Answer-first summary for fast verification
Answer: Apply astype to specific columns using psdf[‘column_name‘].astype(‘desired_type‘).
The correct answer is **B**. To perform type casting on specific columns in a pandas-on-Spark DataFrame, you use the `astype` method on the desired columns. This allows for explicit control over data types, ensuring compatibility, optimizing performance, and enforcing data integrity. Automatic conversions do occur, but explicit casting is often necessary for specific needs. Incorrect options include: **A** (automatic conversion doesn't cover all needs), **C** (casting the entire DataFrame is not targeted), and **D** (type casting is indeed supported).
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How can you perform type casting for specific columns when converting a pandas-on-Spark DataFrame to a PySpark DataFrame using the astype method?
A
Type casting is automatic; no additional steps are needed.
B
Apply astype to specific columns using psdf[‘column_name‘].astype(‘desired_type‘).
C
Use the astype method on the entire DataFrame.
D
Type casting is not supported in pandas-on-Spark.
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