matplotlib.pyplot als pLT importieren
from matplotlib import pyplot as plt
import matplotlib.pyplot as plt
Foolish Flamingo
from matplotlib import pyplot as plt
import matplotlib.pyplot as plt from matplotlib import pyplot as plt
plt.plot([0, 1, 2, 3, 4, 5], [0, 1, 4, 9, 16, 25])
plt.show()import matplotlib.pyplot as plt
import numpy as np
data = np.random.rand(1024,2)
plt.scatter(data[:,0],data[:,1])
plt.show()
// Don't be
// fooled by this simplicity— plt.scatter() is a rich command.import matplotlib.pylot as plt import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
plt.show()import matplotlib.pyplot as plt
import numpy as np
# Simple data to display in various forms
x = np.linspace(0, 2 * np.pi, 400)
y = np.sin(x ** 2)
fig, axarr = plt.subplots(2, 2)
fig.suptitle("This Main Title is Nicely Formatted", fontsize=16)
axarr[0, 0].plot(x, y)
axarr[0, 0].set_title('Axis [0,0] Subtitle')
axarr[0, 1].scatter(x, y)
axarr[0, 1].set_title('Axis [0,1] Subtitle')
axarr[1, 0].plot(x, y ** 2)
axarr[1, 0].set_title('Axis [1,0] Subtitle')
axarr[1, 1].scatter(x, y ** 2)
axarr[1, 1].set_title('Axis [1,1] Subtitle')
# Fine-tune figure;
# hide x ticks for top plots and y ticks for right plots
plt.setp([a.get_xticklabels() for a in axarr[0, :]], visible=False)
plt.setp([a.get_yticklabels() for a in axarr[:, 1]], visible=False)
# Tight layout often produces nice results
# but requires the title to be spaced accordingly
fig.tight_layout()
fig.subplots_adjust(top=0.88)
plt.show()