python pip install matplotlib
pip install matplotlib
python matplotlib
from matplotlib import pyplot as plt
# Median Developer Salaries by Age
dev_x = [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]
dev_y = [38496, 42000, 46752, 49320, 53200,
56000, 62316, 64928, 67317, 68748, 73752]
plt.plot(dev_x, dev_y)
plt.xlabel('Ages')
plt.ylabel('Median Salary (USD)')
plt.title('Median Salary (USD) by Age')
plt.show()
#Basic line graph using python module matplotlib
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()
Use matplotlib in python
import matplotlib.pyplot as plt # Import the matplotlib module
from matplotlib import style # Optionally you dont need to use style
style.use('ggplot') # Just for style
x = [10, 20, 30, 40, 50] # Get points to plot on graph
plt.plot(x) # We want to plot x on our graph
plt.show()
matplotlib.pyplot
plt.plot([1, 2, 3, 4], [1, 4, 9, 16]) # plot x against y
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