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Articles by Rishikesh Kumar Rishi
Page 44 of 102
What's the difference between Matplotlib.pyplot and Matplotlib.figure?
matplotlib.pyplotThe matplotlib.pyplot is a collection of functions that make matplotlib work like MATLAB. Each pyplot function makes some change to a figure: e.g., creates a figure, creates a plotting area in a figure, plots some lines in a plotting area, decorates the plot with labels, etc.In matplotlib.pyplot, various states are preserved across function calls, so that it keeps track of things like the current figure and plotting area, and the plotting functions are directed to the current axesmatplotlib.figureThe figure keeps track of all the child Axes, a smattering of 'special' artists (titles, figure legends, etc), and the canvas. A figure ...
Read MoreHow to pass RGB color values to Python's Matplotlib eventplot?
To pass RGB color values to Python's Matplotlib eventplot, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a 1D array, pos, to define the positions of one sequence of eventsMake a list of color tuple r, g, b.Plot identical parallel lines at the given positions.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True pos = 10 * np.random.random(100) colors = [(0.75, 0.50, 0.25)] plt.eventplot(pos, orientation='horizontal', linelengths=0.75, color=colors) ...
Read MoreHow to embed fonts in PDFs produced by Matplotlib
To embed fonts in PDFs produced by Matplotlib, we can use rc.Params['pdf.fonttype']=42.StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure, using figure() method.Create x and y data points using numpy.Plot x and y data points using scatter() method.Set the title of the plot.Save the figure in pdf format.Exampleimport numpy as np from matplotlib import pyplot as plt, font_manager as fm plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True plt.rcParams['pdf.fonttype'] = 42 fig, ax = plt.subplots() x = np.random.rand(100) y = np.random.rand(100) ax.scatter(x, y, c=y, marker="v") ...
Read MoreHow to animate the colorbar in Matplotlib?
To animate the colorbar in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Add an '~.axes.Axes' to the figure as part of a subplot arrangement.Instantiate Divider based on the pre-existing axes, i.e., ax object and return a new axis locator for the specified cell.Create an axes at the given *position* with the same height (or width) of the main axes.Create random data using numpy.Use imshow() method to plot random data.Set the title of the plot.Instantiate the list of colormaps.To animate the ...
Read MoreMatplotlib animation not working in IPython Notebook?
To animate a plot in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a random data of shape 10X10 dimension.Create a figure and a set of subplots, using subplots() method.Makes an animation by repeatedly calling a function *func*, using FuncAnimation() class.To update the contour value in a function, we can define a method animate that can be used in FuncAnimation() class.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import matplotlib.animation as animation plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = ...
Read MoreHow to display the count over the bar in Matplotlib histogram?
To display the count over the bar in matplotlib histogram, we can iterate each patch and use text() method to place the values over the patches.StepsSet the figure size and adjust the padding between and around the subplots.Make a list of numbers to make a histogram plot.Use hist() method to make histograms.Iterate the patches and calculate the mid-values of each patch and height of the patch to place a text.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = [3, 5, 1, 7, 9, 5, 3, 7, 5] _, ...
Read MoreHow to replace auto-labelled relative values by absolute values in Matplotlib?
To replace auto-labelled relayive values by absolute values in matplotlib, we can use autopct=lambda p: .StepsSet the figure size and adjust the padding between and around the subplots.Make lists of labels, fractions, explode position and get the sum of fractions to calculate the percentage.Make a pie chart using labels, fracs and explode with autopct=lambda p: .To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True labels = ('Read', 'Eat', 'Sleep', 'Repeat') fracs = [5, 3, 4, 1] total = sum(fracs) explode = (0, 0.05, 0, 0) plt.pie(fracs, explode=explode, labels=labels, ...
Read MoreHow to make simple double head arrows on the axes in Matplotlib?
To make simple double head arrows on the axes in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Use annotate() method to annotate the point xy with text='Arrows'. Start the tuple and end it for positions. In arrowprops dictionary, use arrowstyle "" and color='red'.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True plt.annotate('Arrows', xy=(0.1, .1), xytext=(0.5, 0.5), arrowprops=dict(arrowstyle='', color='red')) plt.show()Output
Read MoreHow to add legends and title to grouped histograms generated by Pandas? (Matplotlib)
To add legends and title to grouped histograms generated by Pandas, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe with "a", "b", "c" and "d" keys.Plot data frame with kind="hist"Set a title for the axes.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import pandas as pd plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame({'a': [1, 1, 1, 1, 3], 'b': [1, 1, 2, 1, 3], 'c': [2, 2, 2, 1, 3], 'd': [2, 1, 2, 1, 3], }) df.plot(kind='hist') plt.title("Grouped Histograms") plt.show()Output
Read MorePlot scatter points on polar axis in Matplotlib
To plot scatter points on polar axis in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize a variable, N, for number of sample data.Get r, theta, area and color data using numpyCreate a new figure or activate an existing figure.Plot theta, r, colors and area, using scatter() method.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True N = 150 r = 2 * np.random.rand(N) theta = 2 * np.pi * np.random.rand(N) area = 200 ...
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