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  2. Statistical graphics - Wikipedia

    en.wikipedia.org/wiki/Statistical_graphics

    Whereas statistics and data analysis procedures generally yield their output in numeric or tabular form, graphical techniques allow such results to be displayed in some sort of pictorial form. They include plots such as scatter plots , histograms , probability plots , spaghetti plots , residual plots, box plots , block plots and biplots .

  3. Wikipedia:Graphs and charts - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Graphs_and_charts

    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.

  4. Comparison of numerical-analysis software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_numerical...

    Integrated data analysis graphing software for science and engineering. Flexible multi-layer graphing framework. 2D, 3D and statistical graph types. Built-in digitizing tool. Analysis with auto recalculation and report generation. Built-in scripting and programming languages. Perl Data Language: Karl Glazebrook 1996 c. 1997 2.080 28 May 2022: Free

  5. Plot (graphics) - Wikipedia

    en.wikipedia.org/wiki/Plot_(graphics)

    Scatterplot : A scatter graph or scatter plot is a type of display using variables for a set of data. The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis. [8]

  6. Point and figure chart - Wikipedia

    en.wikipedia.org/wiki/Point_and_figure_chart

    Point and figure (P&F) is a charting technique used in technical analysis. Point and figure charting does not plot price against time as time-based charts do. Instead it plots price against changes in direction by plotting a column of Xs as the price rises and a column of Os as the price falls. [1] [2]

  7. Empirical distribution function - Wikipedia

    en.wikipedia.org/.../Empirical_distribution_function

    Statsmodels, we can use statsmodels.distributions.empirical_distribution.ECDF; Matplotlib, using the matplotlib.pyplot.ecdf function (new in version 3.8.0) [7] Seaborn, using the seaborn.ecdfplot function; Plotly, using the plotly.express.ecdf function; Excel, we can plot Empirical CDF plot; ArviZ, using the az.plot_ecdf function

  8. SymPy - Wikipedia

    en.wikipedia.org/wiki/SymPy

    SymPy is an open-source Python library for symbolic computation.It provides computer algebra capabilities either as a standalone application, as a library to other applications, or live on the web as SymPy Live [2] or SymPy Gamma. [3]

  9. Glyph (data visualization) - Wikipedia

    en.wikipedia.org/wiki/Glyph_(data_visualization)

    These visual objects are collectively called a glyph. It helps visualizing data relation in data analysis, statistics, etc. by using any custom notation. In the context of data visualization, a glyph is the visual representation of a piece of data where the attributes of a graphical entity are dictated by one or more attributes of a data record.