Can you explain what DataFrames are?

DataFrames are tabular data structures that provide a schema, column names, and support operations such as filtering, aggregation, and joins. In Pandas, a DataFrame is an in‑memory table that supports vectorized operations and is ideal for quick prototyping. In Spark, a DataFrame is distributed across a cluster, enabling large‑scale data processing with lazy evaluation and integration with SQL. DataFrames allow you to write concise code for ETL, data analysis, and machine learning pipelines. For example, you can read a CSV into a DataFrame, filter rows, group by a column, and compute aggregates in a few lines of code. They are the foundation of many data science libraries and are essential for efficient data manipulation.