The Best 368 Analytics Libraries

368 Components & Libraries

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Analytics Repositories

Apache Spark - A unified analytics engine for large-scale data processing

Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for da…

Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.

Redash is designed to enable anyone, regardless of the level of technical sophistication, to harness the power of data big and small. SQL users leverage Redash to explore, query, visualize, and share…

🦔 PostHog provides open-source product analytics, session recording, feature flagging and A/B testing that you can self-host.

PostHog is available with hosting in the EU or US and is fully SOC 2 compliant. It's free to get started and comes with a generous monthly free tier: We're constantly adding new features, with web an…

An orchestration platform for the development, production, and observation of data assets.

With Dagster, you declare—as Python functions—the data assets that you want to build. Dagster then helps you run your functions at the right time and keep your assets up-to-date. Here is an example o…

Modin: Scale your Pandas workflows by changing a single line of code

By simply replacing the import statement, Modin offers users effortless speed and scale for their pandas workflows: If you want to install Modin with a specific engine, we recommend: Modin automatica…

A data visualization and analytics component, especially well-suited for large and/or streaming datasets.

Portfolio and risk analytics in Python

At the core of pyfolio is a so-called tear sheet that consists of various individual plots that provide a comprehensive image of the performance of a trading algorithm. Here's an example of a simple …

A Python based monitoring and tracking tool for Plex Media Server.

This is free software under the GPL v3 open source license. Feel free to do with it what you wish, but any modification must be open sourced. A copy of the license is included.

An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs for Scala, Java, Rust, Ruby, and Python.

There are two types of APIs provided by the Delta Lake project. Delta Lake guarantees backward compatibility for all Delta Lake tables (i.e., newer versions of Delta Lake will always be able to read …

Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.

There are many ways to get involved in Flyte, including: Flyte is available under the Apache License 2.0. Use it wisely.

Portfolio analytics for quants, written in Python

Here's an example of a simple tear sheet analyzing a strategy: Output: Output: You can create 7 different report tearsheets: Let' create an html tearsheet Output will generate something like this: P…

DevSecOps, ASPM, Vulnerability Management. All on one platform.

DefectDojo is maintained by: Core Moderators can help you with pull requests or feedback on dev ideas: Moderators can help you with pull requests or feedback on dev ideas:

Modern, privacy-friendly, and detailed web analytics that works without cookies or JS.

Not shown: management view, session view, full service view. (You'll need to install Shynet for yourself to see those!) Here's the information Shynet can give you about your visitors: Shynet isn't f…

Carefully curated resource links for data science in one place

A trove of carefully curated resources and links (on the topics of software, platforms, language, techniques, etc.) related to data science, all in one place. Homework 3

Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray

Then, define the BigDL model using Keras-style API:

An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈

These three functionalities enable a variety of use cases for data scientists, machine learning engineers, and data engineers: From here, you can quickly log a dataset: And there you have it, you now…

Expressive analytics in Python at any scale.

Ibis is a Python library that provides a lightweight, universal interface for data wrangling. It helps Python users explore and transform data of any size, stored anywhere. Ibis has three primary com…

LakeSoul is an end-to-end, realtime and cloud native Lakehouse framework with fast data ingestion, concurrent update and incremental data analytics on cloud storages for both BI and AI applications.

LakeSoul is a cloud-native Lakehouse framework that supports scalable metadata management, ACID transactions, efficient and flexible upsert operation, schema evolution, and unified streaming & ba…

A powerful data & AI notebook templates catalog: prompts, plugins, models, workflow automation, analytics, code snippets - following the IMO framework to be searchable and reusable in any context.

(aka the "awesome-notebooks") The objective of this repository is to create the largest catalog of production-ready Jupyter Notebooks templates. With those templates, it becomes easy to create data p…

The purpose of this project is to share knowledge on how awesome Streamlit is and can be

This project provides This repo is maintained by me :-) Thanks In the pull request you should Thanks. In the pull request you should Please note that your app should not require high compute power as…

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

Graphistry gets used on problems like visually mapping the behavior of devices and users, investigating fraud, analyzing machine learning results, and starting in graph AI. It provides point-and-clic…

A site that displays up to date COVID-19 stats, powered by fastpages.

The content of this site shows statistics and reports regarding Covid-19.

[UNMAINTAINED] Automated machine learning for analytics & production

Automated machine learning for production and analytics auto_ml is designed for production. Here's an example that includes serializing and loading the trained model, then getting predictions on sing…

Open Source Pricing & Packaging Infrastructure

Lotus is a pricing and billing engine that enables SaaS companies to deploy, monitor, and experiment with custom subscriptions and complex models like usage-based pricing. Lotus provides a flexible a…

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.

Text analytics can be a bit overwhelming and frustrating at times with the unstructured and noisy nature of textual data and the vast amount of information available. "Text Analytics with Python" is …

Diskover Community Edition - Open source file indexer, file search engine and data management and analytics powered by Elasticsearch

diskover is an open source file system indexer that uses Elasticsearch to index and manage data across heterogeneous storage systems. Using diskover, you are able to more effectively search and organ…

:zap: Data quality management for SQL, Spark, and Pandas-accessible data

Soda Core is a free, open-source, command-line tool that enables you to use the Soda Checks Language to turn user-defined input into aggregated SQL queries. When it runs a scan on a dataset, Soda Cor…

Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.

A collection of Python demos for spatial data analytics, geostatistics and machine learning methods. Please cite as: I use these demonstrations for: Other resources that you might be interested in in…

An end-to-end GoodReads Data Pipeline for Building Data Lake, Data Warehouse and Analytics Platform.

Pipeline Consists of various modules: EMR - I used a 3 node cluster with below Instance Types: Finally, pyspark uses python2 as default setup on EMR. To change to python3, setup environment variable…

Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

With Intel(R) Extension for Scikit-learn, you can: To install Intel(R) Extension for Scikit-learn, run: The software acceleration is achieved through patching. It means, replacing the stock scikit-le…