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Articles by Rishikesh Kumar Rishi
Page 65 of 102
How to make Matplotlib show all X coordinates?
To show all X coordinates (or Y coordinates), we can use xticks() method (or yticks()).StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Set x=0 and y=0 margins on the axes.Plot x and y data points using plot() method.Use xticks() method to show all the X-coordinates in the plot.Use yticks() method to show all the Y-coordinates in the plot.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 x = np.arange(0, 10, 1) y =np.arange(0, 10, 1) plt.margins(x=0, y=0) ...
Read MoreHow to customize the axis label in a Seaborn jointplot using Matplotlib?
To customize the axis label in a Seaborn jointplot, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Use jointplot() method to plot a joint plot in Seaborn.To set the customized axis label, we can use LaTex representation or set_xlabel() method properties.To display the figure, use show() method.Exampleimport seaborn as sns import numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.random.randn(1000, ) y = 0.2 * np.random.randn(1000) + 0.5 h = sns.jointplot(x, y, height=3.50) h.ax_joint.set_xlabel('$\bf{X-Axis\ ...
Read MoreHow to decrease the density of x-ticks in Seaborn?
To decrease the density of x-ticks in Seaborn, we can use set_visible=False for odd positions.StepsSet the figure size and adjust the padding between and around the subplots.Create a dataframe with X-axis and Y-axis keys.Show the point estimates and confidence intervals with bars, using barplot() method.Iterate bar_plot.get_xticklabels() method. If index is even, then make them visible; else, not visible.To display the figure, use show() method.Exampleimport pandas import matplotlib.pylab as plt import seaborn as sns plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pandas.DataFrame({"X-Axis": [i for i in range(10)], "Y-Axis": [i for i in range(10)]}) bar_plot = sns.barplot(x='X-Axis', y='Y-Axis', data=df) for ...
Read MoreHow to remove the space between subplots in Matplotlib.pyplot?
To remove the space between subplots in matplotlib, we can use GridSpec(3, 3) class and add axes as a subplot arrangement.StepsSet the figure size and adjust the padding between and around the subplots.Add a grid layout to place subplots within a figure.Update the subplot parameters of the gridIterate in the range of dimension of grid specs.Add a subplot to the current figure.Set the aspect ratios.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import matplotlib.gridspec as gridspec plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True gs1 = gridspec.GridSpec(3, 3) gs1.update(wspace=0.5, hspace=0.1) for i in range(9): ax1 = plt.subplot(gs1[i]) ax1.set_aspect('equal') plt.show()Output
Read MoreWhat is the difference between plt.show and cv2.imshow in Matplotlib?
A simple call to the imread method loads our image as a multi-dimensional NumPy array (one for each Red, Green, and Blue component, respectively) and imshow displays our image on the screen. Whereas, cv2 represents RGB images as multi-dimensional NumPy arrays, but in reverse order.StepsSet the figure size and adjust the padding between and around the subplots.Initialize the filename.Add a subplot to the current figure using nrows=1, ncols=2, and index=1.Read the image using cv2.Off the axes and show the figure in the next statement.Add a subplot to the current figure using nrows=1, ncols=2, and index=2.Read the image using plt.Off the ...
Read MoreHow to make Matplotlib scatterplots transparent as a group?
To make matplotlib scatterplots transparent as a group, we can change the alpha value in the scatter() method argument with a different group value.StepsSet the figure size and adjust the padding between and around the subplots.Make a method to return a grouped x and y points.Get group 1 and group 2 data points.Plot group1, x and y points using scatter() method with color=green and alpha=0.5.Plot group2, x and y points using scatter() method with color=red and alpha=0.5.To display the figure, use 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 def ...
Read MoreMap values to colors in Matplotlib
To map values to a colors tuple(red, green and blue) in matplotlib, we can take the following steps −Create a list of values from 1.00 to 2.00, count=10.Get linearly normalized data into the vmin and vmax interval.Get an object to map the scalar data to rgba.Iterate the values to map the color values.Print the values against the mapped red, green, and blue values.Exampleimport numpy as np from matplotlib import cm, colors values = np.linspace(1.0, 2.0, 10) norm = colors.Normalize(vmin=1.0, vmax=2.0, clip=True) mapper = cm.ScalarMappable(norm=norm, cmap=cm.Greys_r) for value in values: print("%.2f" % value, "=", "red:%.2f" % mapper.to_rgba(value)[0], ...
Read MoreDrawing a network graph with networkX and Matplotlib
To draw a network graph with networkx and matplotlib, plt.show() −Set the figure size and adjust the padding between and around the subplots.Make an object for a dataframe with the keys, from and to.Get a graph containing an edgelist.Draw a graph (Step 3) using draw() method with some node properties.To display the figure, use show() method.Exampleimport pandas as pd import networkx as nx from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame({'from': ['A', 'B', 'C', 'A'], 'to': ['D', 'A', 'E', 'C']}) G = nx.from_pandas_edgelist(df, 'from', 'to') nx.draw(G, with_labels=True, node_size=100, alpha=1, linewidths=10) plt.show()Output
Read MoreHow do you draw R-style axis ticks that point outward from the axes in Matplotlib?
To draw R-style (default is regular style) axis ticks that point outward from the axes in matplotlib, we can use rcParams["xticks.direction"]="out" for X-axis.StepsSet the figure size and adjust the padding between and around the subplots.Set outwaord tick points using plt.rcParams.Initialize a variable for the number of data points.Create x and y data points using numpy.Plot x and y data points using plot() method.To display the figure, use 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 plt.rcParams['ytick.direction'] = 'out' # in plt.rcParams['xtick.direction'] = 'out' # in n = 10 x = ...
Read MoreHow do I make the width of the title box span the entire plot in Matplotlib?
To make width of title box span the entire plot in matplotlib, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Plot x and y data points using plot() method, with color=black and linewidth=7.Get the current axes using gca() method.Set the title of of the plot.Return the bbox patch using get_bbox_patch() methodTo display the figure, use 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(-2, 2, 100) y = np.sin(x) plt.plot(x, y, c='black', ...
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