F — Format

Rules that enforce idiomatic use of the PySpark DataFrame API — covering code style, readability, and correct function usage.

Rule	Title
F001	Avoid chaining withColumn() and withColumnRenamed()
F002	Avoid drop() — use select() for explicit columns
F003	Avoid selectExpr() — prefer select() with col()
F004	Avoid spark.sql() — prefer native DataFrame API
F005	Avoid stacking multiple withColumn() — use withColumns()
F006	Avoid stacking multiple withColumnRenamed() — use withColumnsRenamed()
F007	Prefer filter() before select() for clarity
F008	Avoid print() — prefer the logging module
F009	Avoid nested when() — use stacked .when().when().otherwise()
F010	Always include otherwise() at the end of a when() chain
F011	Avoid backslash line continuation — use parentheses
F012	Always wrap literal values with lit()
F013	Avoid reserved column names with __ prefix and __ suffix
F014	Avoid explode_outer() — handle nulls with higher-order functions
F015	Avoid multiple consecutive filter() calls — combine conditions
F016	Avoid long DataFrame renaming chains — overwrite the same variable
F017	Avoid expr() — use native PySpark functions instead
F018	Use Spark native datetime functions instead of Python datetime objects
F019	Avoid inferSchema=True and mergeSchema=True in Spark read options
F020	Avoid select("*") — use explicit column names