The correct answer is D. Matplotlib.

Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. Matplotlib can be used in Python scripts, the Python and IPython shell, web application servers, and various graphical user interface toolkits.

dtreeviz is a Python library for visualizing decision trees. It can be used to visualize the structure of a decision tree, as well as the distribution of data points at each node in the tree.

Pandas is a Python library for data analysis. It provides high-performance, easy-to-use data structures and data analysis tools for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data.

Seaborn is a Python data visualization library based on Matplotlib. It provides a high-level interface for drawing attractive statistical graphics.

Here is an example of how to use Matplotlib to visualize a decision tree:

“`import matplotlib.pyplot as plt
from sklearn.tree import DecisionTreeClassifier

Create a decision tree classifier

clf = DecisionTreeClassifier()

Train the classifier on the Iris dataset

clf.fit(X_train, y_train)

Predict the labels of the test set

y_pred = clf.predict(X_test)

Create a figure

fig, ax = plt.subplots()

Plot the decision tree

plt.tree(clf, feature_names=features, class_names=classes, filled=True)

Show the figure

plt.show()
“`

This will produce a figure showing the decision tree classifier. The figure will show the features that were used to split the data, as well as the classes that were assigned to each node in the tree.