Search Results for "data transformation"
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Showing 49 open source projects for "data transformation"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Data Formulator
Create rich visualizations with AI
To create rich visualizations, data analysts often need to iterate back and forth among data processing and chart specification to achieve their goals. To achieve this, analysts need not only proficiency in data transformation and visualization tools but also efforts to manage the branching history consisting of many different versions of data and charts. Recent LLM-powered AI systems have greatly improved visualization authoring experiences, for example by mitigating manual data transformation barriers via LLMs' code generation ability. ... -
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Polyhedra
Polyhedral Computation Interface
Polyhedra provides an unified interface for Polyhedral Computation Libraries such as CDDLib.jl. This manipulation notably includes the transformation from (resp. to) an inequality representation of a polyhedron to (resp. from) its generator representation (convex hull of points + conic hull of rays) and projection/elimination of a variable with e.g. Fourier-Motzkin. -
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Chain.jl
A Julia package for piping a value through transformation expressions
A Julia package for piping a value through a series of transformation expressions using a more convenient syntax than Julia's native piping functionality. -
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collapse
Advanced and Fast Data Transformation in R
collapse is a high-performance R package designed for fast and efficient data transformation, aggregation, reshaping, and statistical computation. Built to offer a more performant alternative to dplyr and data.table, it is particularly well-suited for large datasets and econometric applications. It operates on base R data structures like data frames and vectors and uses highly optimized C++ code under the hood to deliver significant speed improvements. collapse also includes tools for grouped operations, weighted statistics, and time series manipulation, making it a compact yet powerful utility for data scientists and researchers working in R. -
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AI Data Science Team
An AI-powered data science team of agents
AI Data Science Team is a Python library and agent ecosystem designed to accelerate and automate common data science workflows by modeling them as specialized AI “agents” that can be orchestrated to perform tasks like data cleaning, transformation, analysis, visualization, and machine learning. It provides a modular agent framework where each agent focuses on a step in the typical data science pipeline — for example, loading data from CSV/Excel files, cleaning and wrangling messy datasets, engineering predictive features, building models with AutoML, connecting to SQL databases, and producing visual outputs — all driven by natural language or programmatic instructions. ... -
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Malli
High-performance data-driven data specification library
Malli is a powerful, data-driven schema library for Clojure and ClojureScript, offering rich support for specification, validation, parsing, error reporting, and generative testing. Designed for performance, Malli leverages efficient runtime representations and code generation, seamlessly integrating with Clojure’s data-oriented architecture. It supports function schemas, JSON transformation, and OpenAPI generation for strong API contracts. -
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Blue Whale Configuration Platform
Blue Whale smart cloud configuration platform
Has accumulated experience in supporting hundreds of Tencent businesses, compatible with various complex system architectures, born in operation and maintenance, and proficient in operation and maintenance. From configuration management to job execution, task scheduling and monitoring self-healing, and then through operation and maintenance big data analysis to assist operational decision-making, it covers the full-cycle assurance management of business operations in a comprehensive manner. The open PaaS has a powerful development framework and scheduling engine, as well as a complete operation and maintenance development training system, which helps the rapid transformation and upgrading of operation and maintenance. ... -
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Kapacitor
Open source framework for processing, monitoring, and alerting
Open source framework for processing, monitoring, and alerting on time series data. Kapacitor is a real-time data processing engine for monitoring and alerting, specifically designed to work with time-series data from InfluxDB. -
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NeuralOperators.jl
DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia
Neural operator is a novel deep learning architecture. It learns an operator, which is a mapping between infinite-dimensional function spaces. It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function... -
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Tidier.jl
Meta-package for data analysis in Julia, modeled after the R tidyverse
Tidier.jl is a Julia package that brings tidyverse-style data manipulation and analysis to Julia, inspired by R's dplyr and tidyverse. It allows users to write expressive and concise data transformation code using chaining (|>) and intuitive syntax. Built on top of DataFrames.jl, Tidier.jl aims to make data wrangling more accessible to users familiar with R or looking for cleaner data pipelines in Julia. -
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CoordinateTransformations.jl
A fresh approach to coordinate transformations
CoordinateTransformations is a Julia package to manage simple or complex networks of coordinate system transformations. Transformations can be easily applied, inverted, composed, and differentiated (both with respect to the input coordinates and with respect to transformation parameters such as rotation angle). Transformations are designed to be light-weight and efficient enough for, e.g., real-time graphical applications, while support for both explicit and automatic differentiation makes... -
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DataFramesMeta.jl
Metaprogramming tools for DataFrames
Metaprogramming tools for DataFrames.jl objects to provide more convenient syntax. DataFrames.jl has the functions select, transform, and combine, as well as the in-place select! and transform! for manipulating data frames. DataFramesMeta.jl provides the macros @select, @transform, @combine, @select!, and @transform! to mirror these functions with more convenient syntax. Inspired by dplyr in R and LINQ in C#. -
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sparklyr
R interface for Apache Spark
