Matplotlib Articles

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Circular (polar) histogram in Python

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 06-May-2021 2K+ Views

To plot circular (polar) histogram in Python, we can take the following steps−Create data points for theta, radii and width using numpy.Add a subplot to the current figure, where projection='polar' and nrows=1, ncols=1 and index=1.. Make a bar plot using bar() method, with theta, radii and width data pointsIterate radii and bars after zipping them together and set the face color of the bar and the alpha value. Lesser the alpha value, greater the transparency.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 = 20 theta = ...

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How to put text outside Python plots?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 06-May-2021 3K+ Views

To put text outside a plot, we can change the text position by changing the value of text_pos_x and text_pos_yStepsCreate data points for x and y.Initialize the text position of x and y.To plot x and y, use plot() method with color='red'.Use text() method to add text to figure.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 x = np.linspace(1, 5, 100) y = np.exp(x) text_pos_x = 0.60 text_pos_y = 0.50 plt.plot(x, y, c='red') plt.text(text_pos_x, text_pos_y, "$\mathit{y}=e^{x}$", fontsize=14, transform=plt.gcf().transFigure, color='green') plt.show()Output

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Adjusting gridlines and ticks in Matplotlib imshow

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 06-May-2021 5K+ Views

To adjust gridlines and ticks in matplotlib imshow(), we can take the following steps−Create data, a 2D array, using numpy.Using imshow() method, display data as an image.Set xticks and yticks using set_xticks and set_yticks method.To set the xticklabels and yticklabels, use set_xticklabels and set_yticklabels method.Lay out a grid in current line style. Supply the list of x an y positions using grid() method.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(9, 9) plt.imshow(data, interpolation="nearest") ax = plt.gca() ax.set_xticks(np.arange(-.5, 9, 1)) ax.set_yticks(np.arange(-.5, 9, 1)) ...

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Matplotlib Plot Lines with Colors through Colormap

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 06-May-2021 14K+ Views

To plot lines with colors through colormap, we can take the following steps−Create x and y data points using numpyPlot x and y data points using plot() method.Count n finds, number of color lines has to be plotted.Iterate in a range (n) and plot the lines.Limit the x ticks range.Use show() method to display the figure.Exampleimport numpy as np import matplotlib.pylab as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(0, 2 * np.pi, 64) y = np.exp(x) plt.plot(x, y) n = 20 colors = plt.cm.rainbow(np.linspace(0, 1, n)) for i in range(n): plt.plot(x, i * y, color=colors[i]) plt.xlim(4, ...

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How to add group labels for bar charts in Matplotlib?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 06-May-2021 1K+ Views

To make grouped labels for bar charts, we can take the following steps −Create lists for 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() method.Set a title for the axes using set_title() method.Get or set the current tick locations and ...

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How to rotate xticklabels in Matplotlib so that the spacing between each xticklabel is equal?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 06-May-2021 425 Views

To rotate xticklabels in matplotlib to make equal spacing between two xticklabels, we can take the following steps −Make a list of numbers from 1 to 4.Using subplot(), sdd a subplot to the current figure.Add xticks and yticks on the current subplot (using step 1).Set xtick labels by passing a list and to make label rotation (= 45).To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = [1, 2, 3, 4] ax1 = plt.subplot() ax1.set_xticks(x) ax1.set_yticks(x) ax1.set_xticklabels(["one", "two", "three", "four"], rotation=45) plt.show()Output

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Colorplot of 2D array in Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 06-May-2021 1K+ Views

To plot a colorplot of a 2D array, we can take the following steps −Create data (i.e., 2D array) using numpy.For colorplot, use imshow() method, with input data (Step 1) and colormap is "PuBuGn".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, cmap='PuBuGn') plt.show()Output

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Adding caption below X-axis for a scatter plot using Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 06-May-2021 5K+ Views

To add caption below X-axis for a scatter plot, we can use text() method for the current figure.StepsCreate x and y data points using numpy.Create a new figure or activate an existing figure using figure() method.Plot the scatter points with x and y data points.To add caption to the figure, use text() method.Adjust the padding between and around the subplots.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 x = np.random.rand(10) y = np.random.rand(10) fig = plt.figure() plt.scatter(x, y, c=y) fig.text(.5, .0001, "Scatter Plot", ha='center') plt.tight_layout() plt.show()Output

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How to plot a confusion matrix with string axis rather than integer in Python?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 06-May-2021 681 Views

To plot a confusion matrix with string axis rather than integer in Python, we can take the following steps−Make a list for labels.Create a confusion matrix. Use confusion_matrix() to calculate accuracy of classification.3. Add an '~.axes.Axes' to the figure as part of a subplot arrangement.Plot the values of a 2D matrix or array as a color-coded image.Using colorbar() method, create a colorbar for a ScalarMappable instance, *mappable*6. Set x and y ticklabels using set_xticklabels and set_yticklabels methods.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt from sklearn.metrics import confusion_matrix plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True labels ...

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Set variable point size in Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 06-May-2021 490 Views

To set the variable point size in matplotlib, we can take the following steps−Initialize the coordinates of the point.Make a variable to store the point size.Plot the point using scatter method, with marker=o, color=red, s=point_size.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 xy = (3, 4) point_size = 100 plt.scatter(x=xy[0], y=xy[1], marker='o', c='red', s=point_size) plt.show()Output

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