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Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
Since 7 October 2024, Python 3.13 is the latest stable release, and it and, for few more months, 3.12 are the only releases with active support including for bug fixes (as opposed to just for security) and Python 3.9, [55] is the oldest supported version of Python (albeit in the 'security support' phase), due to Python 3.8 reaching end-of-life.
Python and Matplotlib are cross-platform, and are therefore available for Windows, OS X, and the Unix-like operating systems like Linux and FreeBSD. Matplotlib can create plots in a variety of output formats, such as PNG and SVG. Matplotlib mainly does 2-D plots (such as line, contour, bar, scatter, etc.), but 3-D functionality is also available.
Numeric literals in Python are of the normal sort, e.g. 0, -1, 3.4, 3.5e-8. Python has arbitrary-length integers and automatically increases their storage size as necessary. Prior to Python 3, there were two kinds of integral numbers: traditional fixed size integers and "long" integers of arbitrary size.
This free software had an earlier incarnation, Macsyma. Developed by Massachusetts Institute of Technology in the 1960s, it was maintained by William Schelter from 1982 to 2001. In 1998, Schelter obtained permission to release Maxima as open-source software under the GNU General Public license and the source code was released later that year ...
DOT is a graph description language, developed as a part of the Graphviz project. DOT graphs are typically stored as files with the .gv or .dot filename extension — .gv is preferred, to avoid confusion with the .dot extension used by versions of Microsoft Word before 2007.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
The algorithm for computing a dot plot is closely related to kernel density estimation. The size chosen for the dots affects the appearance of the plot. Choice of dot size is equivalent to choosing the bandwidth for a kernel density estimate. In the R programming language this type of plot is also referred to as a stripchart [3] or stripplot. [4]