Programming Articles - Page 1318 of 3363

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

To get a 3D plot, we can use fig.add_subplot(111, projection='3d') method to instantiate the axis. After that, we can use the scatter method to draw different data points on the x, y, and z axes.StepsCreate a new figure, or activate an existing figure.Add an `~.axes.Axes` to the figure as part of a subplot arrangement, where nrows = 1, ncols = 1, index = 1 and projection is ‘3d’.Iterate a list of marks, xs, ys and zs, to make scatter points.Set x, y, and z labels using set_xlabel, y_label, and z_label methods.Use plt.show() method to plot the figure.Exampleimport matplotlib.pyplot as plt import ... 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

First, we can define our dictionary and then, convert that dictionary into keys and values. Finally, we can use the data to plot a bar chart.StepsCreate a dictionary, i.e., data, where milk and water are the keys.Get the list of keys of the dictionary.Get the list of values of the dictionary.Plot the bar using plt.bar().Using plt.show(), show the figure.Exampleimport matplotlib.pyplot as plt data = {'milk': 60, 'water': 10} names = list(data.keys()) values = list(data.values()) plt.bar(range(len(data)), values, tick_label=names) plt.show()Output

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