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Articles by Rishikesh Kumar Rishi
Page 83 of 102
Putting arrowheads on vectors in Matplotlib's 3D plot
To draw arrow heads vectors in 3D matplotlb's plot, we can take the following steps −Create a 2D array, where x, y, z, u, v and w are the coordinates of the arrow locations and direction components of arrow vectors.Using figure() method, create a new figure or activate an existing figure.Add an '~.axes.Axes' to the figure as part of a subplot arrangement, using add_subplot() method.Plot a 3D field of arrows, using quiver() method.Using ylim, xlim, zlim, limit the range of the axes.Set the title of the plot.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = ...
Read MoreRemove the X-axis ticks while keeping the grids (Matplotlib)
To remove the X-ticks while keeping the grids, we can take the following steps−Use gca() method to get the current axes, creating one if necessary.Plot the x and np.sin(x) using plot() method with linewidth=5, label y=sin(x).Remove yticks and xticks by passing empty array in the argument of set_xticklabels and set_yticklabels methods respectively.Configure grid lines by putting flag as True.Place the legend for the plot label in the argument.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(0, 2*np.pi, 100) ax = plt.gca() ax.plot(x, np.sin(x), c='r', lw=5, ...
Read MorePlotting a transparent histogram with non-transparent edge in Matplotlib
To plot a transparent histogram with non-transparent edge, we can take the following steps−Create a set of random data points (y).Initialize the number of bins to be drawn.To plot the histogram, we can use hist() method with edge color and facecolor tuplesTo 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 y = np.random.rand(100) nbins = 5 plt.hist(y, bins=nbins, edgecolor=(1, 0, 0, 1), lw=5, facecolor=(.09, .12, .65, .87), rwidth=0.8) plt.show()Output
Read MoreExtract csv file specific columns to list in Python
To extract csv file for specific columns to list in Python, we can use Pandas read_csv() method.StepsMake a list of columns that have to be extracted.Use read_csv() method to extract the csv file into data frame.Print the exracted data.Plot the data frame using plot() method.To display the figure, use show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True columns = ["Name", "Marks"] df = pd.read_csv("input.csv", usecols=columns) print("Contents in csv file:", df) plt.plot(df.Name, df.Marks) plt.show()The csv file contains the following data −NameMarksArun98Shyam75Govind54Javed92Raju87OutputWhen we execute the code, it will extract the data from the csv file ...
Read MoreHow to make a log histogram in Python?
To make a log histogram, we can use log=True in the argument of the hist() method.StepsMake a list of numbers.Plot a histogram with density=True.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True k = np.array([5, 5, 5, 5]) x, bins, p = plt.hist(np.log(k), density=True, log=True) plt.show()Output
Read MoreHow 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 ...
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