Search Results for "python data analysis" - Page 4
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Showing 1158 open source projects for "python data analysis"
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Kedro
A Python framework for creating reproducible, maintainable code
Kedro is an open sourced Python framework for creating maintainable and modular data science code. Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems. Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems together. ... -
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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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pytype
A static type analyzer for Python code
pytype is a static type analyzer that checks and infers types for Python code without executing it, catching errors at “compile time” and generating actionable diagnostics. It grew alongside Python typing at Google and can understand both inline annotations and unannotated code via powerful inference. The tool consumes stub files (.pyi) for the standard library and third-party packages (from typeshed and its own built-ins), enabling accurate checks even in large, mixed-quality codebases.... -
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Copulas
A library to model multivariate data using copulas
Copulas is a Python library for modeling multivariate distributions and sampling from them using copula functions. Given a table of numerical data, use Copulas to learn the distribution and generate new synthetic data following the same statistical properties. Choose from a variety of univariate distributions and copulas – including Archimedian Copulas, Gaussian Copulas and Vine Copulas. -
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Deequ
Deequ is a library built on top of Apache Spark
...It also includes a little domain-specific language called DQDL (Data Quality Definition Language) which allows declarative specification of quality rules. Users typically run Deequ before feeding data downstream (to ML pipelines, analytics, or production systems), enabling early detection and isolation of data errors. There is also a Python wrapper, PyDeequ, for users who prefer working from Python environments. -
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Scrapy
A fast, high-level web crawling and web scraping framework
Scrapy is a fast, open source, high-level framework for crawling websites and extracting structured data from these websites. Portable and written in Python, it can run on Windows, Linux, macOS and BSD. Scrapy is powerful, fast and simple, and also easily extensible. Simply write the rules to extract the data, and add new functionality if you wish without having to touch the core. Scrapy does the rest, and can be used in a number of applications. -
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JC
CLI tool and python library
...The JC parsers can also be used as python modules. In this case, the output will be a python dictionary, or a list of dictionaries, instead of JSON. Two representations of the data are available. The default representation uses a strict schema per parser and converts known numbers to int/float JSON values. Certain known values of None are converted to JSON null, known boolean values are converted, and, in some cases, additional semantic context fields are added. -
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Dash
Build beautiful web-based analytic apps, no JavaScript required
Dash is a Python framework for building beautiful analytical web applications without any JavaScript. Built on top of Plotly.js, React and Flask, Dash easily achieves what an entire team of designers and engineers normally would. It ties modern UI controls and displays such as dropdown menus, sliders and graphs directly to your analytical Python code, and creates exceptional, interactive analytics apps. Dash apps are very lightweight, requiring only a limited number of lines of Python or... -
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Metaflow
A framework for real-life data science
Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. -
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APIPark
APIPark is the #1 open-source AI Gateway and Developer Portal
...No matter which AI model you use, APIPark provides a one-stop integration solution. It unifies the management of all authentication information and tracks the costs of API calls. Standardize the request data format for all AI models. When switching AI models or modifying prompts, it won’t affect your app or microservices, simplifying your AI usage and reducing maintenance costs. You can quickly combine AI models and prompts into new APIs. For example, using OpenAI GPT-4 and custom prompts, you can create sentiment analysis APIs, translation APIs, or data analysis APIs. ... -
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Dagster
An orchestration platform for the development, production
Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust... -
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Protocol Buffers
Google's data interchange format
Protocol Buffers are Google’s fast and simple, language- and platform-neutral, extensible mechanism for serializing structured data. It allows you to define how your data should be structured once, and then using a special generated source code, you can then easily write and read your structured data to and from a variety of data streams and using a variety of languages. Protocol Buffers currently supports a wide array of languages, including C++, Java, Python, Ruby, and many others with more to come. -
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pywebview
Build GUI for your Python program with JavaScript, HTML, and CSS
pywebview is a lightweight cross-platform wrapper around a webview component that allows to display HTML content in its own native GUI window. It gives you power of web technologies in your desktop application, hiding the fact that GUI is browser based. You can use pywebview either with a lightweight web framework like Flask or Bottle or on its own with a two way bridge between Python and DOM. pywebview uses native GUI for creating a web component window: WinForms on Windows, Cocoa on macOS... -
