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Matplotlib Articles
Page 72 of 91
How to shade the regions between the curves in Matplotlib?
To shade the regions between curves, we can use the fill_between() method.StepsInitialize the variable n. Initiliize x and y data points using numpy.Create a figure and a set of subplots, fig and ax.Plot the curve using plot method.Use fill_between() method, fill the area between the two curves.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True n = 256 X = np.linspace(-np.pi, np.pi, n, endpoint=True) Y = np.sin(2 * X) fig, ax = plt.subplots() ax.plot(X, Y, color='blue', alpha=1.0) ax.fill_between(X, 0, Y, color='blue', alpha=.2) plt.show()Output
Read MoreHow to center an annotation horizontally over a point in Matplotlib?
To center an annotation horizontally over a point, we can take the following steps−Create points for x and y using numpy.Create labels using xpoints.Use scatter() method to scatter the points.Iterate labels, xpoints and ypoints and annotate the plot with label, x and y with different properties, make horizontal alignment ha=center.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True xpoints = np.linspace(1, 10, 10) ypoints = np.random.rand(10) labels = ["%.2f" % i for i in xpoints] plt.scatter(xpoints, ypoints, c=xpoints) for label, x, y in zip(labels, xpoints, ypoints): ...
Read MoreHow can I display an image using cv2 in Python?
To read an image in Python cv2, we can take the following steps−Load an image from a file.Display the image in the specified window.Wait for a pressed key.Destroy all of the HighGUI windows.Exampleimport cv2 img = cv2.imread("baseball.png", cv2.IMREAD_COLOR) cv2.imshow("baseball", img) cv2.waitKey(0) cv2.destroyAllWindows()Output
Read MoreExtract Matplotlib colormap in hex-format
To extract matplotlib colormap in hex-format, we can take the following steps −Get the rainbow color map.Iterate in the range of rainbow colormap length.Using rgb2hex method, convert rgba tuple to a hexadecimal representation of a color.Examplefrom matplotlib import cm import matplotlib cmap = cm.rainbow for i in range(cmap.N): rgba = cmap(i) print("Hexadecimal representation of rgba:{} is {}".format(rgba, matplotlib.colors.rgb2hex(rgba)))Output............... ........................ .................................... Hexadecimal representation of rgba:(1.0, 0.3954512068705424, 0.2018824091570102, 1.0) is #ff6533 Hexadecimal representation of rgba:(1.0, 0.38410574917192575, 0.1958454670071669, 1.0) is #ff6232 Hexadecimal representation of rgba:(1.0, 0.37270199199091436, 0.18980109344182594, 1.0) is #ff5f30 .........................................................
Read MoreHow do you directly overlay a scatter plot on top of a jpg image in Matplotlib?
To directly overlay a scatter plot on top of a jpg image, we can take the following steps −Load an image "bird.jpg", using imread() method, Read an image from a file into an array.Now display data as an image.To plot scatter points on the image make lists for x_points and y_points.Generate random numbers for x and y and append in lists.Using scatter method, plot x and y points.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True data = plt.imread("logo2.jpg") im = plt.imshow(data) x_points = [] y_points ...
Read MorePlot a histogram with Y-axis as percentage in Matplotlib
To plot a histogram with Y-axis as percentage in matplotlib, we can take the following steps −Create a list of numbers as y.Create a number of bins.Plot a histogram using hist() method, where y, bins, and edgecolor are passed in the argument.Store the patches to set the percentage on Y-axis.Create a list of colors from the given alphanumeric numbers.To set the percentage, iterate the patches (obtained in step 3).Set the Y-axis ticks range.To display the figure, use show() method.Exampleimport random import numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True y = [4, 1, 8, ...
Read MoreSetting Y-axis in Matplotlib using Pandas
To set Y-Axis in matplotlib using Pandas, we can take the following steps −Create a dictionary with the keys, x and y.Create a data frame using Pandas.Plot data points using Pandas plot, with ylim(0, 25) and xlim(0, 15).To display the figure, use show() method.Exampleimport numpy as np import pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True d = dict( x=np.linspace(0, 10, 10), y=np.linspace(0, 10, 10)*2 ) df = pd.DataFrame(d) df.plot(kind="bar", ylim=(0, 25), xlim=(0, 15)) plt.show()Output
Read MoreHow to remove the outline of a circle marker when using pyplot.plot in Matplotlib?
To remove the outline of a circle marker, we can reduce the value of marker edge width.Initialize list for x and y, with a single value.Limit x and y axis range for 0 to 5.Lay out a grid in current line style.Plot the given x and y using plot() method, with marker="o", markeredgecolor="red", markerfacecolor="green" and minimum markeredgewidth to remove the outline.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = [4] y = [3] plt.xlim(0, 5) plt.ylim(0, 5) plt.grid() plt.plot(x, y, marker="o", markersize=20, markeredgecolor="black", markerfacecolor="green", markeredgewidth=.1) plt.show()Output
Read MoreHow to use 'extent' in matplotlib.pyplot.imshow?
To use extent in matplotlib imshow(), we can use extent [left, right, bottom, top].StepsCreate random data using numpy.Display the data as an image, i.e., on a 2D regular raster with data and extent [−1, 1, −1, 1] arguments.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True data = np.random.rand(4, 4) plt.imshow(data, extent=[-1, 1, -1, 1]) plt.show()Output
Read MorePython Matplotlib Venn diagram
To plot a Venn diagram, first install Venn diagram using command "pip install matplotlib-venn". Using venn3, plot a 3-set area-weighted Venn diagram.StepsCreate 3 sets.Using venn3, make a Venn diagram.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt from matplotlib_venn import venn3 plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True set1 = {'A', 'B', 'C'} set2 = {'A', 'B', 'D'} set3 = {'A', 'E', 'F'} venn3([set1, set2, set3], ('Group1', 'Group2', 'Group3')) plt.show()Output
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