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Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.
Exploratory data analysis is a technique to analyze and investigate a dataset and summarize its main characteristics. A main advantage of EDA is providing the visualization of data after conducting analysis. Tukey's championing of EDA encouraged the development of statistical computing packages, especially S at Bell Labs. [4]
A visual programming data-flow software suite with widgets for statistical data analysis, interactive data visualization, data mining, and machine learning. Origin: GUI, COM, C/ C++ and scripting: proprietary: No 1992: June 22, 2017 / 2017 SR2: Windows: Multi-layer 2D, 3D and statistical graphs for science and engineering. Built-in digitizing tool.
Interactive data visualization enables direct actions on a graphical plot to change elements and link between multiple plots. [59] Interactive data visualization has been a pursuit of statisticians since the late 1960s. Examples of the developments can be found on the American Statistical Association video lending library. [60]
Orange, a data mining, machine learning, and bioinformatics software; Pandas – High-performance computing (HPC) data structures and data analysis tools for Python in Python and Cython (statsmodels, scikit-learn) Perl Data Language – Scientific computing with Perl; Ploticus – software for generating a variety of graphs from raw data
KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.