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  2. Wikipedia : How to create charts for Wikipedia articles

    en.wikipedia.org/wiki/Wikipedia:How_to_create...

    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. A simple SVG line plot with Matplotlib. Here is a minimal line plot (output image is shown on the right):

  3. Matplotlib - Wikipedia

    en.wikipedia.org/wiki/Matplotlib

    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.

  4. Scatter plot - Wikipedia

    en.wikipedia.org/wiki/Scatter_plot

    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.

  5. File:Mpl example scatter plot.svg - Wikipedia

    en.wikipedia.org/wiki/File:Mpl_example_scatter...

    Source code has been (very) slightly modified into fully object-oriented matplotlib interface. A pseudo-random generator is used with a constant seed to ensure reproducibility when updating in the futre. The original shebang was also removed. The matplotlib (mpl) version is 1.5.3, with Python 2.7 and numpy 1.10

  6. Plotly - Wikipedia

    en.wikipedia.org/wiki/Plotly

    Plotly was founded by Alex Johnson, Jack Parmer, Chris Parmer, and Matthew Sundquist. [2]The founders' backgrounds are in science, energy, and data analysis and visualization. [2]

  7. Scatterplot smoothing - Wikipedia

    en.wikipedia.org/wiki/Scatterplot_smoothing

    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 .

  8. Principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Principal_component_analysis

    Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.

  9. Root locus analysis - Wikipedia

    en.wikipedia.org/wiki/Root_locus_analysis

    The root locus plots the poles of the closed loop transfer function in the complex s-plane as a function of a gain parameter (see pole–zero plot). Evans also invented in 1948 an analog computer to compute root loci, called a "Spirule" (after "spiral" and " slide rule "); it found wide use before the advent of digital computers .