Programming Articles - Page 1204 of 3363

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

To rotate xtick labels in Seaborn boxplot, we can take the following steps −Create data points for xticks.Draw a boxplot using boxplot() method that returns the axis.Now, set the xticks using set_xticks() method, pass xticks.Set xticklabels and pass a list of labels and rotate them by passing rotation=45, using set_xticklabels() method.To display the figure, use show() method.Exampleimport seaborn as sns from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True xticks = [1, 4, 5, 2, 3] ax = sns.boxplot(xticks) ax.set_xticks(xticks) ax.set_xticklabels(["one", "two", "three", "four", "five"], rotation=45) plt.show()OutputRead More

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 .........................................................

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 More

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 More

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

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()OutputRead More

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

To imporove the label placement for matplotlib scatter chart, we can first plot the scatter points and annotate those points with labels.StepsCreate points for x and y using numpy.Create labels using xpoints.Use scatter() method to scatter points.Iterate the labels, xpoints and ypoints and annotate the plot with label, x and y with different properties.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 More

To plot bar graphs with same X coordinates (G1, G2, G3, G4 and G5), side by side in matplotlib, we can take the following steps −Create the following lists – labels, men_means and women_means with different data elements.Return evenly spaced values within a given interval, using numpy.arrange() method.Set the width variable, i.e., width=0.35.Create fig and ax variables using subplots method, where default nrows and ncols are 1.The bars are positioned at *x* with the given *align*\ment. Their dimensions are given by *height* and *width*. The vertical baseline is *bottom* (default 0), so create rect1 and rect2 using plt.bar() method.Set the Y-axis label using plt.ylabel() ... Read More