Alternatives to pandas

Polars, which is aware of the data-wrangling habits of its users, exposes a complete Python interface, including all of the features necessary to manipulate DataFrames. This includes an expression language, which will allow you to write readable, performant code. Polars was written in Rust to provide the Rust ecosystem with a feature-complete DataFrame interface. Use it as either a DataFrame Library or as a query backend for your Data Models.

OpenRefine (previously Google Refine), is a powerful tool to work with messy data. It can clean it, transform it into another format, and extend it with web services or external data. OpenRefine keeps your data secure on your computer until you share it or collaborate with others. Unless you wish it to, your private data will never leave your computer. It works by installing a small server on your computer. You then use your web browser for interaction with it. OpenRefine allows you to explore large data sets easily. Watch the video below to learn more about this functionality. OpenRefine can link and extend your data with many webservices. OpenRefine can also upload your cleaned data to Wikidata.

Vaex.io aims to democratize the use of big data by making it available to everyone, on any device, at any scale. Your prototype is the solution to reducing development time by 80%. Create automatic pipelines for every model. Empower your data scientists. Turn any laptop into an enormous data processing powerhouse. No clusters or engineers required. We offer reliable and fast data-driven solutions. Our state-of-the art technology allows us to build and deploy machine-learning models faster than anyone else on the market. Transform your data scientists into big data engineers. We offer comprehensive training for your employees to enable you to fully utilize our technology. Memory mapping, a sophisticated Expression System, and fast Out-of-Core algorithms are combined. Visualize and explore large datasets and build machine-learning models on a single computer.

Built and maintained by a group of differential privacy experts and used in production at institutions such as the U.S. Census Bureau. Spark-based and supports input tables with billions of rows. Supports an ever-growing number of aggregation operators, data transformation operators and privacy definitions. Perform public and privacy joins, filters or user-defined function on your data. Calculate counts, sums and quantiles under multiple privacy models. Our simple tutorials and extensive documentation make it easy to differentiate privacy. Tumult Analytics was built on Tumult Core - our sophisticated privacy foundation. Tumult Core mediates access to sensitive information and means that each program and application has an embedded proof of security. Composed of small, easily-reviewable components. Stability tracking and floating point primitives that are proven to be safe. Generic framework based on peer reviewed research.

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.

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.

Avanzai allows you to use natural language to produce Python code that is ready for production. This will help you speed up your financial data analysis. Avanzai makes financial data analysis easier for both beginners as well as experts. It uses plain English to provide simple English support. Natural prompts allow you to plot times series data, equity index members, or stock performance data. Use AI to generate code using the relevant Python packages. You can edit the code as needed. Once you are satisfied with the code, copy it into your local environment. Then you can get to work. Use Python packages such as Pandas, Numpy and others to perform quant analysis. You can quickly extract fundamental data and calculate the performance for nearly all US stocks. Accurate and current information will improve your investment decisions. Avanzai allows you to write the same Python code as quants to analyze complex financial data.

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Bokeh allows you to create simple plots but can also handle custom or specialized use cases. Apps, dashboards and plots can be published on web pages or in Jupyter notebooks. Python offers a wide range of powerful analytics tools, including NumPy and Scipy, Pandas. Scikit-Learn, OpenCV and Scikit-Learn. Bokeh server allows you to connect these tools to rich interactive visualizations in your browser. It has a wide range of widgets, plot tools and UI events that trigger Python callbacks. Researchers at Monash University maintain Microscopium. Researchers can use it to explore large image datasets using Bokeh's interactive tools. Panel is a tool that allows for polished data presentation and makes use of the Bokeh server. Anaconda created it and supports it. Panel allows you to easily create interactive web apps and dashboards using user-definable widgets. These widgets can be connected to plots, images or tables, text, or any other data.

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.

Web ARChive (WARC), files can be handled with this tool and library. Naively join archives into one. Extract files from archive. List commands available. List contents of archive. Write out the contents of the archive. Split archives into individual records. Verify the digest and verify conformance. The library may not yet be thread-safe. Warcat's goal is to create a tool that can be used to manipulate any archive, such as zip or tar archives, as quickly and as efficiently as other tools. Warcat can partially extract large files that have been gzip-ed. Warcat is not a warranty and cannot guarantee your files' safety. Make backups and make sure to test them! A WARC file is a collection of one or more records that are concatenated together. Each record has named fields, newline and a content block. A Content Block can be one of two types: binary data or named fields, newline and binary data.

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.

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.

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.

