Flash cards
Review the key moves
What is the main idea behind Matplotlib Labels and Title?
Lesson checks
Practice each idea before moving on
Short Mimo-style checks built from this lesson's code, terms, and sequence.
Which statement best captures the main point of this lesson?
Complete the missing token from the example code.
___ numpy as npPut the learning moves in the order that makes the concept easiest to apply.
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
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()Create a Title for a Plot
With Pyplot, you can use the title() function to set a title for the plot.
Example
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.title("Sports Watch Data")
plt.xlabel("Average
Pulse")
plt.ylabel("Calorie Burnage")
plt.show()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
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()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
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.title("Sports Watch Data", loc = 'left')
plt.xlabel("Average
Pulse")
plt.ylabel("Calorie Burnage")
plt.plot(x,
y)
plt.show()