Alternatives to Seaborn

Matplotlib is a Python library that allows you to create interactive, animated, or static visualizations. Matplotlib makes difficult things simple and easy. Many third-party packages extend and build upon Matplotlib functionality. These include several higher-level plotting interfaces such as seaborn, HoloViews and ggplot.

Software requirements are growing exponentially but your team's ability to meet them is not. Qt 6's APIs and tools allow developers and designers to create more. You can create consistent branded 2D and 3D applications with a native or custom look & feel using developer-friendly tools, a lighter, but more powerful QML language and a flexible graphics structure. Qt 6 and its vast ecosystem offer everything you need to develop, design, and deploy software for all your product lines, from microcontrollers (MCUs), to supercomputers. With the same codebase, you can create applications that are both beautiful and powerful in the front end. Qt Group is a global company that develops software for over 70 industries. It is the technology behind more than 1+ billion applications and devices. Global companies and developers around the world use Qt.

Scapy is an interactive packet manipulation program. It can forge and decode packets from a variety of protocols, send them over the wire, capture them and match requests and responses. It can handle most of the classic tasks such as scanning, tracerouting and probing, attacks, or network detection (it can replace Hping, 85% nmap, arpspoofsk, arping), tcpdumpshark, p0f and tshark). It can also handle a lot more specific tasks than most other tools, such as sending invalid frames, injecting 802.11 frames, combining technologynics (VLAN hopping+ARP caching poisoning, VOIP descoding on WEP encrypted channel), and so forth. Scapy works natively on Linux and Windows as well as OSX and most Unixes that have libpcap. The same code base runs natively on Python 2 and Python 3 Scapy development uses Git version control system. The GitHub repository hosts the Scapy reference repository.

ggplot2 allows you to create declarative graphics using The Grammar of Graphics. You provide the data and tell ggplot2 what graphical primitives you want to use. ggplot2 has been around for over 10 years and is used by thousands to create millions of plots. This means that ggplot2 itself is relatively stable. If we do make any changes, it will be to add functions or arguments to existing functions rather than to change the behavior of existing ones. If we do make changes to existing behavior, we will do so for compelling reasons. It is better to start with a systematic introduction to ggplot2 than to read individual documentation pages.

Requests is an elegant and simple HTTP library. Requests makes it easy to send HTTP/1.1 queries. You don't need to manually add query strings or form-encode your PUT and POST data to your URLs. Instead, you can use the JSON method. Requests is the most downloaded Python package today, pulling in approximately 30M downloads per week, according to GitHub. Requests is currently dependent upon 1,000,000+ repositories. This code is certainly worth your trust. PyPI has Requests. Requests is available to meet the demands of building reliable and robust HTTP-speaking applications for today's needs. Automated content decompression and decoding. International URLs and domains. Sessions with cookie persistence. Browser-style TLS/SSL verification. Basic and digest authentication, as well as familiar dict-like cookies. Multi-part file uploads. SOCKS proxy support. Connection timeouts and streaming downloading.

PyQtGraph is a pure Python graphics and GUI library based on PyQt/PySide or NumPy. It is intended for use in mathematics/scientific/engineering applications. Although written entirely in Python, the library is extremely fast thanks to its heavy use of NumPy to perform number crunching and Qt GraphicsView framework for fast display. PyQtGraph is available under the MIT open source license. Interactive view boxes for basic 2D plotting. Line and scatter plots. Data can be scaled/panned with the mouse. Rapid drawing allows for real-time data display. Displays all data types (int, float, any bit depth, RGB, RGBA or luminance). Multidimensional images can be sliced at arbitrary angles using these functions (great for MRI data). Rapid update for video display and real-time interaction Image display with interactive level control and lookup tables. Mesh rendering with isosurface generator. Interactive viewports can be rotated/zoomed with the mouse. For easier programming, use the basic 3D scenegraph.