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cuDF
GPU DataFrame Library
Built based on the Apache Arrow columnar memory format, cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data. cuDF provides a pandas-like API that will be familiar to data engineers & data scientists, so they can use it to easily accelerate their workflows without going into the details of CUDA programming. For additional examples, browse our complete API documentation, or check out our more detailed notebooks. cuDF can be installed with conda (miniconda, or the full Anaconda distribution) from the rapidsai channel. cuDF is supported only on Linux, and with Python versions 3.7 and later. ... -
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CTGAN
Conditional GAN for generating synthetic tabular data
CTGAN is a collection of Deep Learning based synthetic data generators for single table data, which are able to learn from real data and generate synthetic data with high fidelity. If you're just getting started with synthetic data, we recommend installing the SDV library which provides user-friendly APIs for accessing CTGAN. The SDV library provides wrappers for preprocessing your data as well as additional usability features like constraints. When using the CTGAN library directly, you may... -
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Superduper
Superduper: Integrate AI models and machine learning workflows
Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. ... -
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bearer
Code security scanning tool (SAST) to discover security risks
Welcome to the Bearer documentation. Bearer is a static application security testing (SAST) tool that scans your source code and analyzes your data flows to discover, filter and prioritize security risks and vulnerabilities leading to sensitive data exposures (PII, PHI, PD). We provides built-in rules against a common set of security risks and vulnerabilities, known as OWASP Top 10. Leakage of sensitive data through cookies, internal loggers, third-party logging services, and into analytics... -
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Soufflé
Datalog variant for tool designers crafting analyses in Horn clauses
Rapid prototyping for your analysis problems with logic; enabling deep design-space explorations; designed for large-scale static analysis; e.g., points-to analysis for Java, taint-analysis, and security checks. Futamura projections/partial evaluation for effective translation to parallel C++; optimized staged compilation; specialized data-structures for logical relations. -
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JumpServer
Manage assets on different clouds at the same time
The JumpServer bastion machine complies with the 4A specification of operation and maintenance security audit. Zero threshold, fast online acquisition and installation. Just a browser, the ultimate Web Terminal experience. Easily support massive concurrent access. One system manages assets on different clouds at the same time. Audit recordings are stored in the cloud and will never be lost. One system, is used by multiple subsidiaries and departments at the same time. Prevent identity fraud... -
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Peroxide
Rust numeric library with high performance and friendly syntax
Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. -
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ConcurrentSim.jl
Discrete event process oriented simulation framework written in Julia
A discrete event process-oriented simulation framework written in Julia inspired by the Python library SimPy. One of the longest-lived Julia packages (originally under the name SimJulia). -
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Gretel Synthetics
Synthetic data generators for structured and unstructured text
Unlock unlimited possibilities with synthetic data. Share, create, and augment data with cutting-edge generative AI. Generate unlimited data in minutes with synthetic data delivered as-a-service. Synthesize data that are as good or better than your original dataset, and maintain relationships and statistical insights. Customize privacy settings so that data is always safe while remaining useful for downstream workflows. Ensure data accuracy and privacy confidently with expert-grade reports.... -
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gosec
Golang security checker
...Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with the License. You can integrate third-party code analysis tools with GitHub code scanning by uploading data as SARIF files. The workflow shows an example of running the gosec as a step in a GitHub action workflow that outputs the results.sarif file. The workflow then uploads the results.sarif file to GitHub using the upload-serif action. Gosec can be configured to only run a subset of rules, to exclude certain file paths, and produce reports in different formats. ... -
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NVTX (NVIDIA Tools Extension Library)
C-based Application Programming Interface (API)
NVTX (NVIDIA Tools Extension) is a cross-platform API designed to annotate source code with rich metadata that can be consumed by developer profiling and debugging tools. It allows developers to insert markers, ranges, and events directly into their applications, providing contextual insight into how code executes on CPUs and GPUs. These annotations are visualized in tools such as NVIDIA Nsight Systems and Nsight Compute, enabling developers to identify performance bottlenecks, track... -
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Behaviour Suite Reinforcement Learning
bsuite is a collection of carefully-designed experiments
bsuite is a research framework developed by Google DeepMind that provides a comprehensive collection of experiments for evaluating the core capabilities of reinforcement learning (RL) agents. Its main goal is to identify, measure, and analyze fundamental aspects of learning efficiency and generalization in RL algorithms. The library enables researchers to benchmark their agents on standardized tasks, facilitating reproducible and transparent comparisons across different approaches. Each...
