Which of the following tools is primarily used for data visualization in data science?

Matplotlib is primarily used for data visualization in data science, making it the correct choice. It is a versatile library in Python that allows users to create static, animated, and interactive visualizations. With Matplotlib, data scientists can produce a wide range of graph types, such as line charts, scatter plots, bar charts, and more, enabling them to effectively explore and communicate insights from their data.

Pandas, while it contains visualization capabilities, is primarily a data manipulation and analysis tool. It can create basic plots, but its main focus is on providing data structures and functions for handling structured data.

Scikit-learn is a library designed for machine learning that provides tools for classification, regression, clustering, and model selection, among others. It does not directly focus on data visualization but can be used in conjunction with visualization libraries to present model results.

TensorFlow is an open-source machine learning framework primarily used for building and training deep learning models. Its primary emphasis is on computational graphs and neural network implementation rather than data visualization.

Therefore, Matplotlib stands out as the go-to tool specifically tailored for data visualization in data science.