WebDataRocks, a free JS library that creates functional pivot tables with ease of use, is a simple and straightforward JS library. It can be used in conjunction with Angular Vue React or other frameworks. Free Customization is flexible JavaScript client-side component Loads up to 1MB of JSON and CSV data files Enterprise features in full Integration with third party charting libraries Enterprise features in full For efficient data management, you can use features like filtering and sorting, number formatting, conditional formatting, calculated values and totals. It allows you to print or export web reports in PDF, Excel, or HTML by using just one click. Modern UI ready-to-use The tool has a spreadsheet-like interface that is optimized for both browsers and mobile apps. This web reporting tool already incorporates all the principles of reliability and an excellent user experience.

Dash & Dash Enterprise allow you to build and deploy analytic web applications using Python, R, or Julia. No JavaScript or DevOps are required. The world's most successful companies offer AI, ML and Python analytics at a fraction of the cost of full-stack development. Dash is the way they do it. Apps and dashboards that run advanced analytics such as NLP, forecasting and computer vision can be delivered. You can work in Python, R, or Julia. Reduce costs by migrating legacy per-seat license software to Dash Enterprise's unlimited end-user pricing model. You can deploy and update Dash apps faster without an IT or DevOps staff. You can create pixel-perfect web apps and dashboards without having to write any CSS. Kubernetes makes it easy to scale. High availability support for mission-critical Python apps

Gevent is a Python networking library that uses coroutine. It uses greenlet to provide an API for high-level synchronous APIs on top of the event loops libev and libuv. Gevent is inspired by Eventlet, but has a more consistent API and simpler implementation. It also offers better performance. See why gevent is used by others and see the list of open-source projects that are based on gevent.

CVXOPT, a free software package that allows convex optimization using the Python programming language, is available for download. It can be used with Python's interactive interpreter, the command line to execute Python scripts or integrated into other software via Python extension module. Its primary purpose is to simplify the development of software for convex optimization by using Python's extensive standard library as well as the strengths of Python, a high-level programming languages. Efficient Python classes that can handle dense and sparse (real and complicated) matrices. Includes Python indexing, slicing, and overloaded operations for matrix mathmetic. Interfaces to the linear programming solution in GLPK, semidefinite programming solvers DSDP5 and linear, quadratic, and second-order cone programming solutions in MOSEK.

urllib3 is a powerful and user-friendly HTTP client that Python uses. You should use urllib3 as a client for your Python environment. Many critical features are missing from the Python standard library, and urllib3 provides them. Thread safety, connection pooling and client-side SSL/TLS verification. Multipart encryption is used for file uploads. Helpers for dealing with HTTP redirects and retrying requests. Support for deflate, gzip, and brotli encryption. Proxy support for HTTPS and SOCKS. 100% coverage of the test. urllib3 is one the most downloaded Python packages. It is a dependency on many popular Python packages such as Requests, Pip and more! urllib3 is available under the MIT License. API Reference documentation provides API-level documentation. The User Guide explains how to use the library to accomplish common tasks. For lower-level tweaking, the Advanced Usage Guide is a more detailed guide.

Implementation of the WebSocket Protocol. RFC 6455 & RFC 7692. websockets is an open-source library that allows you to build WebSocket clients and servers in Python. It focuses on correctness and simplicity, robustness and performance. It is built on top of Python's standard asynchronous I/O framework asyncio and provides an elegant coroutine-based API. websockets has been rigorously tested to ensure compliance with RFC 6455. Continuous integration fails below 100% branch coverage. websockets was designed for production. It was the first library to correctly handle backpressure before the issue became well-known in the Python community. Memory usage is optimized and configurable. C extensions accelerate expensive operations. It is pre-compiled for Linux and macOS and packaged in the wheel format according to each Python version. websockets handles everything so you can concentrate on your application.

