import matplotlib.pyplot as plt
from matplotlib import pyplot as plt
import matplotlib.pyplot as plt
import matplotlib.pyplot as plt
from matplotlib import pyplot as plt
import matplotlib.pyplot as plt
matplotlib
# importing matplotlib module
from matplotlib import pyplot as plt
# x-axis values
x = [5, 2, 9, 4, 7]
# Y-axis values
y = [10, 5, 8, 4, 2]
# Function to plot scatter
plt.scatter(x, y)
# function to show the plot
plt.show()
import matplotlib.pyplot as plt
from matplotlib import pyplot as plt
import matplotlib.pyplot as plt1
print(dir(plt) == dir(plt1))
True
matplotlib python
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator
import numpy as np
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
# Make data.
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
# Plot the surface.
surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
linewidth=0, antialiased=False)
# Customize the z axis.
ax.set_zlim(-1.01, 1.01)
ax.zaxis.set_major_locator(LinearLocator(10))
# A StrMethodFormatter is used automatically
ax.zaxis.set_major_formatter('{x:.02f}')
# Add a color bar which maps values to colors.
fig.colorbar(surf, shrink=0.5, aspect=5)
plt.show()
matplotlib
# importing matplotlib module
from matplotlib import pyplot as plt
# Plotting to our canvas
plt.plot([1,2,3],[4,5,1])
# Showing what we plotted
plt.show()
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