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Articles by Rishikesh Kumar Rishi
Page 91 of 102
Logarithmic Y-axis bins in Python
To plot logarithmic Y-axis bins in Python, we can take the following steps −Create x and y points using numpy.Set the Y-axis scale using the yscale() method.Plot the x and y points, using the plot() method with linestyle="dashdot" and label="y=log(x)".To activate the label of the line, use the legend() method.To display the figure, use the 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(1, 100, 1000) y = np.log(x) plt.yscale('log') plt.plot(x, y, c="red", lw=3, linestyle="dashdot", label="y=log(x)") plt.legend() plt.show()Output
Read MoreHow to plot matplotlib contour?
To plot matplotlib contour, we can take the following steps −Create data points for x, y and h using numpy.Using the countourf() method, create a colored 3D (alike) plot.Using the set_over() method, set the color for high out-of-range values when "norm.clip = False".Using the set_under() method, set the color for low out-of-range values when "norm.clip = False".Using the changed() method, call this whenever the mappable is changed to notify all the callbackSM listeners to the "changed" signal.Use the show() method to display the figure.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = ...
Read MoreHow to display a 3D plot of a 3D array isosurface in matplotlib mplot3D or similar?
Let's take an example to see how to display a 3D plot of a 3D array isosurface in matplotlib −Exampleimport numpy as np import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.arange(-5, 5, 0.25) y = np.arange(-5, 5, 0.25) x, y = np.meshgrid(x, y) h = x ** 2 + y ** 2 fig = plt.figure() ax = Axes3D(fig) ax.plot_surface(x, y, h, rstride=1, cstride=1, cmap=plt.cm.rainbow, linewidth=0, antialiased=False) plt.show()Output
Read MoreHow to save the plot to a numpy array in RGB format?
To save the plot to a numpy array in RGB format, we can take the following steps −Create r, g and b random array using numpy.Zip r, g and b (grom step 1) to make an rgb tuple list.Convert rgb into a numpy array to plot it.Plot the numpy array that is in rgb format.Save the figure at the current location.To display the figure, use the 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 r = np.random.rand(100) g = np.random.rand(100) b = np.random.rand(100) rgb = zip(r, g, b) arr = np.array([item for item in rgb]) plt.plot(arr) plt.savefig("myplot.png") ...
Read MoreHow to set the range of Y-axis for a Seaborn boxplot using Matplotlib?
To set the range of Y-axis for a Seaborn boxplot, we can take the following steps −Using set_style() method, set the aesthetic style of the plots.Load the dataset using load_dataset("tips"); need Internet.Using boxplot(), draw a box plot to show distributions with respect to categories.To set the range of Y-axis, use the ylim() method.To display the figure, use the show() method.Examplefrom matplotlib import pyplot as plt import seaborn as sns plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True sns.set_style("whitegrid") tips = sns.load_dataset("tips") ax = sns.boxplot(x="day", y="total_bill", data=tips) plt.ylim(5, 50) plt.show()Output
Read MoreWriting numerical values on the plot with Matplotlib
To write numerical values on the plot, we can take the following steps −Create points for x and y using numpy.Create labels using xpoints.Use the scatter() method to scatter the points.Iterate labels, xpoints and ypoints and annotate the plot with label, x and y with different properties.To display the figure, use the 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 xpoints = np.linspace(1, 10, 25) ypoints = np.random.rand(25) labels = ["%.2f" % i for i in xpoints] plt.scatter(xpoints, ypoints, c=xpoints) for label, x, y in zip(labels, xpoints, ypoints): plt.annotate( ...
Read MoreHow to change the color of a line using radiobuttons in Matplotlib?
To change the color of a line using radiobutton we can take following steps −Create x and y data points using numpy.Adjust the figure size and padding between and around the subplots.Create a figure and a set of subplots using subplots() method.Plot curve with x and y data points using plot() method.Add an axes to the current figure and make it the current axes, using axes() method.Add a radio button to the current axes.Change the color of the curve with radion button using change_color() method, that can be passed in on_clicked() method.To display the figure use show() method.Exampleimport numpy as ...
Read MoreHow to zoom a portion of an image and insert in the same plot in Matplotlib?
To zoom a portion of an image and insert in the same plot, we can take the following steps −Create x and y points, using numpy.To zoom a part of an image, we can make data for x and y points, in that range.Plot x and y points (Step 1), using the plot() method with lw=2, color red and label.Use the legend() method to place text for the plot, Main curve.Create the axes using the axes() method by putting the rectangle’s coordinate.Plot x and y points (Step 2), using the plot() method with lw=1, color='green' and label, i.e., subpart of ...
Read MoreAdding extra axis ticks using Matplotlib
To add extra ticks in matplotlib, we can take the following Steps −Create x and y points using numpy.Plot x and y points over the plot, where x ticks could be from 1 to 10 (100 data points) on the curve.To add extra ticks, use xticks() method and increase the range of ticks to 1 to 20 from 1 to 10.To display the figure, use the 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(1, 10, 100) y = np.sin(x) plt.plot(x, y) plt.xticks(range(1, 20)) plt.show()Output
Read MoreHow to make the marker face color transparent without making the line transparent in Matplotlib?
To make the marker face color transparent without making the line transparent in matplotlib, we can take the following steps −Create x_data and y_data(sin(x_data)), using numpy.Plot curve using x_data and y_data, with marker style and marker size. By changing the alpha, we can make it transparent to opaque.To get the essence of transparency (keeping alhpa value lesser), we can make grid lines, to see through.To display the figure, use the 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_data = np.linspace(1, 10, 100) y_data = np.sin(x_data) plt.plot(x_data, y_data, c='green', marker='o', alpha=.3, ms=10, ...
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