Properties allow you to access all URL parts, such as scheme, user password, host, path, query, path, port, and password. All URL manipulations result in a new URL object. Strings passed to constructor or modification methods are automatically encoded and give canonical representations as a result. Regular properties are percent-decoded. To get encoded strings, you can use raw_ versions. As.human_repr(), URLs can be represented in a human-readable format. PyPI has binary wheels for Linux and MacOS. You can use the tarball to compile yarl from the source code if you want to install it on another operating system (such as Alpine Linux, which isn't manylinux-compliant due to the missing glibc). It requires Python headers and a C compiler. The pure-Python version (uncompiled) is slower. PyPy uses a pure Python implementation and is therefore unaffected by this variable.

The Python multi-platform windowing and multimedia library. pyglet, a powerful and easy-to-use Python library, allows you to create games and other visually rich applications on Windows, Mac OS X and Linux. It supports windowing, user event handling, Joysticks and OpenGL graphics. It also supports loading images and videos. This is all done with a friendly Pythonic API that's easy to use and doesn't get in the way. pyglet is available under the BSD open source license. This allows you to use it for commercial and open-source projects without restriction. No external dependencies or installation requirements. pyglet doesn't require any additional Python to meet most application or game requirements. This simplifies distribution and installation. This makes it easy for you to package your project using freezers like PyInstaller. pyglet offers real platform native windows that allow you to use multiple windows and multi-monitor desktops.

gTTS (Google Text-to-Speech) is a Python library and CLI to interface with Google Translate’s text-to-speech API. For further audio manipulation or to write spoken mp3 data to files, you can use bytestring (file-like object) or stdout. You can also pre-generate Google Translate request URLs to feed an external program. A speech-specific sentence tokenizer that can be customized to allow for unlimited text lengths, while maintaining proper intonation, abbreviations and decimals. You can also make pronunciation corrections with custom-designed text pre-processors.

DHTMLX is a powerful and easy-to-use JavaScript UI library that provides a wide range of customizable and flexible components for building modern and responsive web applications. It offers 30+ full-featured UI widgets, including grids, charts, diagrams, schedulers, gantt charts, calendars, trees, forms, and more. These components are optimized for fast rendering, ensuring that your application runs smoothly in all browsers and devices. DHTMLX is compatible with popular web frameworks such as React, Angular, and Vue.js. This makes it an excellent choice for developers who are already working with these frameworks and want to add a powerful UI library to their projects. Moreover, DHTMLX supports different data sources and formats, making it easy to integrate with various back-end technologies. DHTMLX provides extensive configuration and customization abilities for its UI components, allowing developers to tailor their appearance and behavior to meet specific application requirements and extend its functionality with custom features if needed. DHTMLX also has comprehensive documentation that covers every aspect of the library, including detailed API references, tutorials, and code examples, as well as an active community.

List & Label is a reporting tool made for software developers which adds powerful report functions to your application. Itis the preferred reporting component used by thousands worldwide software development teams. List & Label supports a huge variety of data sources, is seamless to integrate and extends applications with convenient print, export and preview functions. The reporting tool is made for development environments such as .NET, C#, Delphi, C++, ASP.NET, ASP.NET MVC, .NET Core etc. The WYSIWYG Report Designer in Office Look & Feel is included in all editions. It helps developers and end users to create flexible reports and dashboards the way they like it. The additionally included and entirely browser-based Web Report Designer for ASP.NET MVC offers more flexibility in development and is independent from printer drivers. Reports for web applications can be designed anywhere at any time in the browser of your choice. List & Label is "Made in Germany" by combit.

The ROOT data analysis framework can be used extensively in High Energy Physics (HEP). It also has its own output format (.root). ROOT can be interfaced with C++ software. pyROOT is a Python software tool. Unfortunately, pyROOT is not compatible with python3.4. broot is a small library which converts data from python numpy to ROOT files. These ROOT files contain trees with a branch each array. This library provides a generic way to convert python numpy datastructures into ROOT files. The library should be portable, and it should support python2, ROOT v5 or ROOT v6 (no modifications to the ROOT part required). The library should be easy to install. Users will only need to compile the library once.

