Matplotlib Articles

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Make 3D plot interactive in Jupyter Notebook (Python & Matplotlib)

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 4K+ Views

In this article, we can take a program code to show how we can make a 3D plot interactive using Jupyter Notebook.StepsCreate a new figure, or activate an existing figure.Create fig and ax variables using subplots method, where default nrows and ncols are 1, projection=’3d”.Get x, y and z using np.cos and np.sin function.Plot the 3D wireframe, using x, y, z and color="red".Set a title to the current axis.To show the figure, use plt.show() method.Exampleimport matplotlib.pyplot as plt import numpy as np fig = plt.figure() ax = fig.add_subplot(111, projection='3d') u, v = np.mgrid[0:2 * np.pi:30j, 0:np.pi:20j] x = np.cos(u) * ...

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Multiple axes in Matplotlib with different scales

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 4K+ Views

In the following code, we will see how to create a shared Y-axis.StepsCreate fig and ax variables using subplots method, where default nrows and ncols are 1.Plot line with lists passed in the argument of plot() method with color="red".Create a twin of Axes with a shared X-axis but independent Y-axis.Plot the line on ax2 that is created in step 3.Adjust the padding between and around subplots.To show the figure use plt.show() method.Exampleimport matplotlib.pyplot as plt fig, ax1 = plt.subplots() ax1.plot([1, 2, 3, 4, 5], [3, 5, 7, 1, 9], color='red') ax2 = ax1.twinx() ax2.plot([11, 12, 31, 41, 15], [13, 51, ...

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Prevent scientific notation in matplotlib.pyplot

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 20K+ Views

To prevent scientific notation, we must pass style='plain' in the ticklabel_format method.StepsPass two lists to draw a line using plot() method.Using ticklabel_format() method with style='plain'. If a parameter is not set, the corresponding property of the formatter is left unchanged. Style='plain' turns off scientific notation.To show the figure, use plt.show() method.Examplefrom matplotlib import pyplot as plt plt.plot([1, 2, 3, 4, 5], [11, 12, 13, 14, 15]) plt.ticklabel_format(style='plain')    # to prevent scientific notation. plt.show()Output

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Manually add legend Items Python Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 23K+ Views

Using plt.legend() method, we can create a legend, and passing frameon would help to keep the border over there.StepsSet the X-axis label using plt.xlabel() method.Set the Y-axis label using plt.ylabel() method.Draw lines using plot() method.Location and legend drawn flags can help to find a location and make the flag True for the border.Set the legend with “blue” and “orange” elements.To show the figure use plt.show() method.Exampleimport matplotlib.pyplot as plt plt.ylabel("Y-axis ") plt.xlabel("X-axis ") plt.plot([9, 5], [2, 5], [4, 7, 8]) location = 0 # For the best location legend_drawn_flag = True plt.legend(["blue", "orange"], loc=0, frameon=legend_drawn_flag) plt.show()Output

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Show only certain items in legend Python Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 2K+ Views

Using plt.legend(), we can add or show certain items just by putting the values in the list.StepsSet the X-axis label using plt.xlabel() method.Set the Y-axis label using plt.ylabel() method.Plot the lines using the lists that are passed in the plot() method argument.Location and legend_drawn flags can help to find a location and make the flag True for border.Set the legend with “blue” and “orange” elements.To show the figure use plt.show() method.Exampleimport matplotlib.pyplot as plt plt.ylabel("Y-axis ") plt.xlabel("X-axis ") plt.plot([9, 5], [2, 5], [4, 7, 8]) location = 0 # For the best location legend_drawn_flag = True plt.legend(["blue", ...

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What does .shape[] do in “for i in range(Y.shape[0])” using Matplotlib?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 1K+ Views

The shape property is usually used to get the current shape of an array, but it may also be used to reshape the array in-place by assigning a tuple of array dimensions to it.StepsGet an array Y using np.array method.Y.shape would return a tuple (4, ).Y.shape[0] method would return 4, i.e., the first element of the tuple.Exampleimport numpy as np Y = np.array([1, 2, 3, 4]) print("Output of .show method would be: ", Y.shape, " for ", Y) print("Output of .show[0] method would be: ", Y.shape[0], " for ", Y) print("Output for i in range(Y.shape[0]): ", end=" ") for ...

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Automatically run %matplotlib inline in IPython Notebook

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 16-Mar-2021 343 Views

%matplotlib would return the backend value.%matplotlib auto would return the name of the backend, over Ipython shell.ExampleIn [1]: %matplotlib autoOutputUsing matplotlib backend: GTK3Agg

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Adding textures to graphs using Matplotlib

Prasad Naik
Prasad Naik
Updated on 16-Mar-2021 655 Views

In this program, we will plot a bar graph using the matplotlib library. The most important Step in solving matplotlib related problems using the matplotlib library is importing the matplotlib library. The syntax is:import matplotlib.pyplot as pltPyplot is a collection of command style functions that make Matplotlib work like MATLAB. In addition to plotting the bar graphs, we will also add some textures to the graphs. The 'hatch' parameter in the bar() function is used to define the texture of the barAlgorithmStep 1: Define a list of values. Step 2: Use the bar() function and define parameters like xaxis, yaxis, ...

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How to show two figures using Matplotlib?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 16-Mar-2021 10K+ Views

We can use the method, plt.figure(), to create the figures, and then, set their titles by passing strings as arguments.StepsCreate a new figure, or activate an existing figure, with the window title “Welcome to figure 1”.Draw a line using plot() method, over the current figure.Create a new figure, or activate an existing figure, with the window title “Welcome to figure 2”.Draw a line using plot() method, over the current figure.Using plt.show(), show the figures.Examplefrom matplotlib import pyplot as plt plt.figure("Welcome to figure 1") plt.plot([1, 3, 4]) plt.figure("Welcome to figure 2") plt.plot([11, 13, 41]) plt.show()Output

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Plotting a 3d cube, a sphere and a vector in Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 16-Mar-2021 5K+ Views

Get fig from plt.figure() and create three different axes using add_subplot, where projection=3d.Set up the figure title using ax.set_title("name of the figure"). Use the method ax.quiver to plot vector projection, plot3D for cube, and plot_wireframe for sphere after using sin and cos.StepsCreate a new figure, or activate an existing figure.To draw vectors, get a 2D array.Get a zipped object.Add an ~.axes.Axes to the figure as part of a subplot arrangement, with 3d projection, where nrows = 1, ncols = 3 and index = 1.Plot a 3D field of arrows.Set xlim, ylim and zlim.Set the title of the axis (at index ...

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