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Page 1947 of 2109
How to set my xlabel at the end of X-axis in Matplotlib?
To set the xlabel at the end of X-axis in matplotlib, we can take the following steps −Create data points for x using numpy.Using subplot() method, add a subplot to the current figure.Plot x and log(x) using plot() method.Set the label on X-axis using set_label() method, with fontsize=16, loc=left, and color=red.To set the xlabel at the end of X-axis, use the coordinates, x and y.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(1, 2, 5) ax = plt.subplot() ax.plot(x, np.log(x)) ax.set_xticks(x) label = ax.set_xlabel('X ->', fontsize=16, loc="left", c="red") ax.xaxis.set_label_coords(1.0, -0.025) plt.show()Output
Read MoreHow to draw axis in the middle of a figure in Matplotlib?
To draw axis in the middle of a figure, we can take the following steps −Create x and sqr data points using numpy.Create a new figure, or activate an existing figure, using figure() method.Add an axis to the figure as a part of a subplot arrangement.Set the postion of left and bottom spines.Set the color of the right and top spines.Plot x and sqr, using plot() method, with label y=x2 and color=red.Place the legend using legend() method. Set the location at upper right corner.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True ...
Read MoreWhat does a 4-element tuple argument for 'bbox_to_anchor' mean in Matplotlib?
If a 4-tuple or B box Base is given, then it specifies the b box (x, y, width, height) that the legend is placed in.StepsCreate x and y data points using numpy.Plot x and y using plot() method, with label y=sin(x) and color=green.To place the legend at a specific location, use location 'upper left' and use legend box dimension with four tuples that was defined in the above description.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-2, 2, 10) y = np.sin(x) plt.plot(x, ...
Read MoreHow to make the angles in a Matplotlib polar plot go clockwise with 0° at the top?
To make the angles in a matplotlib polar plot go clockwise with 00 at the top, we can take the followingsteps−StepsAdd a subplot to the current figure ax.To set polar plot clockwise with top 0o, set the theta direction as −1 using set_theta_direction()method. And, use set_theta_offset() method to set the offset for the location of 0 in radians.Create theta, using numpy.Plot theta and sin(theta) on the current axis.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True ax = plt.subplot(1, 1, 1, projection='polar') ax.set_theta_direction(-1) ax.set_theta_offset(np.pi / 2.0) ...
Read MoreEquivalent to matlab's imagesc in Matplotlib
To make equivalent imagesc, we can use extent [left, right, bottom, top].StepsCreate random data using numpy.Display the data as an image, i.e., on a 2D regular raster, with data and extent [−1, 1, −1, 1] arguments.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True data = np.random.rand(4, 4) plt.imshow(data, extent=[-1, 1, -1, 1]) plt.show()Output
Read MoreShading an area between two points in a Matplotlib plot
To shade an area between two points in matplotlib, we can take the following steps−Create x and y data points using numpy.Plot x and y data points, with color=red and linewidth=2.To shade an area parallel to X-axis, initialize two variables, y1 and y2.To add horizontal span across the axes, use axhspan() method with y1, y2, green as shade color, and alpha for transprency of the shade.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(0, 20, 500) y = np.cos(3*x) + np.sin(2*x) plt.plot(x, y, c='red', lw=2) ...
Read MoreCreating a graph with date and time in axis labels with Matplotlib
To create a graph with date and time in axis labels, we can take the following steps−Create a figure and add a set of subplots.Create x and y data points using numpy.Set date formatter for X-axis.Plot x and y using plot() method.Set the ticks of X-axis.Set the date-time tick labels for X-axis, with some rotation.Make the plot tight layout using plt.tight_layout() method.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt, dates import datetime import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() x = np.array([datetime.datetime(2021, 1, 1, i, 0) for i ...
Read MoreHow to plot 1D data at a given Y-value with PyLab using Matplotlib?
To plot 1D data at a given Y-value with pyplot, we can take the following steps−Initialize y value.Create x and y data points using numpy. zeros_like helps to return an array of zeros with the same shape and type as a given array and add y-value for y data points.Plot x and y with linestyle=dotted, color=red, and linewidth=5.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True y_value = 1 x = np.arange(10) y = np.zeros_like(x) + y_value plt.plot(x, y, ls='dotted', c='red', lw=5) plt.show()Output
Read MoreMatplotlib savefig with a legend outside the plot
To save a file with legend outside the plot, we can take the following steps −Create x data points using numpy.Plot y=sin(x) curve using plot() method, with color=red, marker="v" and label y=sin(x).Plot y=cos(x), curve using plot() method, with color=green, marker="x" and label y=cos(x).To place the legend outside the plot, use bbox_to_anchor(.45, 1.15) and location="upper center".To save the figure, use savefig() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-2, 2, 100) plt.plot(x, np.sin(x), c="red", marker="v", label="y=sin(x)") plt.plot(x, np.cos(x), c="green", marker="x", label="y=cos(x)") plt.legend(bbox_to_anchor=(.45, 1.15), loc="upper center") plt.savefig("legend_outside.png")OutputWhen we execute this code, it will ...
Read MoreHow to change the scale of an existing table in Matplotlib?
To change scale of a table, we can use the scale() method. Steps −Create a figure and a set of subplots, nrows=1 and ncols=1.Create a random data using numpy.Make columns value.Make the axis tight and off.Initialize a variable fontsize to change the fontsize.To set the fontsize of the table and to scale the table, we can use 1.5 and 1.5.To display the figure, use the show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, axs = plt.subplots(1, 1) data = np.random.random((10, 3)) columns = ("Column I", "Column II", "Column III") axs.axis('tight') ...
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