Altair Engineering, Inc. is not affiliated with the Vega-Altair open-source projects. Altair's API is easy to use, consistent, and friendly. It is built on top VegaLite's powerful visualization grammar. This simple design produces beautiful and efficient visualizations with minimal code. The idea behind linking data columns to visual encoding channels is the key. All other details of the plot are handled automatically. This declarative plotting idea allows for a surprising variety of plots and visualizations. It is possible to create them using relatively simple grammar.

ActiveReports is a complete reporting tool for.NET. With our intuitive Visual Studio integrated reporting designer and rich controls, you can create beautiful reports. - Feature-packed reporting for WinForms and WPF, ASP.NET Core, MVC,.NET Core and.NET Core 3 End User Report Designers, Web and Desktop - Dynamic reporting via flexible API and expressions Multiple report types available to suit all reporting needs Export formats available in 10+ formats What's new in ActiveReports. NET v15.1: - Section report deployment of Linux with.NET Core or.NET 5 - Custom font resolution JSViewer Performance Improvement - PDF/UA Enhancements - Chart Enhancements Extended Page Break properties - Dynamic Column Width What's new in ActiveReports version 2.0: RichText support allows you to display dynamic HTML content. Angular, Vue, and React Designer Components - Designer enhancements Guide to Authoring Revised Reports

Beautiful Soup is a library that allows you to easily scrape information from web pages. It sits atop an HTML/XML parser and provides Pythonic idioms to iterate, search, and modify the parse tree. Beautiful Soup's support of Python 2 was terminated on December 31, 2020, one year after the sunset date. New Beautiful Soup development will now exclusively target Python 3. Beautiful Soup 4's final release to support Python 2 was 4.9.3. Beautiful Soup is licensed under MIT license. You can download the tarball and drop the bs4/ directory in almost any Python program (or into your library path), and then start using it immediately.

The Python Imaging Library provides image processing capabilities for your Python interpreter. This library supports many file formats, an efficient internal representation, as well as powerful image processing capabilities. The core image library allows for quick access to data stored only in basic pixel formats. It should be a solid foundation for an image processing tool. Tidelift subscribers can get Pillow for Enterprise. The Python Imaging Library is perfect for batch processing and image archival applications. The library can be used to create thumbnails, convert file formats, and print images. The current version can identify and read a wide range of formats. The most common interchange and presentation formats are the only ones that support writing. The library includes basic image processing functionality such as point operations, filtering using a set of convolution kernels and color space conversions.

Openpyxl is an open-source Python library that can read/write Excel 2010 files xlsx/xlsm/xltx/xltm. It was created because there wasn't an existing library that could natively read/write Python in the Office Open XML format. Openpyxl was originally built on PHPExcel. All credit to the PHPExcel team. Openpyxl doesn't guard against quadratic blowup attacks or billion laughs XML attacks by default. Defusedxml can be installed to protect against these attacks. Install openpyxl with pip This should be done in a Python virtualenv with no system packages. Sometimes, you may want to work with a particular version's checkout. This could be true if bugs have been fixed, but no release has been made. To get started with openpyxl, you don't need to create a file in the filesystem. Simply import the Workbook class to get started. When a sheet is created, it automatically gives it a name. You can give a worksheet a name to make it a key in the workbook.

Imageio is an image library written in Python that allows you to easily read and write a variety of image data including animated images, volumetrics data, and scientific formats. It runs on Python 3.5+ and is cross-platform. Imageio is written entirely in Python, making it easy to install. Imageio is compatible with Python 3.5+. It works with Pypy. Imageio is dependent on Numpy, Pillow. For some formats, imageio needs additional libraries/executables (e.g. Imageio can help you download/install ffmpeg. You need to know where to look for the causes of problems if something doesn't work. This overview will help you understand how things work and where they might go wrong.