sparklyr is an R package that provides seamless interfacing with Apache Spark clusters—either local or remote—while letting users write code in familiar R paradigms. It supplies a dplyr-compatible backend, Spark machine learning pipelines, SQL integration, and I/O utilities to manipulate and analyze large datasets distributed across cluster environments. -
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Apache DevLake
Apache DevLake is an open-source dev data platform
...You can ask Apache DevLake many questions regarding your development process. Just connect and query. Your Dev Data lives in many silos and tools. DevLake brings them all together to give you a complete view of your Software Development Life Cycle (SDLC). From DORA to scrum retros, DevLake implements metrics effortlessly with prebuilt dashboards supporting common frameworks and goals. DevLake fits teams of all shapes and sizes, and can be readily extended to support new data sources, metrics, and dashboards, with a flexible framework for data collection and transformation. -
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Jitsu
Jitsu is an open-source Segment alternative
...Jitsu can either stream data in real-time or send it in micro-batches (up to once a minute). Apply any transformation with Jitsu. Just write JavaScript code right in the UI to do anything with incoming data. And yes, the code editor supports code completion, debugging and many more. It feels like a full-featured IDE! -
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Pyper
Concurrent Python made simple
Pyper is a Python-native orchestration and scheduling framework designed for modern data workflows, machine learning pipelines, and any task that benefits from a lightweight DAG-based execution engine. Unlike heavier platforms like Airflow, Pyper aims to remain lean, modular, and developer-friendly, embracing Pythonic conventions and minimizing boilerplate. It focuses on local development ergonomics and seamless transition to production environments, making it ideal for small teams and... -
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PyVista
3D plotting and mesh analysis through a streamlined interface
3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK). PyVista is a helper module for the Visualization Toolkit (VTK) that takes a different approach on interfacing with VTK through NumPy and direct array access. This package provides a Pythonic, well-documented interface exposing VTK’s powerful visualization backend to facilitate rapid prototyping, analysis, and visual integration of spatially referenced datasets. This module can be used for... -
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Datumaro
Dataset Management Framework, a Python library and a CLI tool to build
Datumaro is a flexible Python-based dataset management framework and command-line tool for building, analyzing, transforming, and converting computer vision datasets in many popular formats. It supports importing and exporting annotations and images across a wide variety of standards like COCO, PASCAL VOC, YOLO, ImageNet, Cityscapes, and many more, enabling easy integration with different training pipelines and tools. Datumaro makes it easy to merge datasets, split them into... -
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Datapipe
Real-time, incremental ETL library for ML with record-level depend
Datapipe is a real-time, incremental ETL library for Python with record-level dependency tracking. Datapipe is designed to streamline the creation of data processing pipelines. It excels in scenarios where data is continuously changing, requiring pipelines to adapt and process only the modified data efficiently. This library tracks dependencies for each record in the pipeline, ensuring minimal and efficient data processing. -
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Fondant
Production-ready data processing made easy and shareable
Fondant is a modular, pipeline-based framework designed to simplify the preparation of large-scale datasets for training machine learning models, especially foundation models. It offers an end-to-end system for ingesting raw data, applying transformations, filtering, and formatting outputs—all while remaining scalable and traceable. Fondant is designed with reproducibility in mind and supports containerized steps using Docker, making it easy to share and reuse data processing components.... -
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HStreamDB
HStreamDB is an open-source, cloud-native streaming database
HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications. By subscribing to streams in HStreamDB, any update of the data stream will be pushed to your apps in real-time, and this promotes your apps to be more responsive. You can also replace message brokers with HStreamDB and everything you do with message brokers can be done better with HStreamDB. HStreamDB provides built-in support for event time-based stream processing. ... -
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Ubix Linux
The Pocket Datalab
Ubix stands for Universal Business Intelligence Computing System. Ubix Linux is an open-source, Debian-based Linux distribution geared towards data acquisition, transformation, analysis and presentation. Ubix Linux purpose is to offer a tiny but versatile datalab. Ubix Linux is easily accessible, resource-efficient and completely portable on a simple USB key. Ubix Linux is a perfect toolset for learning data analysis and artificial intelligence basics on small to medium datasets. ... -
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Mara Pipelines
A lightweight opinionated ETL framework, halfway between plain scripts
This package contains a lightweight data transformation framework with a focus on transparency and complexity reduction. Data integration pipelines as code: pipelines, tasks and commands are created using declarative Python code. PostgreSQL as a data processing engine. Extensive web ui. The web browser as the main tool for inspecting, running and debugging pipelines. GNU make semantics. -
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GETL
ETL engine based on Groovy
P.S. Dear friends. Repository migration to https://github.com/ascrus/getl . You can download jar file from this site or maven. GETL - based package in Groovy, which automates the work of loading and transforming data. His name is an acronym for «Groovy ETL». GETL is a set of libraries of pre-built classes and objects that can be used to solve problems unpacking, transform and load data into programs written in Groovy, or Java, as well as from any software that supports the work with... -
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Feathr
A scalable, unified data and AI engineering platform for enterprise
Feathr is a data and AI engineering platform that is widely used in production at LinkedIn for many years and was open sourced in 2022. It is currently a project under LF AI & Data Foundation. Define data and feature transformations based on raw data sources (batch and streaming) using Pythonic APIs. Register transformations by names and get transformed data(features) for various use cases including AI modeling, compliance, go-to-market and more. Share transformations and data(features)...