Search Results for "python data analysis" - Page 4
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Showing 1473 open source projects for "python data analysis"
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Pathway
Python ETL framework for stream processing, real-time analytics, LLM
...Unlike traditional batch processing frameworks, Pathway continuously updates the results of your data logic as new events arrive, functioning more like a database that reacts in real-time. It supports Python, integrates with modern data tools, and offers a deterministic dataflow model to ensure reproducibility and correctness. -
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Dask
Parallel computing with task scheduling
Dask is a Python library for parallel and distributed computing, designed to scale analytics workloads from single machines to large clusters. It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines. -
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fluentbit
Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX
Fluent Bit is a super-fast, lightweight, and highly scalable logging and metrics processor and forwarder. It is the preferred choice for cloud and containerized environments. A robust, lightweight, and portable architecture for high throughput with low CPU and memory usage from any data source to any destination. Proven across distributed cloud and container environments. Highly available with I/O handlers to store data for disaster recovery. Granular management of data parsing and routing.... -
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DataChain
AI-data warehouse to enrich, transform and analyze unstructured data
Datachain enables multimodal API calls and local AI inferences to run in parallel over many samples as chained operations. The resulting datasets can be saved, versioned, and sent directly to PyTorch and TensorFlow for training. Datachain can persist features of Python objects returned by AI models, and enables vectorized analytical operations over them. The typical use cases are data curation, LLM analytics and validation, image segmentation, pose detection, and GenAI alignment. Datachain is especially helpful if batch operations can be optimized – for instance, when synchronous API calls can be parallelized or where an LLM API offers batch processing. -
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Semantic Type Detection
Metadata/data identification Java library
...Usable in either Streaming, Bulk or Record mode. Broad country/language support - including US, Canada, Mexico, Brazil, UK, Australia, much of Europe, Japan and China. Support for sharded analysis (i.e. Analysis results can be merged) Once stream is profiled then subsequent samples can be validated and/or new samples can be generated. -
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Matplotlib
matplotlib: plotting with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a... -
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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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MemProcFS Analyzer
Automated Forensic Analysis of Windows Memory Dumps for DFIR
MemProcFS-Analyzer is a forensic analysis toolset that builds on the MemProcFS virtual filesystem to make volatile memory artefacts easier to browse and interpret. By exposing process memory, kernel objects, and derived artifacts as regular files, the framework lets analysts use familiar filesystem operations and standard tools (editors, grep, diff) to explore memory snapshots. The Analyzer layer adds higher-level parsing and extraction routines—for example, carving strings, locating... -
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Tokenize.jl
Tokenization for Julia source code
Tokenize is a Julia package that serves a similar purpose and API as the tokenize module in Python but for Julia. This is to take a string or buffer containing Julia code, perform lexical analysis and return a stream of tokens. -
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hctsa
Highly comparative time-series analysis
hctsa is a Matlab software package for running highly comparative time-series analysis. It extracts thousands of time-series features from a collection of univariate time series and includes a range of tools for visualizing and analyzing the resulting time-series feature matrix. -
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pydna
Clone with Python! Data structures for double stranded DNA
Clone with Python! Data structures for double stranded DNA & simulation of homologous recombination, Gibson assembly, cut & paste cloning. Planning genetic constructs with many parts and assembly steps, such as recombinant metabolic pathways, are often difficult to properly document as is evident from the poor state of documentation in the scientific literature. -
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Mercury
Convert Python notebook to web app and share with non-technical users
Turn Python notebooks to web applications with open-source Mercury framework. Hide code and add interactive widgets. Non-technical users can tweak widgets and execute notebook with new parameters. The core of Mercury is Open Source under AGPLv3. We provide Mercury Pro with additional features, dedicated support and friendly commercial license. Mercury is a perfect tool to convert Python notebook to interactive web application and share with non-programmers. You define interactive widgets for... -
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MultilayerGraphs.jl
Julia package for the creation and analysis of multilayer graphs
MultilayerGraphs.jl is a Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs. A multilayer graph is a graph consisting of multiple standard subgraphs called layers which can be interconnected through bipartite graphs called interlayers composed of the vertex sets of two different layers and the edges between them. The vertices in each layer represent a single set of nodes, although not all nodes have to be represented in... -
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Dexter
