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  2. 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.

  3. Freedman–Diaconis rule - Wikipedia

    en.wikipedia.org/wiki/Freedman–Diaconis_rule

    For a set of empirical measurements sampled from some probability distribution, the Freedman–Diaconis rule is designed approximately minimize the integral of the squared difference between the histogram (i.e., relative frequency density) and the density of the theoretical probability distribution.

  4. Inverse Gaussian distribution - Wikipedia

    en.wikipedia.org/wiki/Inverse_Gaussian_distribution

    Wald distribution using Python with aid of matplotlib and NumPy And to plot Wald distribution in Python using matplotlib and NumPy : import matplotlib.pyplot as plt import numpy as np h = plt . hist ( np . random . wald ( 3 , 2 , 100000 ), bins = 200 , density = True ) plt . show ()

  5. GNU Scientific Library - Wikipedia

    en.wikipedia.org/wiki/GNU_Scientific_Library

    The GSL can be used in C++ classes, but not using pointers to member functions, because the type of pointer to member function is different from pointer to function. [23] Instead, pointers to static functions have to be used. Another common workaround is using a functor. C++ wrappers for GSL are available.

  6. Sturges's rule - Wikipedia

    en.wikipedia.org/wiki/Sturges's_rule

    Sturges's rule [1] is a method to choose the number of bins for a histogram.Given observations, Sturges's rule suggests using ^ = + ⁡ bins in the histogram. This rule is widely employed in data analysis software including Python [2] and R, where it is the default bin selection method.

  7. Plotting algorithms for the Mandelbrot set - Wikipedia

    en.wikipedia.org/wiki/Plotting_algorithms_for...

    The top row is a series of plots using the escape time algorithm for 10000, 1000 and 100 maximum iterations per pixel respectively. The bottom row uses the same maximum iteration values but utilizes the histogram coloring method. Notice how little the coloring changes per different maximum iteration counts for the histogram coloring method plots.

  8. Chernoff face - Wikipedia

    en.wikipedia.org/wiki/Chernoff_face

    Example and code for the R statistical software environment; Example and code for Python using the matplotlib library; ChernoffFace package in Python using the matplotlib library; Function ChernoffFace in Wolfram Language (Mathematica) at Wolfram Function Repository; Example code for MATLAB using Statistics and Machine Learning Toolbox.

  9. Stem-and-leaf display - Wikipedia

    en.wikipedia.org/wiki/Stem-and-leaf_display

    A stem-and-leaf plot of prime numbers under 100 shows that the most frequent tens digits are 0 and 1 while the least is 9. A stem-and-leaf display or stem-and-leaf plot is a device for presenting quantitative data in a graphical format, similar to a histogram, to assist in visualizing the shape of a distribution.