Ruffus is a Python computation pipeline library. It is open-sourced and powerful, user-friendly, and widely used for science and bioinformatics. Ruffus was designed to automate scientific and other analyses with minimal fuss and effort. It is suitable for even the most basic tasks. Even complex pipelines can be handled. This will prevent make or scons from becoming cross-eyed and recursive. No "clever magic", no pre-processing. The lightweight syntax, which does one small thing well, is unambitious. Ruffus is licensed under the permissive MIT-free software license. This license allows for free use and inclusion in proprietary software. It is a good idea to run your pipeline in a temporary directory that is not connected to your original data. Ruffus is a lightweight Python module that can be used to build computational pipelines. Ruffus requires Python 2.6 and higher, or Python 3.0 and higher.

Cryptography can include both high-level instructions and low-level interfaces for common cryptographic algorithms like symmetric ciphers and message digests. Use cryptography's high level symmetric encryption recipe to encrypt. Cryptography can be broadly divided into two levels. One that uses safe cryptographic recipes and requires very few configuration options. These are safe and simple to use, and don't require developers make many decisions. The second level is low-level cryptographic primitives. These can be dangerous and could be misused incorrectly. These require the ability to make decisions and have a deep understanding of cryptographic concepts. This layer is known as the "hazardous materials" (or "hazmat") because of the danger involved in working at this level. These materials live in the cryptography.hazmat packaging, and their documentation will always include an admonition at its top.

Pygame is a collection of Python modules that can be used to create video games. Pygame is an extension of the SDL library. This allows you create full-featured games and multimedia programs using the python programming language. Pygame is portable and can be used on almost every platform and operating system. Pygame is completely free. Pygame is free and open-source. You can use it to create commercial, freeware, shareware, or open-source games. Dual-core CPUs are common and 8-core CPUs easily available on desktop systems, multi-core CPUs allow you to do more with your game. Select pygame functions will release the dreaded Python GIL. This is something you can do with C code. Optimized C and assembly code are used for core functions. C code is often 10-20x faster than Python code, while assembly code can easily be 100x faster than Python code. It is compatible with many operating systems. You just need to apt-get or emerge.

Python-sql allows you to create SQL queries in a pythonic manner. Select with where condition, simple selects Select with multiple joins or with join. Select with group_by or select with the output name Select with order_by or sub-select. Select another schema and insert query using default values. Insert query with query and values. Update query with values. Update query with where condition. Update query with from list. Delete query with where condition and delete query using sub-query. Provides limit style and qmark style as well as numeric style.

WTForms allows you to easily validate and render forms for Python web development. It works with any web framework or template engine. It supports data validation, CSRF Protection, Internationalization (I18N), among other features. There are many community libraries that allow for closer integration with popular frameworks. WTForms strives to make APIs as easy as possible. WTForms can be used by a variety of libraries. However, if a library is not listed it doesn't necessarily mean it won't work. Any ORM or object-DB should be able to work as long as they allow access to members via data objects. WTForms uses unicode string throughout the source code. It assumes that input to forms has been forced to unicode by your framework. WTForms fields default to unicode strings. As long as your templating engine is capable of handling that, you should not have unicode issues.

statsmodels is an Python module that provides classes, functions, and methods for the estimation of various statistical models. It also allows for statistical data exploration and statistical tests. Each estimator has a comprehensive list of available result statistics. To ensure accuracy, the results are compared to existing statistical packages. The package is available under the Modified BSD (3 clause) license. statsmodels allows you to specify models using R-style formulas or pandas DataFrames. To see the available results, take a look at dir (results). Results describe attributes. __doc__, results methods have their own documentation strings. Numpy arrays can be used in place of formulas. Installing statsmodels as part of the Anaconda distribution is the easiest way to do so. This cross-platform distribution allows for data analysis and scientific computing. This is the preferred method of installation for most users.

python_docx is a Python library that allows you to create and update Microsoft Word (.docx), files. Word's fundamental structure is the paragraph. They are used for body text as well as headings and list items such bullets. Although you can specify width and height, it is not recommended. If you only specify one, python docx uses it for the correct scaled value of both. This ensures that your image doesn't look stretched and preserves the aspect ratio. You should learn what a Word paragraph format is. It allows you to apply multiple formatting options to a paragraph at a time. Python-docx can be used to create new documents and make changes to existing documents. It only allows you to make changes to existing documents. However, if you start with a blank document, it may feel like you are creating one from scratch.

