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To close a Python figure by a keyboard input, we can use plt.pause() method, an input, and close() method.StepsSet the figure size and adjust the padding between and around the subplots.Create random t and y data points using numpy.Create a new figure or activate an existing figure using figure() method.Plot t and y data points using plot() method.Set the title of the plot.Redraw the current figure using draw() method.Run a true loop to pause the current figure.Take input from the user to go to the next statement.Use close() method to close the figure.Exampleimport numpy as np from matplotlib import pyplot ... Read More
To display an np.array with imshow(), we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Make a 2D data raster using an np.array.Display the data as an image, i.e., on a 2D regular raster.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 data = np.array( [[0.1, 0.7, 0.6, 0.3], [0.2, 0.6, 0.5, 0.2], [0.8, 0.3, 0.80, 0.01], [0.3, 0.4, 0.2, 0.1]] ) plt.imshow(data, interpolation="nearest", cmap="RdYlGn_r") plt.show()Output
To increase the space for X-axis labels in Matplotlib, we can use the spacing variable in subplots_adjust() method's argument.StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Create x and y data points using numpy.Plot x and y using plot() method.Put xlabel using xlabel() method with LaTex expression.Use subplots_adjust() method to increase or decrease the space for X-axis labelsTo 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 fig = plt.figure() x = ... Read More
To set Dataframe column value as X-axis labels in Python Pandas, we can use xticks in the argument of plot() method.StepsSet the figure size and adjust the padding between and around the subplots.Make a dataframe using Pandas with column1 key.Plot the Pandas dataframe using plot() method with column1 as the X-axis column.To display the figure, use show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = pd.DataFrame({"column1": [4, 6, 7, 1, 8]}) data.plot(xticks=data.column1) plt.show()Output
To plot a color wheel based on a colormap using Python/Matplotlib, we can use the colorbar class and can use copper colormap.StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Add an axes to the figure using add_axes() method.Set the direction of the axes.Linearly normalize the data using Normalize class.Draw a colorbar in an existing axes.Set the artist's visibility.Turn the X- and Y-axis off.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt, cm, colors, colorbar plt.rcParams["figure.figsize"] = [7.50, 3.50] ... Read More
To connect two points on a 3D scatter plot, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Add an axes to the current figure as a subplot arrangement.Create lists for x, y and z.Plot x, y and z data points using scatter() methodTo connect the points, use plot() method with x, y and z data points with black color line.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig = ... Read More
We can plot statsmodels linear regression (OLS) with a non-linear curve but with linear data.StepsSet the figure size and adjust the padding between and around the subplots.To create a new one, we can use seed() method.Initialize the number of sample and sigma variables.Create linear data points x, X, beta, t_true, y and res using numpy.Res is an ordinary Least Square class instance.Calculate the standard deviation. Confidence interval for prediction applies to WLS and OLS, not to general GLS, that is, independently but not identically distributed observations.Create a figure and a set of subplots using subplot() method.Plot all the curves using ... Read More
To control the alpha value on a 3D scatter plot using Python and Matplotlib, we can set the facecolor and edgecolors value.Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Add an '~.axes.Axes' to the figure as part of a subplot arrangement.Create x, y and z data points using numpy.Plot x, y and z points using scatter() method.Set the facecolors and edgecolors.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 ... Read More
To show all X coordinates (or Y coordinates), we can use xticks() method (or yticks()).StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Set x=0 and y=0 margins on the axes.Plot x and y data points using plot() method.Use xticks() method to show all the X-coordinates in the plot.Use yticks() method to show all the Y-coordinates in the plot.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 x = np.arange(0, 10, 1) y =np.arange(0, 10, 1) plt.margins(x=0, y=0) ... Read More
To customize the axis label in a Seaborn jointplot, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Use jointplot() method to plot a joint plot in Seaborn.To set the customized axis label, we can use LaTex representation or set_xlabel() method properties.To display the figure, use show() method.Exampleimport seaborn as sns import numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.random.randn(1000, ) y = 0.2 * np.random.randn(1000) + 0.5 h = sns.jointplot(x, y, height=3.50) h.ax_joint.set_xlabel('$\bf{X-Axis\ ... Read More