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Server Side Programming Articles
Page 1960 of 2109
How 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, ...
Read MoreHow to extract a subset of a colormap as a new colormap in Matplotlib?
To extract a subset of a colormap as a new colormap, we can take the following steps −Create a random array with 10×10 shape.Add a subplot to the current figure, where nrows=1, ncols=2 and index=1.Initialize using get_cmap so that scatter knows.Using imshow() method with colormap, display the data as an image, i.e., on a 2D regular raster, with data and colormap (Steps 1 and 3).Add a subplot to the current figure, where nrows=1, ncols=2 and index=2.Extract a subset of the colormap from the existing colormap (From step 3).Using imshow() method with colormap, display the data as an image, i.e., on a 2D regular raster, ...
Read MoreHow to enforce axis range in Matplotlib?
To enforce axis range in matplotlib, we can take the following steps −Set x and y limits using xlim and ylim methods, respectively.Create x and y points for the curve using numpy.Plot x and y using the plot() method.To show the figure, use the show() method.Exampleimport matplotlib.pyplot as plt import datetime import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.array([datetime.datetime(2021, 1, 1, i, 0) for i in range(24)]) y = np.random.randint(100, size=x.shape) plt.plot(x, y) plt.show()Output
Read MoreGet the list of figures in Matplotlib
To get the list of figures in matplotlib, we can take the following steps −Using figure() method, create a new figure, or activate an existing figure. Creating x figures, i.e., x=3.To get the list of figures, use the plt.get_fignums() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True plt.figure() plt.figure() plt.figure() print("Number of figures created: ", len(plt.get_fignums())) plt.show()OutputNumber of figures created: 3
Read MoreHow to plot a wav file using Matplotlib?
To plot a .wav file using matplotlib, we can take following the steps −To read a .wav file, we can use the read() method.After reading the .wav file, we will get a tuple. At the 0 th index, rate would be there and at the 1st index, array sample data.Use the plot() method to plot the .wav file.Set y and x labels using ylabel and xlabel with “Amplitude” and “Time” label, respectively.To display the figure, use the show() method.Examplefrom scipy.io.wavfile import read import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True input_data = read("my_audio.wav") audio = input_data[1] plt.plot(audio[0:1024]) plt.ylabel("Amplitude") plt.xlabel("Time") plt.show()Output
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