It is more than a new generation "Decision Cube"; it is also more than Pivot Grid control. It is a standalone, high-speed OLAP-cube engine. Integrate FastCube OLAP library to your application, prepare data (or multiple data sets) for your end-users and bring Business Intelligence directly to your application! Your end-users have full control over the creation of reports. This will help them make reasonable decisions. FastCube VCL is a set that can be used to create pivot table reports. It supports Delphi 7 - XE8, C++Builder 2005 - XE8, Embarcadero RAD Studio 10 – 11 and Lazarus. Customers will no longer require Excel-tables to perform cross-tab and multi-dimensional data analysis. FastCube components are easily integrated into host applications. FastCube users don't need to be proficient in programming to create reports. FastCube is a set OLAP Desktop components that Delphi can use.

Advanced data analysis with no code Get insights quickly and accurately. Datavore: Why? Datavore makes it easier to create workflows and combine signals faster. To validate and test signals, you need to track indicators across multiple datasets. Organize. Organize all your data. Dynamic filters can be used to quickly locate internal and external data. Explore. Create dashboards to monitor, compare, and evaluate lines. Track multiple indicators across different datasets efficiently and effectively. Analyze. Deep proprietary research is possible by creating forecasting models and regression analyses. Platform. Excel flexibility with cloud scalability. Automate tedious tasks and perform quantitative research easily. Excel Syntax. Use pre-built time series formulas to create custom functions. Patented ingestion engine. Find concepts and relationships within large datasets. Alignment of calendars. Match data to predefined periods or the company's fiscal calendar. Aggregations

Coheris Spad by ChapsVision offers a self-service data analysis service for Data Scientists of all industries and sectors. Coheris Spad is taught at many top French and foreign universities. This gives it a great reputation within the Data Scientists community. Coheris Spad from ChapsVision gives you a wealth of methodological knowledge that covers a wide range of data analysis. You have all the power to discover, prepare, and analyze your data in a user-friendly, intuitive environment.

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.

The world's only free modern embeddable data and analytics platform that provides a self-service, powerful, secure & seamless end-to-end experience. DataClarity Unlimited Analytics Benefits: SIMPLIFIED DATA INTEGRATION – Easily connect, join, curate, cache & catalog diverse data through drag and drop, custom SQL builder and AI-powered data profiling. | INTERACTIVE REPORTS & DASHBOARDS – craft compelling storyboards using 80 stunning visualizations, geospatial maps & flexibility to bring your own charts. | REAL-TIME ANALYSIS – Perform advanced analysis & data exploration using drill-down, drill-through, filters, built-in statistical & predictive models, or your own Python and R code. | SMOOTH APPLICATION INTEGRATION – Achieve seamless integration with robust APIs, tailor-made configurations and flexible embedding features. | SECURITY and GOVERNANCE – Comply with your security guidelines, governance standards, multitenancy, row-level data protection, and SSO (Single Sign-On). DataClarity Unlimited Analytics is tailored for ISVs , SaaS providers, consultancies, and IT teams and includes: free forever software license, free version updates & access to support resources, and optional paid 24/7 production support with SLA.

Molecula, an enterprise feature store, simplifies, speeds up, and controls big-data access to power machine scale analytics and AI. Continuously extracting features and reducing the data dimensionality at the source allows for millisecond queries, computations, and feature re-use across formats without copying or moving any raw data. The Molecula feature storage provides data engineers, data scientists and application developers with a single point of access to help them move from reporting and explaining with human scale data to predicting and prescribing business outcomes. Enterprises spend a lot of time preparing, aggregating and making multiple copies of their data before they can make any decisions with it. Molecula offers a new paradigm for continuous, real time data analysis that can be used for all mission-critical applications.

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.

MyDataModels' best-in-class predictive analytics model TADA allows professionals to use their Small Data to improve their business. It is a simple-to-use tool that is easy to set up. TADA is a predictive modeling tool that delivers fast and useful results. With our 40% faster automated data preparation, you can transform your time from days to just a few hours to create ad-hoc effective models. You can get results from your data without any programming or machine learning skills. Make your time more efficient with easy-to-understand models that are clear and understandable. You can quickly turn your data into insights on any platform and create automated models that are effective. TADA automates the process of creating predictive models. Our web-based pre-processing capabilities allow you to create and run machine learning models from any device or platform.

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.

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.

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.

