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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. File:Sinh cosh tanh.svg - Wikipedia

    en.wikipedia.org/wiki/File:Sinh_cosh_tanh.svg

    This plot was created with Matplotlib. Source code. Python code. import numpy as np import matplotlib.pyplot as plt lim = 8 size = 5.6 fig, ax = plt. subplots ...

  4. File:Stability region for Euler method.svg - Wikipedia

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

    from pylab import linspace, pi, exp, real, imag, axis import matplotlib.path as mpath import matplotlib.patches as mpatches import matplotlib.pyplot as plt w = exp (1 j * linspace (0, 2 * pi, 200)) Path = mpath.

  5. File:Sierpinski triangle.svg - Wikipedia

    en.wikipedia.org/wiki/File:Sierpinski_triangle.svg

    from __future__ import division import matplotlib.pyplot as plt plt. figure plt. subplot (1, 1, 1) plt. axis ('off') def drawBlue (p1, p2, p3): plt. fill ([p1 [0], p2 ...

  6. Arghakhanchi 1 (constituency) - Wikipedia

    en.wikipedia.org/wiki/Arghakhanchi_1_(constituency)

    import matplotlib.pyplot as plt # Data for the financial federalism representation levels = ["Federal Government", "State/Provincial Government", "Local Government"] revenues = [60, 30, 10] # Revenue percentage distribution expenditures = [50, 40, 10] # Expenditure percentage distribution # Creating the figure and axis

  7. File:Beta distribution pdf.svg - Wikipedia

    en.wikipedia.org/wiki/File:Beta_distribution_pdf.svg

    from matplotlib.pyplot import * from numpy import linspace from scipy.stats import beta x = linspace (0, 1, 75) fig = figure ax = fig. add_subplot (111) ax. plot (x ...

  8. 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]

  9. Risch algorithm - Wikipedia

    en.wikipedia.org/wiki/Risch_Algorithm

    In symbolic computation, the Risch algorithm is a method of indefinite integration used in some computer algebra systems to find antiderivatives.It is named after the American mathematician Robert Henry Risch, a specialist in computer algebra who developed it in 1968.