What is a DataFrame in Databricks?

A DataFrame in Databricks is a structured data collection organized into columns, which aligns perfectly with the definition provided in the correct option. This structure allows for efficient processing and manipulation of large datasets, similar to a table in a relational database or an Excel spreadsheet but with more powerful capabilities.

DataFrames enable users to perform complex queries, filtering, and transformations on data with ease. In Databricks, they are built on top of Apache Spark, providing an optimized execution engine and making it capable of handling big data.

In contrast, other alternatives do not accurately represent the concept of a DataFrame. For instance, a collection of PDFs refers to documents and lacks the structured data organization needed for analytical processes. A spreadsheet application implies a user interface for manual data entry and analysis but does not equate to a DataFrame's operational capabilities in a distributed computing environment. Finally, an image processing tool pertains to applications designed for manipulating images, which is unrelated to the structured data analysis that DataFrames facilitate.