IMSL numerical libraries can improve performance and reduce development time. IMSL's tools allow you to achieve your strategic goals. Your IMSL library can be used to model regression, create decision trees, build neural networks, forecast time series, and make decisions. The IMSL C Numerical Library has been proven reliable and robust across all industries. It provides companies with a high-ROI solution to building cutting-edge analytics tools. The IMSL C Numerical Library is able to quickly add sophisticated functionality to your analytic applications, including data mining, forecasting, and advanced statistical analysis. Integration and deployment are easy with the IMSL C library. Easy migrations, support common platforms and combination of platforms, and no additional infrastructure to embed in applications or databases, all possible with the IMSL C library.

The NumPy vectorization and indexing concepts are fast and flexible. They are the current de-facto standard in array computing. NumPy provides comprehensive mathematical functions, random numbers generators, linear algebra routines and Fourier transforms. NumPy is compatible with a wide variety of hardware and computing platforms. It also works well with sparse array libraries, distributed, GPU, or GPU. NumPy's core is C code that has been optimized. Enjoy Python's flexibility with the speed and efficiency of compiled code. NumPy's high-level syntax makes it easy for programmers of all backgrounds and experience levels. NumPy brings the computational power and simplicity of languages such as C and Fortran into Python, making it a language that is much easier to learn and to use. This power is often accompanied by simplicity: NumPy solutions are often simple and elegant.

Material Design Lite (MDL), a collection of components for web developers, is based on Google’s Material Design Philosophy. It's a visual language for users that combines the traditional principles of good design with technology and science. To properly use the Material Design Lite components, it is important to understand the goals and principles behind Material Design. Before you attempt to use the components, you should read the Material Design Introduction. You must use a browser that supports dialog elements in order to use the dialog component. At the time of writing, only Opera and Chrome have native support. Other browsers will need to either include the dialog polyfill, or create your own. Once you have dialog support, create a dialog element. When using the polyfill, the element must be a child element of the body element. Add a content element to that container with the class mdl–dialog content.

The library has been completely rewritten in Typescript/ES6 since v1.0.0. The old and massive jQuery plugin is gone. The library's core is now very small thanks to the plugin-based architecture. Everything else is built around a plugin. Every file in the dist/css or dist/js folders contains two versions: the original code in.css or.js files and the minified code within the.min.css or.min.js. files. You should use the.min.css and.min.js files on your production website to speed up page loading times and improve the user experience. To debug the code faster, you can use the normal files in development mode.

Waiting is a small library that waits for things to happen. It simply waits for a function in various modes to return True. Flux can be used to simulate timelines. Waiting is compatible. When you have a function that you need to wait for, waiting is the most basic use. It is easy to wait forever. If your predicate returns value, it will be returned by wait(). You can also specify a timeout parameter. An exception is made if the timeout expires and the predicate has not been fulfilled. The predicate is polled at a specified interval (default 1 second). You can change the interval with the sleep_seconds argument. Waiting provides two simple options to aggregate multiple predicates. They are similar to Python's built in any() and all() but don't call predicates once they have been satisfied. This is useful for predicates that are slow or inefficient.

The h5py package provides a Pythonic interface for the HDF5 binary data format. It allows you to store large amounts of numerical data and allow you to easily manipulate that data using NumPy. You can cut into multi-terabyte datasets on disk as if they were NumPy arrays. You can store thousands of datasets in one file. You can categorize and tag them however you like. H5py makes use of simple NumPy and Python metaphors like dictionary syntax and NumPy array syntax. You can, for example, iterate over files or examine the.shape and.dtype attributes of data. To get started, you don't need any knowledge about HDF5. In addition to an easy-to-use interface, h5py relies on an object-oriented Cython wrap of the HDF5 CAP API. You can do almost anything from C in HDF5 with h5py.

