Search Results for "python data analysis" - Page 27
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Showing 6357 open source projects for "python data analysis"
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cuDF
GPU DataFrame Library
... 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. The RAPIDS suite of open-source software libraries aims to enable the execution of end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization but exposing that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. -
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Autograd
Efficiently computes derivatives of numpy code
Autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily... -
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Mythril
Security analysis tool for EVM bytecode. Supports smart contracts
Mythril is a security analysis tool for EVM bytecode. It detects security vulnerabilities in smart contracts built for Ethereum, Hedera, Quorum, Vechain, Roostock, Tron and other EVM-compatible blockchains. It uses symbolic execution, SMT solving and taint analysis to detect a variety of security vulnerabilities. It's also used (in combination with other tools and techniques) in the MythX security analysis platform. If you are a smart contract developer, we recommend using MythX tools which... -
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pgsync
Postgres to Elasticsearch/OpenSearch sync
pgsync is a lightweight tool for syncing Postgres databases across environments, such as from production to staging. It allows selective table syncing, data masking, and parallel copying for fast and safe data migration. pgsync is ideal for developers who need realistic test data without exposing sensitive information. -
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OpenDataMCP
Connect any Open Data to any LLM with Model Context Protocol
An initiative aimed at connecting open datasets to Large Language Models (LLMs) using the Model Context Protocol, facilitating seamless access and integration of public data into AI applications. -
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DictDataBase
A python NoSQL dictionary database, with concurrent access and ACID
DictDataBase (DictDB) is a lightweight, Python-based in-memory database that uses dictionaries as its primary data structure. It provides a simple and efficient way to store, retrieve, and manipulate data without requiring an external database server. DictDB is useful for applications needing fast lookups, temporary storage, or embedded database functionalities. -
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Hamilton DAGWorks
Helps scientists define testable, modular, self-documenting dataflow
Hamilton is a lightweight Python library for directed acyclic graphs (DAGs) of data transformations. Your DAG is portable; it runs anywhere Python runs, whether it's a script, notebook, Airflow pipeline, FastAPI server, etc. Your DAG is expressive; Hamilton has extensive features to define and modify the execution of a DAG (e.g., data validation, experiment tracking, remote execution). To create a DAG, write regular Python functions that specify their dependencies with their parameters... -
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mistletoe
A fast, extensible and spec-compliant Markdown parser in pure Python
mistletoe is a Markdown parser in pure Python, designed to be fast, spec-compliant and fully customizable. Apart from being the fastest CommonMark-compliant Markdown parser implementation in pure Python, mistletoe also supports easy definitions of custom tokens. Parsing Markdown into an abstract syntax tree also allows us to swap out renderers for different output formats, without touching any of the core components. -
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EllipsisNotation.jl
Julia-based implementation of ellipsis array indexing notation
Julia-based implementation of ellipsis array indexing notation. This implements the notation .. for indexing arrays. It's similar to Python, in that it means "all the columns before (or after)". Note: .. slurps dimensions greedily, meaning that the first occurrence of .. in an index expression creates as many slices as possible. Other instances of .. afterward are treated simply as slices. Usually, you should only use one instance of .. in an indexing expression to avoid possible confusion. -
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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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pyserde
Yet another serialization library on top of dataclasses
Yet another serialization library on top of data classes, inspired by serde-rs. Declare a class with pyserde's @serde decorator. -
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Cloudberry
One advanced and mature open-source MPP
Apache Cloudberry is a distributed real-time analytics engine designed for querying massive social media datasets. It integrates with Apache AsterixDB and supports efficient ad-hoc queries and aggregations across large volumes of data. Cloudberry is especially useful for dashboards, trend analysis, and time-series social data exploration. -
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CursusDB
CursusDB is an open-source distributed in-memory database
CursusDB is a time-series database built for high-performance analytics and data processing, optimized for handling large volumes of sequential data efficiently. -
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omegaml
MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle
omega|ml is the innovative Python-native MLOps platform that provides a scalable development and runtime environment for your Data Products. Works from laptop to cloud. -
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miepython
Mie scattering of light by perfect spheres
miepython is a pure Python module to calculate light scattering for non-absorbing, partially-absorbing, or perfectly-conducting spheres. Mie theory is used, following the procedure described by Wiscombe. This code has been validated against his results. This code provides functions for calculating the extinction efficiency, scattering efficiency, backscattering, and scattering asymmetry. Moreover, a set of angles can be given to calculate the scattering for a sphere at each of those angles. -
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CellTypist
A tool for semi-automatic cell type classification, harmonization
... and accurate prediction. Scalable and flexible. Python-based implementation is easy to integrate into existing pipelines. A community-driven encyclopedia for cell types. -
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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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DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data... -
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jello
CLI tool to filter JSON and JSON Lines data with Python syntax
Filter JSON and JSON Lines data with Python syntax. jello is similar to jq in that it processes JSON and JSON Lines data except jello uses standard python dict and list syntax. JSON or JSON Lines can be piped into jello via STDIN or can be loaded from a JSON file or JSON Lines files (JSON Lines are automatically slurped into a list of dictionaries). Once loaded, the data is available as a python list or dictionary object named '_'. Processed data can be output as JSON, JSON Lines, bash array... -
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Frouros
Frouros is an open-source Python library for drift detection
Frouros is a Python library for drift detection in machine learning systems that provides a combination of classical and more recent algorithms for both concept and data drift detection. -
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SDGym
Benchmarking synthetic data generation methods
The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from... -
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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. It’s... -
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text-dedup
All-in-one text de-duplication
text-dedup is a Python library that enables efficient deduplication of large text corpora by using MinHash and other probabilistic techniques to detect near-duplicate content. This is especially useful for NLP tasks where duplicated training data can skew model performance. text-dedup scales to billions of documents and offers tools for chunking, hashing, and comparing text efficiently with low memory usage. It supports Jaccard similarity thresholding, parallel execution, and flexible... -
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harmonypy
Integrate multiple high-dimensional datasets with fuzzy k-means
Harmony is an algorithm for integrating multiple high-dimensional datasets. harmonypy is a port of the harmony R package by Ilya Korsunsky. Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. -
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pydantic
Data parsing and validation using Python type hints
Data validation and settings management using Python type hinting. Fast and extensible, pydantic plays nicely with your linters/IDE/brain. Define how data should be in pure, canonical Python 3.6+; validate it with pydantic. id is of type int; the annotation-only declaration tells pydantic that this field is required. Strings, bytes or floats will be coerced to ints if possible; otherwise an exception will be raised. name is inferred as a string from the provided default; because it has...
