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Python•Data Science and Scientific Python

Matplotlib Labels and Title

Create Labels for a Plot

With Pyplot, you can use the xlabel() and ylabel()

Formula

functions to set a label for the x - and y - axis.

Example

Formula

Add labels to the x - and y - axis:
import numpy as np import matplotlib.pyplot as plt x = np.array([80,

85, 90, 95, 100, 105, 110, 115, 120, 125])

Formula

y = np.array([240, 250, 260,

270, 280, 290, 300, 310, 320, 330]) plt.plot(x, y) plt.xlabel("Average Pulse") plt.ylabel("Calorie Burnage") plt.show()

Result:

Create a Title for a Plot

With Pyplot, you can use the title() function to set a title for the plot.

Example

Formula

Add a plot title and labels for the x - and y - axis:
import numpy as np import matplotlib.pyplot as plt x = np.array([80,

85, 90, 95, 100, 105, 110, 115, 120, 125])

Formula

y = np.array([240, 250, 260,

270, 280, 290, 300, 310, 320, 330]) plt.plot(x, y) plt.title("Sports Watch Data") plt.xlabel("Average Pulse") plt.ylabel("Calorie Burnage") plt.show()

Result:

Set Font Properties for Title and Labels

You can use the fontdict parameter in xlabel(), ylabel(), and title() to set font properties for the title and labels.

Example

Set font properties for the title and labels:

Formula

import numpy as np import matplotlib.pyplot as plt x = np.array([80,

85, 90, 95, 100, 105, 110, 115, 120, 125])

Formula

y = np.array([240, 250, 260,

270, 280, 290, 300, 310, 320, 330])

font1 = {'family':'serif','color':'blue','size':20}
font2 = {'family':'serif','color':'darkred','size':15}
plt.title("Sports

Formula

Watch Data", fontdict = font1)

plt.xlabel("Average Pulse", fontdict = font2)

Formula

plt.ylabel("Calorie Burnage", fontdict = font2)

plt.plot(x, y) plt.show()

Result:

Position the Title

You can use the loc parameter in title() to position the title. Legal values are: 'left', 'right', and 'center'. Default value is 'center'.

Example

Position the title to the left:

Formula

import numpy as np import matplotlib.pyplot as plt x = np.array([80,

85, 90, 95, 100, 105, 110, 115, 120, 125])

Formula

y = np.array([240, 250, 260,

270, 280, 290, 300, 310, 320, 330]) plt.title("Sports Watch Data", loc = 'left') plt.xlabel("Average Pulse") plt.ylabel("Calorie Burnage") plt.plot(x, y) plt.show()

Result:

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