Best Data Visualization Software for Jupyter Notebook

Saturn Cloud is an AI/ML platform available on every cloud. Data teams and engineers can build, scale, and deploy their AI/ML applications with any stack.

Datameer is your go-to data tool for exploring, preparing, visualizing, and cataloging Snowflake insights. From exploring raw datasets to driving business decisions – an all-in-one tool.

Stata is a comprehensive, integrated software package that can handle all aspects of data science: data manipulation, visualization and statistics, as well as automated reporting. Stata is quick and accurate. The extensive graphical interface makes it easy to use, but is also fully programable. Stata's menus, dialogs and buttons give you the best of both worlds. All Stata's data management, statistical, and graphical features are easy to access by dragging and dropping or point-and-click. To quickly execute commands, you can use Stata's intuitive command syntax. You can log all actions and results, regardless of whether you use the menus or dialogs. This will ensure reproducibility and integrity in your analysis. Stata also offers complete command-line programming and programming capabilities, including a full matrix language. All the commands that Stata ships with are available to you, whether you want to create new Stata commands or script your analysis.

A simple-to-use interactive tool that allows data exploration, analysis, visualization and machine learning. Cloud Datalab is an interactive tool that allows you to analyze, transform, visualize, and create machine learning models on Google Cloud Platform. It runs on Compute Engine. It connects to multiple cloud services quickly so you can concentrate on data science tasks. Cloud Datalab is built using Jupyter (formerly IPython), a platform that boasts a rich ecosystem of modules and a solid knowledge base. Cloud Datalab allows you to analyze your data on BigQuery and AI Platform, Compute Engine and Cloud Storage using Python and SQL. JavaScript is also available (for BigQuery user defined functions). Cloud Datalab can handle megabytes and terabytes of data. Cloud Datalab allows you to query terabytes and run local analysis on samples of data, as well as run training jobs on terabytes in AI Platform.

Polly allows you to harness the power of biomedical information. The Polly Platform allows you to scale batch jobs, workflows and visualization applications. Polly supports resource pooling, optimizes resource allocation based upon your usage requirements, and makes use of spot instances when possible. This results in optimization, efficiency, quicker response time, and lower costs for resources. Access a dashboard that allows you to monitor and track resource usage and costs in real-time. This will allow you to reduce overheads when resource management is done by your IT team. Polly's infrastructure is built around version control. Polly uses a combination dockers and interactive notebooks to ensure version control for your analyses and workflows. We have created a mechanism that allows data, code, and the environment to co-exist. This, along with cloud data storage and the ability for users to share projects, ensures reproducibility in every analysis.