Unirest is a collection of lightweight HTTP libraries that are available in multiple languages. It was created and maintained by Kong who also maintains the open source API Gateway Kong. Install the npm module to use Unirest for node.js. Unirest makes it easier to create requests. Unirest supports gzip and can parse responses. You can also start with basic examples. To initiate a request, invoke the appropriate method on Unirest object and then call.end() to send it. You can also send the request directly by sending a callback with the URL. This provides simple and straightforward methods to manipulate the request before it is sent. This object is created when Unirest is invoked. This object has methods that can be chained like other libraries, such as jQuery or the popular request module Superagent (which is slightly modeled after this library).

Parsel is a BSD licensed Python library that extracts and removes data from HTML and XML. It uses XPath, CSS selectors and regular expressions. Make a selector object to parse the HTML or XML text. Next, use CSS or XPath expressions for selecting elements. CSS is a language that allows you to apply styles to HTML documents. It defines selectors that allow you to associate styles with specific HTML elements. XPath, which can be used with HTML, is a language that allows you to select nodes from XML documents. You can choose to use CSS or XPath. While CSS is more readable than XPath, some things cannot be done with XPath. Parsel selectors are built on top of lxml and support certain EXSLT extensions. They also come with pre-registered namesspaces for use in XPath statements. Parsel selectors let you chain selectors. This means that you can select by class using CSS, and then switch to XPath if necessary.

Embeddable.NET Library for running workflows within.NET applications, with an integrated HTML5 graphical designer. Designer allows you create interactive workflows with any complexity. You don't need to write them programmatically. Workflow Engine is the backbone for Business Process Management (BPM), which allows you to automate workflow design using visual builders. It is based upon the.NET Framework and JavaScript libraries. Workflow Engine facilitates workflow processing and integration by providing a graphic design tool to create workflow schemes. This software component also simplifies the management, execution and visualization of workflows. Integration with other technologies or databases should be relatively easy and not cause any problems. Workflow Engine provides all the components needed to implement workflows.

Pandas is an open-source data analysis and manipulation tool that is fast, flexible, flexible, and easy to use. It was built on top the Python programming language. Tools for reading and writing data between memory data structures and various formats: CSV, text files, Microsoft Excel, SQL databases and the fast HDF5 format. Intelligent data alignment and integrated handling missing data: Use a powerful group engine to perform split-apply/combine operations on data sets. Time series-functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging. You can even create domain-specific offsets and join time sequences without losing data.

Ant Design is an enterprise-class Angular UI component collection. All components are open-source and available under the MIT license. Ant Design of Angular aims to provide a great development experience for programmers. This StackBlitz link demonstrates a basic use-case. It is recommended that you fork this demo while working on Bug Report. This demo should not be used as a scaffold in a production environment. After changing the directory to your newly created project, you will be able to run the following commands to initialize your project's configuration. These include importing stylesheets and i18n files, and loading the initial modules. To customize the building process, you can use any existing scaffold tools from the Angular ecosystem.

Shadcn/ui, an open-source collection of beautifully designed components, is accessible and customizable. Developers can easily integrate them into their applications. These components, built with Tailwind CSS and designed for copying and pasting are easy to use, allowing rapid development without compromising design quality. The library includes a wide range of components such as buttons, sidebars and avatars. Tabs and charts are also included. All components are designed to be both aesthetically pleasing and functionally excellent. Shadcn UI focuses on composability, theming and customization. Developers can tailor components to match specific project requirements or branding guidelines. The platform offers comprehensive documentation and examples to help developers implement and customize components within their projects. Shadcn's UI allows developers to create user interfaces faster, while ensuring consistency and accessibility.

