common use cases for matplotlib (pyplot functional API)¶
This is a collection of code snippets to cover most common use cases of using matplotlib library
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import numpy as np
1. Initialize ¶
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import matplotlib.pyplot as plt
2. Plot some data ¶
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data = np.random.rand(20)*10
plt.plot(data)
plt.show()
3. show an image ¶
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img = np.random.rand(30, 30, 3)
plt.imshow(img) # changed
plt.show()
4. plot size ¶
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plt.figure(figsize=(10,10)) # changed
data = np.random.rand(20)*10
plt.plot(data)
plt.show()
5. multiple data plotting ¶
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data1 = np.random.rand(20)*10
data2 = np.random.rand(20)*10
plt.plot(data1)
plt.plot(data2) # changed
plt.show()
6. set plot color ¶
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data1 = np.random.rand(20)*10
data2 = np.random.rand(20)*10
plt.plot(data1, color='g') # changed
plt.plot(data2, color='r') # changed
plt.show()
7. plot legend ¶
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data1 = np.random.rand(20)*10
data2 = np.random.rand(20)*10
plt.plot(data1, color='g', label='data1') # changed
plt.plot(data2, color='r', label='data2') # changed
plt.legend() # changed
plt.show()
8. axis turn on/off ¶
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data1 = np.random.rand(20)*10
data2 = np.random.rand(20)*10
plt.axes = 0
plt.plot(data1, color='g', label='data1')
plt.plot(data2, color='r', label='data2')
plt.xticks([]) # changed
plt.yticks([]) # changed
plt.legend()
plt.show()
9. major ticks ¶
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data1 = np.random.rand(20)*10
data2 = np.random.rand(20)*10
plt.axes = 0
plt.plot(data1, color='g', label='data1')
plt.plot(data2, color='r', label='data2')
plt.xticks(np.linspace(0, 20, 4, endpoint=False)) # changed
# plt.yticks([])
plt.legend()
plt.show()
10. minor ticks ¶
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data1 = np.random.rand(20)*10
data2 = np.random.rand(20)*10
plt.plot(data1, color='g', label='data1')
plt.plot(data2, color='r', label='data2')
plt.xticks(np.linspace(0, 20, 4, endpoint=False))
plt.axes().xaxis.set_minor_locator(plt.MultipleLocator(1)) # changed
# plt.yticks([])
plt.legend()
plt.show()
11. grid ¶
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data1 = np.random.rand(20)*10
plt.plot(data1, color='g', label='data1')
plt.xticks(np.linspace(0, 20, 4, endpoint=False))
plt.axes().xaxis.set_minor_locator(plt.MultipleLocator(1))
# plt.yticks([])
plt.legend()
plt.grid(True, which='both') # changed
plt.show()
12. Axis limits ¶
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data1 = np.random.rand(20)*10
plt.axes().xaxis.set_minor_locator(plt.MultipleLocator(1))
plt.plot(data1, color='g', label='data1')
plt.xticks(np.linspace(0, 20, 4, endpoint=False))
plt.xlim(0, 50) # changed
plt.ylim(0, 20) # changed
# plt.yticks([])
plt.legend()
plt.grid(True, which='both')
plt.show()
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