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First, we can create an image using imshow method, taking a harvest matrix. After that, we can mark those image pixels with some value.StepsCreate a list of subjects.Create a list of students.Create a harvest matrix.Create fig and ax variables using subplots method, where default nrows and ncols are 1.Display data as an image, i.e., on a 2D regular raster, with step 1 data.Get or set the current tick locations and labels of the X-axis, with the length of students.Get or set the current tick locations and labels of the Y-axis, with the length of subjects.Set X-axis tick labels of the ... Read More
Using imshow method, we can create an image with an input (5, 5) array dimension. After that, we can use the xticks and yticks method to mark the ticks on the axes.StepsReturn random floats in the half-open interval [5, 5) and interpolation='nearest'.Display data as an image, i.e., on a 2D regular raster, with step 1 data.Get or set the current tick locations and labels of the X-axis, using xticks method.Get or set the current tick locations and labels of the Y-axis, using yticks method.Use plt.show() to show the figure.Exampleimport matplotlib.pyplot as plt import numpy as np plt.imshow(np.random.random((5, 5)), interpolation='nearest') ... Read More
Using plt.xticks(x, labels, rotation='vertical'), we can rotate our tick’s label.StepsCreate two lists, x, and y.Create labels with a list of different cities.Adjust the subplot layout parameters, where bottom = 0.15.Add a subplot to the current figure, where nrow = 1, ncols = 2 and index = 1.Plot the line using plt.plot(), using x and y (Step 1).Get or set the current tick locations and labels of the X-axis. Pass no arguments to return the current values without modifying them, with x and label data.Set or retrieve auto-scaling margins, value is 0.2.Set the title of the figure at index 1, the ... Read More
Using plt.colorbar(ticks=np.linspace(-2, 2, 5)), we can create a discrete color bar.StepsReturn random floats in the half open interval, i.e., x, using np.random.random method.Return random floats in the half open interval, i.e., y, using np.random.random method.Return random integers from `low` (inclusive) to `high` (exclusive), i.e., z, using np.random.randint(-2, 3, 20) method.Set the X-axis label using plt.xlabel().Set the Y-axis label using plt.ylabel().Use the built-in rainbow colormap.Generate a colormap index based on discrete intervals.A scatter plot of *y* vs. *x* with varying marker size and/or color, with x, y and z are created (Steps 1, 2, 3).Create a colorbar for a ScalarMappable instance, ... Read More
Using plt.get_current_fig_manager() and mng.full_screen_toggle() methods, we can maximise a plot.StepsAdd a subplot to the current figure, where nrow = 1, ncols = 1 and index = 1.Create a pie chart using list [1, 2, 3] and pie() method.Return the figure manager of the current figure, using get_current_fig_manager() method. The figure manager is a container for the actual backend-depended window that displays the figure on the screen.Create an abstract base class to handle drawing/rendering operations using the full_screen_toggle() method.Use plt.show() to show the figure.Exampleimport matplotlib.pyplot as plt plt.subplot(1, 1, 1) plt.pie([1, 2, 3]) mng = plt.get_current_fig_manager() mng.full_screen_toggle() plt.show()OutputRead More
First, we can create two axes using the subplot method where nrows=2, ncols=1. That means, we can have two indices to plot the desired plot. We can use ax1.get_shared_x_axes().join(ax1, ax2) method for our plot.StepsCreate two lists of the numbers.Add a subplot to the current figure, ax1, where nrows = 2, ncols = 1, and index is 1 for ax1.Add a subplot to the current figure, ax2, where nrows = 2, ncols = 1, and index is 2 for ax2.Plot x and y using points that are created in step 1.Using get_shared_x_axes().join(ax1, ax2), return a reference to the shared axes Grouper ... Read More
In this program, we can initialize some input values and then try to plot a bar using those values. We can instantiate a figure and axis so that we could set the label, ticks, and annotate the height and width of the bar.StepsMake a list of years.Make a list of populations in that year.Get the number of labels using np.arrange(len(years)) method.Set the width of the bars.Create fig and ax variables using subplots() method, where default nrows and ncols are 1.Set the Y-axis label of the figure using set_ylabel().Set the title of the figure, using set_title().Set the X-ticks with x that ... Read More
Log helps to make a plot with log scaling on both the X and Y axis, whereas symlog (symmetric log) is used for axis scaling.StepsFirst, we can adjust the subplot layout parameters.Return an evenly spaced value (t) within a given interval, using the numpy.arrange() method.Add a subplot to the current figure, with nrows = 1, ncols = 2 and current index is 1.Make a plot with log scaling on the Y axis, using the semilogy() method.Set the title for the axes, using the plt.title() method.Configure the grid lines, using the grid(True) method.Create two evenly spaced values within a given interval ... Read More
We can plot a diagram where a number of students will be plotted on the X-axis and the marks obtained by them will be plotted on the Y-axis. Also, we can set the color for different marks obtained by the students.StepsMake a list of the number of students.Make a list of marks that have been obtained by the students.To represent the color of each scattered point, we can have a list of colors.Using Panda, we can have a list representing the axes of the data frame.Create fig and ax variables using subplots method, where default nrows and ncols are 1.Set ... Read More
Let’s understand the difference between plot, axes, and figure with an example.Plot − Plot helps to plot just one diagram with (x, y) coordinates.Axes − Axes help to plot one or more diagrams in the same window and sets the location of the figure.Figure − This method provides a top-level container for all the plot elements.We can follow these steps to replicate the differences among them −Create a new figure, or activate an existing figure, using plt.figure().Add an axis to the figure as part of a subplot arrangement, using plt.add_subplot(xyz) where x is nrows, y is ncols and z is ... Read More