Bootstrap your application using beautiful Material Design components React Toolbox is a collection of React components that implements the Google Material Design specification. It is built on top of some of today's most popular proposals, such as CSS Modules (written using SASS, Webpack, and ES6). The library seamlessly integrates with your Webpack workflow. It's also easily customizable and flexible. Check out our amazing documentation, which is built using React Toolbox. You can also try all the components with real examples. Our components are so much fun that you don't even need to install them. The app bar is a unique type of toolbar that can be used for branding, navigation and search as well as actions. It usually has controls on the right- and left-sides, as well as a title that displays the current section or the app name. The content should contain elements for children. You can use text, images, or both to create content that is consistent with your app's colors theme.

Oracle Data Access Components are a collection of Windows and.NET data accessibility drivers and tools. They support.NET data access, Microsoft Visual Studio tools to develop Oracle database applications, and ASP.NET providers. ODAC offers comprehensive client support for advanced Oracle database functionality. This includes performance, high availability, security, and many other features. Visual Studio is seamlessly integrated with ODAC to offer developers a seamless development experience. Oracle Data Provider is a Microsoft implementation of ADO.NET that provides access to Oracle databases. OLAP Data Manipulation Language is used to create and manipulate analytic workspace objects. It is a high-performance, feature-rich tool for Microsoft ADO and OLE DB access to Oracle databases. It also allows for its configuration and usage. This section provides information about the usage, installation, configuration, and post-installation.

The Thinkmap SDK allows organizations to integrate data-driven visualization technology in their enterprise Web applications. The Thinkmap application allows users to understand complex information in a way that traditional interfaces cannot. The Thinkmap SDK (v.2.8) contains a variety of configurations that can be used to solve common visualization problems as well as new visualization techniques to customize data displays. Thinkmap is lightweight, fast, extensible, and can connect seamlessly to many data sources. The SDK contains detailed JavaScript reference and conceptual documentation for the Visualization Component, datasource adapters to relational databases and flat file; a library with traditional user interface elements that can also be used in Thinkmap applications; and a complete set examples to assist developers in getting up-and running quickly.

Deepnote is building the best data science notebook for teams. Connect your data, explore and analyze it within the notebook with real-time collaboration and versioning. Share links to your projects with other analysts and data scientists on your team, or present your polished, published notebooks to end users and stakeholders. All of this is done through a powerful, browser-based UI that runs in the cloud.

NetworkX is a Python package that allows you to create, manipulate, and study the structure, dynamics, as well as the functions, of complex networks. Generators for classic, random, and synthetic graphs. Python offers additional benefits such as fast prototyping and easy teaching. Network structure and analysis measures.

It uses a familiar, non XML syntax and compiles into Python modules to maximize performance. Mako's syntax borrows from many other sources, including Jinja2 templates, Cheetah and Myghty, as well as the best ideas of Genshi and Django. Conceptually Mako is embedded Python (i.e. Python Server Page) language. It refines the familiar ideas o componentized layout and inheritance to create one of the most flexible and straightforward models. While still keeping close ties to Python scoping and calling semantics, Mako is conceptually an embedded Python (i.e. Mako's method is very efficient, and was originally designed to be as fast as Cheetah. Today Mako is very similar in speed to Jinja2, who uses a similar approach, and for which Mako was an inspiration. You can access variables from the template's request context as well as their enclosing scope.

DataMelt, or "DMelt", is an environment for numeric computations, data analysis, data mining and computational statistics. DataMelt allows you to plot functions and data in 2D or 3D, perform statistical testing, data mining, data analysis, numeric computations and function minimization. It also solves systems of linear and differential equations. There are also options for symbolic, non-linear, and linear regression. Java API integrates neural networks and data-manipulation techniques using various data-manipulation algorithms. Support is provided for elements of symbolic computations using Octave/Matlab programming. DataMelt provides a Java platform-based computational environment. It can be used on different operating systems and programming languages. It is not limited to one programming language, unlike other statistical programs. This software combines Java, the most widely used enterprise language in the world, with the most popular data science scripting languages, Jython (Python), Groovy and JRuby.