評估一份條件清單，並回傳多種可能結果表達式之一。
語法
when(condition, value)
參數
| 參數 | 類型 | 說明 |
|---|---|---|
condition |
資料行 | 布林條件 |
value |
value | 若條件為真，則回傳的值 |
退貨
資料行
Examples
範例 1：使用 when() 條件與值來建立新欄位。
from pyspark.sql import functions as sf
df = spark.createDataFrame([(2, "Alice"), (5, "Bob")], ["age", "name"])
result = df.select(df.name, sf.when(df.age > 4, 1).when(df.age < 3, -1).otherwise(0))
result.show()
# +-----+------------------------------------------------------------+
# | name|CASE WHEN (age > 4) THEN 1 WHEN (age < 3) THEN -1 ELSE 0 END|
# +-----+------------------------------------------------------------+
# |Alice| -1|
# | Bob| 1|
# +-----+------------------------------------------------------------+
範例二：串接多個 when() 條件。
from pyspark.sql import functions as sf
df = spark.createDataFrame([(1, "Alice"), (4, "Bob"), (6, "Charlie")], ["age", "name"])
result = df.select(
df.name,
sf.when(df.age < 3, "Young").when(df.age < 5, "Middle-aged").otherwise("Old")
)
result.show()
# +-------+---------------------------------------------------------------------------+
# | name|CASE WHEN (age < 3) THEN Young WHEN (age < 5) THEN Middle-aged ELSE Old END|
# +-------+---------------------------------------------------------------------------+
# | Alice| Young|
# | Bob| Middle-aged|
# |Charlie| Old|
# +-------+---------------------------------------------------------------------------+
範例三：使用字面值作為條件。
from pyspark.sql import functions as sf
df = spark.createDataFrame([(2, "Alice"), (5, "Bob")], ["age", "name"])
result = df.select(
df.name, sf.when(sf.lit(True), 1).otherwise(
sf.raise_error("unreachable")).alias("when"))
result.show()
# +-----+----+
# | name|when|
# +-----+----+
# |Alice| 1|
# | Bob| 1|
# +-----+----+