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To preserve padding while setting axis limit, we can avoid using the tight layout, i.e., plt.rcParams["figure.autolayout"] = False.StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Plot x and y data points using plot() method.Set x and y axes limit.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(-10, 10, 100) y = np.sin(x) ** 2 plt.plot(x, y) plt.xlim([0, max(x)+0.125]) plt.ylim([0, max(y)+0.125]) plt.show() OutputIt will produce the following output −Read More
To show (0, 0) on matplotlib graph at the bottom left corner, we can use xlim() and ylim() methods.StepsSet the figure size and adjust the padding between and around the subplots.Make lists of data points for x and y.Plotx and y data points.Setx and y axes scale.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.array([0, 1, 3, 2, 1, 5]) y = np.array([0, 2, 4, 4, 3, 3]) plt.plot(x, y) plt.xlim([0, max(x)+0.5]) plt.ylim([0, max(y)+0.5]) plt.show() OutputIt will produce the ... Read More
To make graph k-NN decision boundaries in matplotlib, we can take the following Steps.StepsSet the figure size and adjust the padding between and around the subplots.Initialize a variable n_neighbors for number of neighbors.Load and return the iris dataset (classification).Create x and y data points.Make lists of dark and light colors.Classifier implementing the k-nearest neighbors vote.Create xmin, xmax, ymin and ymax data points.Create a new figure or activate an existing figure.Create a contourf plot.Create a scatter plot with X dataset.Set x and y axes labels, titles and scale of the axes.To display the figure, use Show() method.Exampleimport numpy as np import ... Read More
To make a mosaic plot in matplotlib, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Install statsmodel package (pip install statsmodels). It is required to create mosaic plots. statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation and inference for statistical models.Make a dictionary for mosaic plot.Create a mosaic plot from a contingency table.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt from statsmodels.graphics.mosaicplot import mosaic plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Dictionary for mosaic plot ... Read More
To plot two violin plot series on the same graph using Seaborn, we can take the following Steps.StepsSet the figure size and adjust the padding between and around the subplots.Load an example dataset from the online repository (requires Internet).Create a violin plot using violinplot() method.To display the figure, use Show() method.Example# Import Seaborn and Matplotlib import seaborn as sns from matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Load an example dataset tips = sns.load_dataset("tips") # Create a violin plot using Seaborn sns.violinplot(x="day", y="total_bill", hue="time", data=tips) ... Read More
The ngMaxlength Directive in AngularJS adds the maxlength validator to the ngModel. This directive is mostly used to control the text-based inputs but can also be applied for controlling the custom text-based controls.This validator sets the maxlength error key if the value ngModel.$viewValue is longer than the integer value obtained by evaluating the Angular JS expression defined in the ngMaxlength attribute value.Syntax..content..Example − ngMaxlength DirectiveCreate a file "ngMaxlength.html" in your Angular project directory and copy-paste the following code snippet. ngMaxlength Directive ... Read More
To autosize text in matplotlib, we can make a tight layout and rotate the ticks.StepsSet the figure size and adjust the padding between and around the subplots.Plot data points of the range of 10.Make a list of labels.Put ticks and labels on the X-axis with 30 rotation.To display the figure, use Show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True plt.plot(range(10)) labels = [7 * repr(i) for i in range(10)] plt.xticks(range(10), labels, rotation=30) plt.show() OutputIt will produce the following output −
To change the scale of imshow in matplotlib without stretching the image, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Create random data points with 4×4 dimension.Display the data as an image, i.e., on a 2D regular raster.Use the extent parameter of imshow to map the image buffer pixel coordinates to a data space coordinate system.Next, set the aspect ratio of the image manually by supplying a value such as "aspect=4" or let it auto-scale by using aspect='auto'. This will prevent stretching of the image. By default, imshow sets the aspect of ... Read More
The ng-style Directive in AngularJS helps you to set the CSS style of an HTML element conditionally. If the condition evaluates to True, the style will be applied. The expression inside the ng-style directive must be an object. This is supported by all the HTML elements.Syntax..content..Example − ngStyle DirectiveCreate a file "ngStyle.html" in your Angular project directory and copy-paste the following code snippet. ngStyle Directive span { color: black; } ... Read More
To use ax.get_ylim() method in matplotlib, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Create random data points using numpy.Plot y data points using plot() method.Use ax.get_ylim() method to print it.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 fig = plt.figure() # Add an axes to the figure ax = fig.add_subplot(1, 1, 1) ... Read More