The Pylons web framework was designed to make it easy and quick to build web applications and websites. They can be as simple as one Python module or as complex as a directory layout for larger, more complex web applications. Pylons includes project templates to help you set up a new web app project. Or, you can create your own and customize it as you wish. This framework makes it easy to write Python web applications. It is simple to expand on the minimalist, component-based philosophy. Use existing Python knowledge. Extensible application design. High performance, fast and efficient with a very small per-request stack. Uses well-tested Python packages. The Pylons 1.0 series is stable, production-ready, but in maintenance-only mode. The Pylons Project maintains the Pyramid web framework to support future development. Pylons 1.0 users are strongly encouraged to use Pyramid for their next project.

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.

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.

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.

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.

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.

Seaborn is a Python data visualization tool that uses matplotlib. It provides a high-level interface to draw attractive and informative statistical graphs. The paper and introductory notes provide a brief overview of the library's ideas. To download the package and get started, visit the installation page. To see some of the seaborn-related tasks, you can look through the example gallery. Then, check out the tutorials and API reference. Visit the GitHub repository to view the code and report a bug. You can find general support questions on StackOverflow. There is also a channel for seaborn.

Enterprise apps require high-performance JavaScript UI controls. Fast, lightweight HTML5/JavaScript apps that are fast and have zero dependencies. New in Wijmo 2022 v1: - Inventory management reference app built in Angular - Website traffic monitoring reference app built in Angular - FlexMap added to GeoDashboard reference app - Rotated Spline Chart - Re-order FlexGrid rows with drag and drop Wijmo's General Features: - CellTemplates for Vue FlexGrids, Angular, and React - Wijmo's single set true JavaScript controls can be used in any framework including Angular and React. Wijmo Web Components allows you to use controls as native HTML elements FlexGrid, JavaScript’s fastest data grid, allows you to filter, group, sort and much more - Visualize data using 80+ charts and controls OLAP Pivot Grid - Instantly analyze, aggregate and visualize data

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.

DataViewsJS allows you to customize the presentation of your data professionally using different layouts, rows templates, calculations and editing modes. You can use the powerful calc engine for calculations on any JSON data set. Our calculation engine optimizes your computing power for complex calculations and large data. DataViewsJS was built from the ground up to be a powerful, flexible, and fast developer tool that can display and edit data to suit any JavaScript application. DataViewsJS includes localized resources for Chinese and Japanese as well as Korean. You can easily add additional languages by creating resource files and setting them up with simple script code. DataViewsJS interchangeable layouts make it easy to present modern data patterns, such as those found on social networks and other sites.

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.

Flutter is Google's UI Toolkit that allows you to create beautiful, natively compiled apps for mobile, web and desktop using a single codebase. Stateful Hot Reload makes your app come to life in a matter of seconds. You can quickly create native interfaces with a rich collection of widgets that you can fully customize. You can quickly ship features that are focused on native end-user experiences. The layering architecture allows for full customization which results in extremely fast rendering and expressive and flexible design. Flutter's widgets include all platform differences, such as scrolling and navigation. Your Flutter code is compiled using Dart's native compilers to native ARM machine codes. Flutter's hot reload allows you to quickly and easily experiment, create UIs, add features and fix bugs quicker. Flutter's hot reload speeds are sub-second and you won't lose state on simulators, emulators, or hardware.

Visplore is a graphical program that allows you to explore large multivariate data such as time series from sensors or machines. These ready-to-use tools can save you a lot of time and help non-programmers make valuable discoveries. Highlights - Use zooming and zooming to quickly access millions of data records. . Interactively select, cleanse, label, and export data Connect with Python, R and Matlab to get started in just a minute.

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.

Dedupe.io, a powerful tool, can help you find similar rows in your data. Machine learning and cutting-edge research allow us to quickly and accurately identify matches within your Excel spreadsheet or database. This will save you time and money. There is more data than ever in today's big data world. All this data can be difficult to use, especially if it was entered manually or comes from different systems. It can be difficult and time-consuming to figure out who is who in a spreadsheet. Dedupe.io is here to help. We created the most dynamic and scalable solution to de-duplicating or linking datasets and created a step-by-step wizard that anyone can use.

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 powerful, yet simple-to-use package for accessing, manipulating and analyzing information. Now available for cloud or on-site deployment. Why combine niche software packages from different vendors. A consolidated portfolio, which includes three of our most popular products (Base SAS, SAS/STAT, and SAS/GRAPH), reduces licensing, maintenance, and training costs, while providing consistent information across your enterprise. SAS statistical procedures are continuously updated to reflect the most recent advances in statistical methodology. Technical support is provided by highly qualified statisticians at master's and doctorate levels. This allows them to provide a level of service that is not possible with other software vendors. SAS has over four decades of experience in developing statistical analysis software that organizations around world rely upon to provide accurate answers for data questions.

