Matplotlib is currently using agg, which is non-GUI backend

# Matplotlib is currently using agg, which is non-GUI backend

The Python "UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure." occurs when you try to display a plot with your Matplotlib backend set to a non-GUI backend, such as Agg.

The first thing you should try is to set the backend to TkAgg.

main.py

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import matplotlib

matplotlib.use('TkAgg')

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 4*np.pi, 150)
y = np.sin(x)

ax = plt.subplot(111)
ax.plot(x, y)

plt.show()

The code for this article is available on GitHub

Make sure to add the matplotlib.use('TkAgg') line above the line that imports matplotlib.pyplot.

successfully showing plot

If you get the ModuleNotFoundError: No module named 'tkinter' in Python error, click on the link and follow the instructions on how to install Tkinter.

# Try using the `plt.savefig()` method instead

Another thing you can try is to use the pyplot.savefig() method instead of using pyplot.show().

main.py

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import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 4*np.pi, 150)
y = np.sin(x)

ax = plt.subplot(111)
ax.plot(x, y)

plt.savefig('my-plot.png')

using pyplot savefig method instead

The code for this article is available on GitHub

The pyplot.savefig() method saves the current plot.

I passed the name of the output image to the method.

pass name of output image to pyplot savefig method

# Try installing the PyQt5 module

Another thing that may help is installing the PyQt5 module.

shell

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pip install PyQt5

# or with pip3
pip3 install PyQt5

install the pyqt5 module

By installing the PyQt5 module, you also install Matplotlib GUI backends, which should resolve the issue.

# Use the `%matplotlib inline` line in Jupyter Notebook

If you get the error when using Jupyter Notebook, set the %matplotlib inline line at the top.

main.py

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%matplotlib inline

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 4*np.pi, 150)
y = np.sin(x)

ax = plt.subplot(111)
ax.plot(x, y)

plt.show()

add matplotlib inline in jupyter notebook

The %matplotlib inline directive is a magic function in IPython.

Its purpose is to set the backend of Matplotlib to the inline backend.

This helps us display the output of plotting commands inline within frontends like Jupyter Notebook, directly below the code cell that produced it.

I've written in detail about this magic function in my how to show a PIL Image in Jupyter Notebook article.

In Jupyter Notebook, you can also try to use the display() function to render your plots.

main.py

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from IPython.display import display

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 4*np.pi, 150)
y = np.sin(x)

ax = plt.subplot(111)
ax.plot(x, y)

display(plt)

import and use display function

We imported and used the display function.

You can pass the plt or fig variables directly to display().

You can also try to use plt or fig as the last line of a cell, instead of calling plt.show().

main.py

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import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 4*np.pi, 150)
y = np.sin(x)

ax = plt.subplot(111)
ax.plot(x, y)

plt

use plt as last line of cell

You can also try using the %matplotlib notebook magic function.

main.py

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%matplotlib notebook
import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 4*np.pi, 150)
y = np.sin(x)

ax = plt.subplot(111)
ax.plot(x, y)

plt.show()

using matplotlib notebook magic function

# Install Tkinter on your machine

If none of the suggestions helped, follow the instructions in this article on how to install Tkinter.

Once you install Tkinter, you should be able to set the backend to TkAgg without running into any issues.

main.py

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import matplotlib

matplotlib.use('TkAgg')

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 4*np.pi, 150)
y = np.sin(x)

ax = plt.subplot(111)
ax.plot(x, y)

plt.show()

successfully showing plot

The code for this article is available on GitHub

You can even try to remove the line that sets the engine and try to use the default one.

main.py

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import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 4*np.pi, 150)
y = np.sin(x)

ax = plt.subplot(111)
ax.plot(x, y)

plt.show()

without explicitly setting backend

# Additional Resources

You can learn more about the related topics by checking out the following tutorials:

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Matplotlib is currently using agg, which is non-GUI backend