Open Source Python Information Analysis Software for Mac

SciDAVis is a user-friendly data analysis and visualization program primarily aimed at high-quality plotting of scientific data. It strives to combine an intuitive, easy-to-use graphical user interface with powerful features such as Python scriptability.

Open source machine learning and data visualization. Build data analysis workflows visually, with a large, diverse toolbox. Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. Place widgets on the canvas, connect them, load your datasets and harvest the insight! When teaching data mining, we like to illustrate rather than only explain.

Grafana OSS is a leading open-source visualization and observability platform that lets you query, visualize, alert on, and explore your data—regardless of where it’s stored. With support for 100+ data source plugins (such as Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, OTel, and more), you can unify metrics, logs, traces, and other observability signals in one place. Grafana OSS empowers you to build dynamic, reusable dashboards with rich visualizations, template variables, interactive filtering, and cross-panel linking. Its Explore mode enables ad-hoc queries and side-by-side comparisons of time ranges, queries, and data sources. Grafana also includes built-in alerting, allowing you to define threshold-based rules and send notifications to external systems (e.g. Slack, PagerDuty, OpsGenie). Backed by a strong community (https://grafana.com/community/) and open governance, Grafana OSS is free to use, modify, and deploy under the AGPL-3.0 license.

IRAMUTEQ : Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires. Logiciel de traitement de données pour des corpus texte ou de type individus/caractères. Permet notamment de réaliser des analyses de type "ALCESTE"

LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.

QtiPlot is a user-friendly, platform independent data analysis and visualization application similar to the non-free Windows program Origin.

A lightweight and powerful python module for scientific analysis and visualization of 3d objects. Inspired by the vpython manifesto "3D programming for ordinary mortals", vedo makes it easy to work with 3D pointclouds, meshes and volumes, in just a few lines of code, even for less experienced programmers. vedo is based on VTK and numpy, with no other dependencies. Import meshes from VTK format, STL, Wavefront OBJ, 3DS, Dolfin-XML, Neutral, GMSH, OFF, PCD (PointCloud). Export meshes as ASCII or binary to VTK, STL, OBJ, PLY formats. Analysis tools like Moving Least Squares, mesh morphing and more. Tools to visualize and edit meshes (cutting a mesh with another mesh, slicing, normalizing, moving vertex positions, etc..). Split mesh based on surface connectivity. Extract the largest connected area. Calculate areas, volumes, center of mass, average sizes etc. Calculate vertex and face normals, curvatures, feature edges. Fill mesh holes.

SPPAS is a scientific computer software package written and maintained by Brigitte Bigi of the Laboratoire Parole et Langage, in Aix-en-Provence, France. Available for free, with open source code, there is simply no other package for linguists to simple use in the automatic annotations of speech, the analyses of any kind of annotated data and the conversion of annotated files. SPPAS is able to produce automatically speech annotations from a recorded speech sound and its orthographic transcription. SPPAS is helpful for the analysis of any annotated data: estimate statistical distributions, make requests, manage files, visualize annotations. SPPAS offers a file converter from/to a wide range of formats: xra, TextGrid, eaf, trs... <https://sppas.org>

*asammdf* is a fast Python parser and editor for ASAM (Associtation for Standardisation of Automation and Measuring Systems) MDF / MF4 (Measurement Data Format) files. It supports MDF versions 2 (.dat), 3 (.mdf) and 4 (.mf4). *asammdf* works on Python 2.7, and Python >= 3.4

A windrose, also know as polar rose plot, is a special diagram for representing the distribution of meteorological datas, typically wind speeds by class and direction.

A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are interested in reuse, and we focus on common NLP tasks that are broadly useful for textmining.

The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded. The implementation of new algorithms is easy and intuitive. The new implemented units are then automatically integrated with the rest of the library. The base of available algorithms is steadily increasing and includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others.

Pretty Damn Quick (PDQ) analytically solves queueing network models of computer and manufacturing systems, data networks, etc., written in conventional programming languages. Generic or customized reports of predicted performance measures are output.

This is a Python-based efficient implementation of several semantic similarity measures. The target is to enable fast and easy calculation of similarity between proteins and genes using the Gene Ontology (GO).

Dowser is a research tool for the web. It clusters results from search engines, associates words that appear in previous searches, and keeps a local cache of all the results you click on in a searchable database. It helps you keep track of what you find.

Gamera is a framework for the creation of structured document analysis applications by domain experts. It combines a programming library with GUI tools for the training and interactive development of recognition systems.

PyPotrace is a Python programming language binding for Peter Selinger's Potrace raster to vector conversion algorithm. No separate Potrace library or application required!

We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community, we-media, and online earning community, with a QQ group of more than 10,000 people and at least 10,000 subscribers. The number of Github Stars exceeds 60k, and it ranks in the top 100 of all Github organizations. The daily up of all its websites exceeds 4k, and the peak of Alexa ranking is 20k. Our core members are certified as CSDN blog experts and short-book programmers as excellent authors. We have established ApacheCN, a non-profit document, and tutorial translation project.

A.I. security app. Development ceased.

This is a prototype implementation of "A Network of Ideas" (ANOI) content system.

Using this plugin-based framework, you can instantly start working on the *brain* of your bot (irc bot, chatterbot, robot, ...). With support for db, irc, logging and programming-language independent plugins, users can easily enhance the functionality.

This is dedicated to development of a small class for organizing data in both a traditional parent<->child hierarchy and by the functions used to generate child data nodes from parent data. The core of the project is in the class definitions contained within arachne.py, a demonstration of how this method of arranging data can be used to solve a relatively interesting problem may be found in test.py

Autoplot is an interactive browser for data on the web. Give Autoplot a URL or local file name and it creates a sensible plot of the data. Autoplot allows you to interactively browse data stored in ascii, .cdf, netcdf, and many other formats. Autoplot's source has been moved to GitHub. Thanks to SourceForge for many years of hosting!

The aim of this project is to translate the geostatistical BMELib Matlab Toolbox (http://www.unc.edu/depts/case/BMELIB/) into Python.

BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.