Seaborn Description
Seaborn is a versatile data visualization library for Python that builds upon matplotlib. It offers a user-friendly interface for creating visually appealing and insightful statistical graphics. To gain a foundational understanding of the library's concepts, you can explore the introductory notes or relevant academic papers. For installation instructions, check out the dedicated page that guides you on how to download and set up the package. You can also explore the example gallery to discover various visualizations you can create with Seaborn, and further your knowledge by diving into the tutorials or API reference for detailed guidance. If you wish to examine the source code or report any issues, the GitHub repository is the place to go. Additionally, for general inquiries and community support, StackOverflow features a specific section for Seaborn discussions. Engaging with these resources will enhance your ability to effectively use the library.
Seaborn Alternatives
JOpt.TourOptimizer
If you are developing software for Logistics Dispatch Solutions, which contain challenges:
-For staff dispatching, such as sales reps, mobile service, or workforce?
-For truck shipment allocation in daily transportation and logistics (scheduling, tour optimization, etc.)?
-For waste management and District Planning?
-Generally, highly constrained problem sets?
And your product does not have an automized optimization engine?
Then JOpt is the perfect fit for your product and can help you to save money, time, and workforce, letting you concentrate on your core business.
JOpt.TourOptimizer is an adaptable component to solve VRP, CVRP, and VRPTW class problems for any route optimization in logistics or similar fields. It comes as a Java library or in Docker Container utilizing the Spring Framework and Swagger.
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DXcharts
In just a few days, you can integrate and customize a lightning-fast financial table with your product. You can make changes or create a completely new interface. You want more? We offer a full access alternative. Data feeds with futures and indices, equities, FX and cryptocurrencies by default. Sign up now to get your data feeds. DXcharts can be integrated with any market data source, as it is data feed-agnostic. Native libraries for all platforms. Native web, native mobile & desktop. Get a solution that is specifically tailored to your product. Analyzing statistics from trading activity can help you evaluate securities and predict their future movements. You can create custom studies with the intuitive dxScript. You can adjust the layout of charts however you like and sync them by instrument, chart type and timeframe, range, studies & appearance.
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JMP Statistical Software
JMP, data analysis software Mac and Windows, combines powerful statistics with interactive visualization.
It is simple to import and process data. Drag-and-drop interface, dynamically linked graphics, libraries of advanced analytics functionality, scripting language, and ways to share findings with others allow users to dig deeper into their data with greater ease.
JMP was originally developed in 1980 to capture the new value of GUI for personal computers. JMP continues to add cutting-edge statistical methods to the software's functionality with every release. John Sall, the organization's founder, is still Chief Architect.
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ggplot2
ggplot2 is a framework for creating graphics in a declarative manner, drawing on the principles outlined in The Grammar of Graphics. Users supply their data and specify how to map variables to aesthetics and which graphical elements to employ, while ggplot2 manages the intricate details. Having been around for over a decade, ggplot2 is utilized by hundreds of thousands of individuals, resulting in the creation of millions of plots. This extensive usage typically means that ggplot2 itself remains relatively stable over time. When updates do occur, they are primarily aimed at introducing new functions or parameters rather than altering the functionality of pre-existing ones; any modifications to current behaviors are made only when absolutely necessary. For those who are just beginning their journey with ggplot2, it is advisable to seek out a structured introduction instead of attempting to learn by perusing isolated documentation pages, as this approach will provide a more comprehensive understanding of the system. Engaging with tutorials and resources designed for beginners can significantly enhance your learning experience.
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Company Details
Company:
Seaborn
Website:
seaborn.pydata.org
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
Customer Support
Online Support
Seaborn Features and Options
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