Matplotlib Labels and Title

Create Labels for a Plot

With Pyplot, you can use the xlabel() and
ylabel()
functions to set a label for the x- and y-axis.

Example

Add labels to the x- and y-axis:

import matplotlib.pyplot as plt

x = np.array([80, 85, 90, 95, 100, 105, 110, 115, 120, 125])

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:

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Create a Title for a Plot

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

Example

Add a plot title and labels for the x- and y-axis:

import matplotlib.pyplot as plt

x = np.array([80, 85, 90, 95, 100, 105, 110, 115, 120, 125])

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:

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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:

import matplotlib.pyplot as plt

x = np.array([80, 85, 90, 95, 100, 105, 110, 115, 120, 125])

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 Watch Data”, fontdict = font1)

plt.xlabel(“Average Pulse”, fontdict = font2)

plt.ylabel(“Calorie Burnage”, fontdict = font2)

plt.plot(x, y)

plt.show()

Result:

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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:

import matplotlib.pyplot as plt

x = np.array([80, 85, 90, 95, 100, 105, 110, 115, 120, 125])

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:

Try it Yourself »

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