The title() method in the Matplotlib module is used to specify the title of the visualization depicted and display the title using various attributes. In this article, we will learn about this function with the help of examples.

Syntax: matplotlib.pyplot.title(label, fontdict=None, loc=’center’, pad=None, **kwargs)

Parameters:

1. label(str): This argument refers to the actual title text string of the visualization depicted.
2. fontdict(dict): This argument controls the appearance of the text such as text size, text alignment etc using a dictionary.
3. loc(str): This argument refers to the location of the title and takes string values like ‘center’, ‘left’ and ‘right’.
4. pad(float): This argument refers to the offset of the title from the top of the axes in points. Its default values in None.
5. **kwargs: This argument refers to the use of other keyword arguments as text properties such as color, fonstyle, linespacing, backgroundcolor, rotation, etc.

Return Type:

The return type is generally a matplotlib.text.Text object. It returns the Text object that represents the title.

1. Displaying a Title on a Linear Graph

In this example, a linear graph is created and title “Linear Graph” is added to the plot using the matplotlib.pyplot.title() function. To display the title setting the label argument is the minimum requirement.

import matplotlib.pyplot as plt

y = [0, 1, 2, 3, 4, 5]
x = [0, 5, 10, 15, 20, 25]

plt.plot(x, y, color='green')
plt.xlabel('x')
plt.ylabel('y')

plt.title("Linear graph")
plt.show()

Output:

Displaying Title

2. Visualizing the ReLU Function with a Title

Here a ReLU function graph is created using matplotlib.pyplot based on the provided x-coordinates. The title “ReLU Function Graph” is added to the plot with custom styling.

x = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]
y = []

for i in range(len(x)):
    y.append(max(0, x[i]))

plt.plot(x, y, color='green')
plt.xlabel('x')
plt.ylabel('y')

plt.title(label="ReLU function graph",
          fontsize=40,
          color="green")

Output:

Visualizing the ReLU Function

3. Customizing a Bar Graph Title

In this example, a bar graph is created and title is customized with the fontweight key from the fontdict argument and the pad argument along with the label parameter.

import matplotlib.pyplot as plt
import numpy as np

language = ['C', 'C++', 'Java', 'Python']
users = [80, 60, 130, 150]

index = np.arange(len(language))
plt.bar(index, users, color='green')
plt.xlabel('Users')
plt.ylabel('Language')
plt.xticks(index, language)

plt.title(label='Number of Users of a particular Language',
          fontweight=10,
          pad='2.0')

Output:

Customizing a Bar Graph Title

4. Customizing Title of Pie Chart Title

In this example, a pie chart is created and title is customized with the label, fontweight keyword from the fontdict and the fontstyle (**kwargs) argument which can take values such as italic, bold or oblique.

foodPreference = ['Vegetarian', 'Non Vegetarian',
                  'Vegan', 'Eggitarian']

consumers = [30, 100, 10, 60]

fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1])
ax.axis('equal')
ax.pie(consumers, labels=foodPreference,
       autopct='%1.2f%%')

plt.title(label="Society Food Preference",
          loc="left",
          fontstyle='italic')

Output:

Customizing Title of Pie Chart Title

5. Customizing Sinusoidal Signal Title

In this example, a sinusoidal signal is visualized and title is customized with the label argument set to ‘Signal’, loc argument set to right and the rotation argument (**kwargs) set to 45 degrees.

from matplotlib import pyplot
import numpy

signalTime = numpy.arange(0, 100, 0.5)

signalAmplitude = numpy.sin(signalTime)

pyplot.plot(signalTime, signalAmplitude, color='green')

pyplot.xlabel('Time')
pyplot.ylabel('Amplitude')

pyplot.title("Signal",
             loc='right',
             rotation=45)

Output:

Customizing Title of Sinusoidal Signal

6. Displaying a Image Title

In this example, an image is displayed and the title is customized with the label argument set to “Geeks 4 Geeks” the fontsize key from fontdict set to 20 and additional parameters backgroundcolor set to ‘green’ and color set to ‘white’.

from PIL import ImageTk, Image
from matplotlib import pyplot as plt

testImage = Image.open('g4g.png')

plt.title("Geeks 4 Geeks",
          fontsize='20',
          backgroundcolor='green',
          color='white')
plt.imshow(testImage)

Output:

Image Displayed

With these methods, we can customize title of our plots and can make our visualizations better and interactive.

riturajsaha

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Article Tags :

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• Write From Home
• Matplotlib Pyplot-class
• Python-Library
• Python-matplotlib

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