To plot magintude spectrum, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Get random seed value.Initialize dt for sampling interval and find the sampling frequency.Create random data points for t.To generate noise, get nse, r, cnse and s using numpyCreate a figure and a set of subplots, using subplots() method.Set the title of the plot.Plot the magnitude spectrum.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True np.random.seed(0) dt = 0.01 # sampling interval Fs = ... Read More

To get the signal plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Get random seed value.Initialize dt for sampling interval and find the sampling frequency.Create random data points for t.To generate noise, get nse, r, cnse and s using numpy.Create a figure and a set of subplots using subplots() method.Set the title of the plot.Plot t and s data points.Set x and y labels.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True np.random.seed(0) dt ... Read More

To tweak axis labels and names orientation for 3D plots 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 with facecolor=white.Get the current figure with 3d projection.Set X, Y and Z Axis labels with linespacing.Plot the data points using plot() method.Set the axis distance.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 figure = plt.figure(facecolor='w') ax = figure.gca(projection='3d') xLabel = ax.set_xlabel('X-axis', linespacing=3.2) yLabel = ax.set_ylabel('Y-axis', linespacing=3.1) zLabel = ax.set_zlabel('Z-Axis', ... Read More

To plot scatter points with clover symbols in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create x, y and z data points using numpy.Plot x, y and s using scatter() method.Set X and Y axes labels.Place a legend at the upper left of the plot.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.arange(0.0, 50.0, 2.0) y = x ** 1.3 + np.random.rand(*x.shape) * 30.0 s = np.random.rand(*x.shape) * 800 + 500 ... Read More

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 More

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 More

To put gap between Y-axis and the first bar in vertical barchart, we can reduce the X-axis scale.StepsSet the figure size and adjust the padding between and around the subplots.Create lists x_val, x_names andvaldata points. Also, initialize width and interval variables.Make a bar plot using bar() method.Get or set the current tick locations and labels of the X-axis.Get or set the current tick locations and labels of the Y-axis.Get or set the x limits of the current axes.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x_val = ... Read More

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 More

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 More

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 More