To change the autopct text color to be white in a pie chart in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a list of hours, activities, and colors to plot pie chart.Make a list of '.Text' instances for the numeric labels, while making the pie chart.Iterate autotexts and set the color of autotext as white.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 plt.figure() hours = [8, 1, 11, 4] activities = ['sleeping', 'exercise', 'studying', 'working'] ... Read More

To change the size of a plot in xgboost.plot_importance, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Load the data from a csv file.Get x and y data from the loaded dataset.Get the xgboost.XGBCClassifier.feature_importances_ model instance.Fit x and y data into the model.Print the model.Make a bar plot.To display the figure, use show() method.Examplefrom numpy import loadtxt from xgboost import XGBClassifier from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # data.csv contains data like -> 13, 145, 82, 19, 110, 22.2, 0.245, 57, ... Read More

To annotate the maximum value in a Pyplot, 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.Make a list of x and y data points.Plot x and y data points using numpy.Find the maximum in Y array and position corresponding to that max element in the arrayAnnotate that point with local max.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 fig = plt.figure() ax = fig.add_subplot(111) x ... Read More

To add third level of ticks in Python Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create t and s data points using numpy.Create a figure and a set of subplots.Plot t and s using plot() method.Create a twin Axes sharing the Y-axis.Plot t and s using plot() method, on axis one.Set X-axis tick position.Create majors, minors and third level of ticks value (thirds).Set major and minor ticks locator with majors, minors and third tick values (thirds)Set ticks length using tick_params().Plot a horizontal line with gray color.To display the ... Read More

To plot hysteresis threshold in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Load some greek coins, Greek coins from Pompeii.Find, high, low, and edges of the images using the sobel filter.Apply hysteresis thresholding to "image".Display the data as an image, i.e., on a 2D regular raster, using imshow() method.Set the titles for the original image and the image with hysteresis threshold.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt from skimage import data, filters plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] ... Read More

To make semilogx and semilogy plots, 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.Scatter and plot x and y data points.Make a plot with log scaling on the X axis.Make a plot with log scaling on the Y axis.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 x = [10, 100, 1000, 10000, 100000] y = [2, 4, 8, 16, 32] fig = plt.figure() plt.scatter(x, y) plt.plot(x, y) ... Read More

To programmatically stop interaction for specific figures in Jupyter notebook, we can use plt.off() to stop any interaction after that.Execute the following commnads sequentially −%matplotlib autoimport matplotlib.pyplot as pltplt.rcParams["figure.figsize"] = [7.50, 3.50]plt.rcParams["figure.autolayout"] = TrueCreate a figure and a set of subplots.Plot the line on the axis (From step 5).Turn off the interaction.To display the figure, use show() method.ExampleIn [1]: %matplotlib auto Using matplotlib backend: Qt5Agg In [2]: import matplotlib.pyplot as plt In [3]: plt.rcParams["figure.figsize"] = [7.50, 3.50]    ...: plt.rcParams["figure.autolayout"] = True In [4]: fig, ax = plt.subplots() In [5]: ax.plot([2, 4, 7, 5, 4, 1]) ... Read More

To animate 3D plot_surface in Matplotlib, we can take the following steps−Initialize variables for number of mesh grids (N), frequency per second (fps) to call a function, and frame numbers (frn).Create x, y and z array for a curve.Make a function to make a z-array using lambda function.To pass a function into animation class, make a user-defined function that removes the previous plot and plot a surface using x, y and z-array.Create a new figure or activate an existing figure.Add a subplot arrangement using subplots() method.Set the Z-axis limit using set_zlim() method.Call the animation class to animate the surface plot.To ... Read More

To combine several matplotlib axes subplots into one figure, we can use subplots() method with nrow=2.StepsSet the figure size and adjust the padding between and around the subplots.Create x, y1 and y2 data points using numpy.Create a figure and a set of subplots.Plot x, y1 and y2 data points using plot() method.To display the figure, use 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 x = np.linspace(-10, 10, 100) y1 = np.sin(x) y2 = np.cos(x) fig, axes = plt.subplots(nrows=2) line1, = axes[0].plot(x, y1, color='red') line2, ... Read More

To get xkcd font working, we can use plt.xkcd() to turn on sketch-style drawing mode.StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Use plt.xkcd() to turn on sketch-style drawing mode.Create a new figure or activate an existing figure.Add an axis to the figure as part of a subplot arrangement.Plot x and y data points using plot() method.Place a text and title on the plot.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x ... Read More