Which libraries can be used for data visualization in Databricks?

The libraries used for data visualization in Databricks include Matplotlib, Seaborn, and Plotly, which are popular Python libraries designed specifically for creating visualizations. Each of these libraries has unique strengths: Matplotlib is a foundational library for 2D plots and graphics, Seaborn builds on Matplotlib and simplifies the creation of attractive statistical graphics, and Plotly enables interactive visualizations that enhance user engagement. Together, these libraries facilitate a comprehensive approach to plotting and visualizing data within the Databricks environment, allowing users to explore data effectively.

The other choices include databases and libraries that may not focus on visualizations. SQL and NoSQL databases are primarily used for data storage and retrieval rather than visualization. Excel and Access, while they offer some visualization features, are not the primary tools typically utilized in a Databricks context. Pandas and NumPy are primarily focused on data manipulation and numeric computations, respectively, rather than on data visualization, even though they are often used in conjunction with visualization libraries.