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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.
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.
Veusz is a free scientific graphing tool that can produce 2D and 3D plots. Users can use it as a module in Python. GeoGebra is open-source graphing calculator and is freely available for non-commercial users. WebPlotDigitizer, PlotDigitizer's online free app or SplineCloud's plot digitizer can be used to extract data from charts.
Gnuplot allows the user to display or store plots in several ways: [23] [24] On the console, such as dumb, sixel. In a desktop window, such as Qt, wxt, X11, aquaterm, win. Embedded in a web page, such as SVG, HTML5, PNG, JPEG, animated GIF. File formats designed for document processing, such as PostScript, PDF, cgm, emf, LaTeX variants.
A scatter plot, also called a scatterplot, scatter graph, scatter chart, scattergram, or scatter diagram, [2] is a type of plot or mathematical diagram using Cartesian coordinates to display values for typically two variables for a set of data. If the points are coded (color/shape/size), one additional variable can be displayed.
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Chart Studio Cloud is a free, online tool for creating interactive graphs. It has a point-and-click graphical user interface for importing and analyzing data into a grid and using stats tools. [ 13 ] Graphs can be embedded or downloaded.
This line attempts to display the non-random component of the association between the variables in a 2D scatter plot. Smoothing attempts to separate the non-random behaviour in the data from the random fluctuations, removing or reducing these fluctuations, and allows prediction of the response based value of the explanatory variable .