Python Data Science Matplotlib Labels and Title Set A Label for the x- and y-axis

Label and titles are used to set a label for the x- and y-axis. You can use the xlabel() and ylabel() functions to set a label with Pyplot.

Example 1: Add labels to the x- and y-axis.

Code

import numpy as np
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()

the output will be

Creating a Title for the Plot:

You can use the title() function to set a title for your plot with Pyplot. Example 2: Add a plot title and labels for the x- and y-axis.

Code

import numpy as np
import matplotlib.pyplot as plt

x = np.array([80, 85, 90, 95, 100, 105, 110, 115, 120, 125])
y = np.array([245, 255, 265, 275, 285, 295, 305, 315, 325, 335])

plt.plot(x, y)

plt.title("Sports Watch Data")
plt.xlabel("Average Pulse")
plt.ylabel("Calorie Burnage")

plt.show()

the output will be

Setting Font Properties for Title and Labels

The fontdict parameter can be used in xlabel(), ylabel(), and title() to set font properties for the title and labels.

Example 3: Set font properties for the title and labels

import numpy as np
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()

the output will be

Positioning the Title

One can use the loc parameter in title() to position the title.

Legal values are: 'left', 'right', and 'center'. Default value is 'center'.

Example 4: Position the title to the left.

Code

import numpy as np
import matplotlib.pyplot as plt

x = np.array([80, 85, 90, 95, 100, 105, 110, 115, 120, 125])
y = np.array([245, 255, 265, 275, 285, 295, 305, 315, 325, 335])

font1 = {'family':'serif','color':'blue','size':20}
font2 = {'family':'serif','color':'darkred','size':15}

plt.title("Sports Watch Data", fontdict = font1, loc = 'left')
plt.xlabel("Average Pulse", fontdict = font2)
plt.ylabel("Calorie Burnage", fontdict = font2)

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

the output will be