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Matplotlib Articles
Page 82 of 91
Adding 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
Read MoreIncrease the distance between the title and the plot in Matplotlib
To increase the distance between the title and the plot in matplotlib, we can take the following steps −Create point x using numpy.Create point y using numpy sin.Set the title of the plot. After changing the value y (in argument), we can increase or decrease the distance between the title and the plot.Plot x and y points using the plot() method, where color is red and line width is 2.Ti 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, 1000) y = np.sin(x) ttl = ...
Read MoreHow do I write a Latex formula in the legend of a plot using Matplotlib inside a .py file?
LaTeX is a typesetting language for producing scientific documents. We use a very small part of the language for writing mathematical notation. Jupyter notebook recognizes LaTeX code written in markdown cells and renders the symbols in the browser using the MathJax JavaScript library.To write a LaTeX formula in the legend of a plot, we can take the following steps −Create data points for x.Create data point for y, i.e., y=sin(x).Plot the curve x and y with LaTex representation.To activate the label, use the legend() method.To display the figure, use the show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] ...
Read MoreHow to draw grid lines behind Matplotlib bar graph?
To draw grid lines behind matplotlib bar graph, we can take the following Steps −Make a list of numbers, i.e., data.Make a bar using the bar() method, by passing data, color='red' and alpha = 0.5. The alpha blending value should be between 0 (transparent) and 1 (opaque).To configure the grid lines, use the grid() method, with color='yellow', linewidth=1, axis='both' and alpha=0.5.To display the figure, show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = [3, 5, 9, 15, 12] plt.bar(range(len(data)), data, color='red', alpha=0.5) plt.grid(color='yellow', linewidth=1, axis='both', alpha=0.5) plt.show()Output
Read MorePlot parallel coordinates in Matplotlib
To plot parallel coordinates, we can take the following Steps −Load dataset iris using Seaborn (Need internet).Pass the loaded data into the parallel_coordinates() method, which will help in parallel plotting.To display the figure, use the show() method.Exampleimport matplotlib.pyplot as plt from pandas.plotting import parallel_coordinates import seaborn as sns plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = sns.load_dataset('iris') parallel_coordinates(data, 'species', colormap=plt.get_cmap("Set2")) plt.show()Output
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