SparkBeyond Discovery automatically analyzes complex data and finds answers to business problems in places you might not have thought. Integrate external data seamlessly into your search space to gain a better understanding of the real factors that influence outcomes and a more holistic view of your business reality. Analytics projects can be made more experimental by interacting in natural language with data and insights. This allows for a deeper partnership between business stakeholders and analytics. Future-proof the hard-earned benefits of analytics by maintaining an evergreen cycle for inputs and outputs. Your insights should change with the world. Auto-connect all data types, from time-series to geospatial, in their raw, granular form without having to write a single line code. Integrate our curated global knowledge database (maps, Wikipedia and demographics) to see the whole picture.

Kibana is a free, open-source user interface that allows you to visualize your Elasticsearch data as well as navigate the Elastic Stack. You can track query load and understand how requests flow through your apps. Kibana allows you to choose how you want to present your data. Start with one question to see what interactive visualizations lead you. Kibana core ships the classics: histograms and line graphs, pie charts and pie charts, as well as sunbursts and sunbursts. You can also search across all your documents. Use Elastic Maps to explore your location data. Or get creative and visualize custom layers or vector shapes. Our curated time series interfaces allow you to perform advanced analysis of your Elasticsearch data. Use powerful, easy to learn expressions to describe queries, transformations, or visualizations.

VertiPaq Analyst is used to analyze VertiPaq storage structure for a data model using Power BI and Analysis Services Tabular. Added measures for segments or partitions: pageable and resident, refresh date, last acces. Analysis Services offers many Dynamic Management Views, (DMV), to gather information about the memory used by a data modeling. For example, DISCOVER_OBJECT_MEMORY_USAGE is a DMV that provides information about all the objects in memory. This DMV can also be used to monitor Analysis Services Multidimensional instances. Kasper de Jonge has created a sample model (BISM memory Report) that organizes the data in a hierarchical fashion. This makes it easy to find expensive tables, databases, and columns on a server. You will need to examine the details of a particular database to be able to analyze it.

Find data insights that will help you solve business and research problems. IBM®, SPSS®, Statistics is a powerful statistical platform. It features a user-friendly interface, a robust set of capabilities that allow your organization to quickly extract actionable insights out of your data. Advanced statistical techniques ensure high quality and accuracy in decision making. All aspects of the analytics lifecycle, from data preparation and management to analysis, reporting and reporting, are covered. An intuitive user interface makes it easy to prepare and analyze data without writing code. You can enhance SPSS syntax with R or Python by using a variety of extensions or building your own. An integrated interface allows you to run advanced and descriptive statistics, regression analysis and decision trees. You can choose from traditional or subscription licenses with multiple capabilities depending on your needs.

Vista is a powerful platform that provides insight-as a service. It offers mobile location data, analytics and media measurement for all sizes of businesses. Vista provides pre-processed insights that can be exported in a variety formats. Vista is a powerful insight-as a service platform that provides mobile location data, analytics and media measurement to businesses of all sizes. This allows them to better understand their customers and their competitors and helps them capitalize on their performance. Multi-faceted tools that can be tailored to the needs of specific organizations. Analytical tools that are tailored to suit all levels of analysts. All data types are available for seamless integration into existing workflows. Our in-house data scientists and GIS analysts create custom reports and analysis. Where visitors were seen 30 mins before or after a visit. The most frequent visits to a particular location are generated from a geographic area.

Zuar offers a dynamic customer portal designed to evolve with your customers' needs. Simplify the creation and management of a personalized, data-driven customer experience. Tackle common challenges such as UI/UX issues, slow performance, and limited functionality with our solution. Zuar ensures a seamless, consistent experience across all platforms and devices, standing as a key component in your data-driven strategy. By integrating with top business intelligence and cloud database platforms, we provide the tools to foster trust and transparency, enhancing customer retention and satisfaction.

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.

Secure is a platform that offers landlords and property managers the ability to make informed decisions using real-time data. Secure, with a focus on Data Analytics and Digital Twin, collects, manages and delivers extensive and diverse data in an easy to use format. Secure reports on data aggregated from disparate systems in your building, providing insights such as energy consumption and occupancy. Secure digital twin is a 3D replica of the building. It provides facility managers with complete remote visibility. It improves operational performance and increases efficiencies. Secure helps you manage your journey towards net-zero emissions by using smart technology. It provides a holistic view of your properties, and manages your energy consumption.