Follow the instructions for Kinetica Cloud Free to create an account and launch Kinetica. Tip Kinetica Cloud takes only a couple of minutes to set up and is an excellent choice to get started./7.2/guides/isochrones/Mon, 01 Jan 0001 00:00:00 +0000/7.2/guides/isochrones/The following is a complete example, using the Python API, of generating images containing isochrones via the /visualize/isochrone and /wms endpoints using an existing graph. Prerequisites Python API Installation Python Virtual Environment PyPI Git Data File Script Detail Connections Constants Graph Creation Visualizing Isochrones Visualizing Isochrones Using WMS Download & Run Prerequisites The prerequisites for running the isochrones example are listed below: Graph server enabled Python API Isochrones example script DC Shape data CSV file Python API Installation Depending on the target operating system, a Python virtual environment may need to be installed first:/7.2/guides/graph_video_guide/Mon, 01 Jan 0001 00:00:00 +0000/7.2/guides/graph_video_guide/In this video series, Hari Subhash walks through graphs in Kinetica, from high-level concepts to practical examples./7.2/guides/jupyterlab/Mon, 01 Jan 0001 00:00:00 +0000/7.2/guides/jupyterlab/Introduction Prerequisites Docker Install Setting Permissions Entering the License Key Pulling the Image Managing the Container Starting Using Stopping Exploring the Environment JupyterLab Contents Mounted Volumes Example Notebooks SVD Recommender and Visualization Example KJIO Utility Library Conclusion References Introduction JupyterLab is an integrated environment that can streamline the development of Python code and Machine Learning (ML) models in Kinetica. Jupyter notebooks integrate code execution, debugging, documentation, and visualization in a single document for consumption by multiple audiences.