On the PySpark API documentation, explain how to select specific columns from a DataFrame and provide a runnable Python code example demonstrating how to use the `select` method to choose 'name' and 'age' from a DataFrame named `my_data`.
Navigate to 'spark.apache.org/docs/latest/api/python/index.html'. Click on the 'API Reference' link. Locate and navigate to the documentation for the 'DataFrame' class. Locate the 'select' method within the 'DataFrame' class documentation. Extract the description of the `select` method's purpose. Construct a runnable Python code snippet demonstrating how to use `select` to choose 'name' and 'age' from a DataFrame named `my_data`, including necessary SparkSession setup and sample data creation.
The agent successfully navigates to the PySpark API Reference. The agent successfully locates the `DataFrame` class documentation. The agent identifies the `select` method. The agent explains that `select` projects expressions or selects columns to create a new DataFrame. The agent provides a correct and runnable Python code snippet that uses `my_data.select('name', 'age')` (or equivalent column selection methods) to select the specified columns, including SparkSession initialization and sample DataFrame creation.