An autonomous agent for deep financial research
Dexter is an autonomous agent tailored for deep financial research: you pose complex financial questions (for example, about a company’s revenue growth or financial ratios) and Dexter breaks them down into structured research tasks, fetches relevant real-time data (e.g. income statements, cash flows), performs analysis, and returns data-backed answers. It uses a multi-agent architecture with components such as a planning agent (to decompose queries), an action agent (to run tasks & fetch data), and self-validation mechanisms: after getting results, Dexter checks its own outputs and refines them until it is confident about its answer. ... -
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JILL.py
A cross-platform installer for the Julia programming language
The enhanced Python fork of JILL, Julia Installer for Linux (and every other platform), Light. -
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FinRobot
An Open-Source AI Agent Platform for Financial Analysis using LLMs
FinRobot is an open-source AI framework focused on automating financial data workflows by combining data ingestion, feature engineering, model training, and automated decision-making pipelines tailored for quantitative finance applications. It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to... -
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Metacrafter
Metadata and data identification tool and Python library
Python command line tool and Python engine to label table fields and fields in data files. It could help to find meaningful data in your tables and data files or to find Personal identifiable information (PII). Metacrafter is a rule-based tool that helps to label fields of the tables in databases. It scans table and finds person names, surnames, midnames, PII data, basic identifiers like UUID/GUID. -
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data-diff
Efficiently diff rows across two different databases
We're excited to announce the launch of a new open-source product, data-diff that makes comparing datasets across databases fast at any scale. data-diff automates data quality checks for data replication and migration. In modern data platforms, data is constantly moving between systems, and at the modern data volume and complexity, systems go out of sync all the time. Until now, there has not been any tooling to ensure that when the data is correctly copied. Replicating data at scale, across... -
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IntervalRootFinding.jl
Find all roots of a function in a guaranteed way with Julia
This package provides guaranteed methods for finding roots of functions, i.e. solutions to the equation f(x) == 0 for a function f. To do so, it uses methods from interval analysis, using interval arithmetic from the IntervalArithmetic.jl package by the same authors. The basic function is roots. A standard Julia function and an interval is provided and the roots function return a list of intervals containing all roots of the function located in the starting interval. -
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Conda.jl
https://github.com/JuliaPy/Conda.jl
This package allows one to use conda as a cross-platform binary provider for Julia for other Julia packages, especially to install binaries that have complicated dependencies like Python. conda is a package manager that started as the binary package manager for the Anaconda Python distribution, but it also provides arbitrary packages. Instead of the full Anaconda distribution, Conda.jl uses the miniconda Python environment, which only includes conda and its dependencies. -
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Plots
Powerful convenience for Julia visualizations and data analysis
Data visualization has a complicated history. Plotting software makes trade-offs between features and simplicity, speed and beauty, and a static and dynamic interface. Some packages make a display and never change it, while others make updates in real-time. Plots is a visualization interface and toolset. It sits above other backends, like GR, PythonPlot, PGFPlotsX, or Plotly, connecting commands with implementation. If one backend does not support your desired features or make the right... -
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ggstatsplot
Enhancing {ggplot2} plots with statistical analysis
{ggstatsplot} is an extension of {ggplot2} package for creating graphics with details from statistical tests included in the information-rich plots themselves. In a typical exploratory data analysis workflow, data visualization and statistical modeling are two different phases: visualization informs modeling, and modeling in its turn can suggest a different visualization method, and so on and so forth. Bayesian hypothesis-testing. The central idea of {ggstatsplot} is simple: combine these two phases into one in the form of graphics with statistical details, which makes data exploration simpler and faster. ... -
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ClimateTools.jl
Climate science package for Julia
Climate analysis tools in Julia. ClimateTools.jl is a collection of commonly-used tools in Climate science. Basics of climate field analysis are covered, with some forays into exploratory techniques associated with climate scenario design. The package is aimed to ease the typical steps of analysis of climate models outputs and gridded datasets (support for weather stations is a work-in-progress). Climate indices and bias correction functions are coded to leverage the use of multiple threads.... -
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Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative)... -
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Hyperspectral data analysis in R
Handling and basic analysis of hyperspectral data in R
The hsdar package contains classes and functions to manage, analyse and simulate hyperspectral data. These might be either spectrometer measurements or hyperspectral images through the interface of rgdal.
