从给定数组中删除等于元素的所有元素。
Syntax
from pyspark.sql import functions as sf
sf.array_remove(col, element)
参数
| 参数 | 类型 | Description |
|---|---|---|
col |
pyspark.sql.Column 或 str |
包含数组的列的名称 |
element |
任意 | 要从数组中删除的元素或 Column 表达式 |
退货
pyspark.sql.Column：从输入列中排除给定值的数组的新列。
例子
示例 1：从简单数组中删除特定值
from pyspark.sql import functions as sf
df = spark.createDataFrame([([1, 2, 3, 1, 1],)], ['data'])
df.select(sf.array_remove(df.data, 1)).show()
+---------------------+
|array_remove(data, 1)|
+---------------------+
| [2, 3]|
+---------------------+
示例 2：从多个数组中删除特定值
from pyspark.sql import functions as sf
df = spark.createDataFrame([([1, 2, 3, 1, 1],), ([4, 5, 5, 4],)], ['data'])
df.select(sf.array_remove(df.data, 5)).show()
+---------------------+
|array_remove(data, 5)|
+---------------------+
| [1, 2, 3, 1, 1]|
| [4, 4]|
+---------------------+
示例 3：删除数组中不存在的值
from pyspark.sql import functions as sf
df = spark.createDataFrame([([1, 2, 3],)], ['data'])
df.select(sf.array_remove(df.data, 4)).show()
+---------------------+
|array_remove(data, 4)|
+---------------------+
| [1, 2, 3]|
+---------------------+
示例 4：从具有所有相同值的数组中删除值
from pyspark.sql import functions as sf
df = spark.createDataFrame([([1, 1, 1],)], ['data'])
df.select(sf.array_remove(df.data, 1)).show()
+---------------------+
|array_remove(data, 1)|
+---------------------+
| []|
+---------------------+
示例 5：从空数组中删除值
from pyspark.sql import functions as sf
from pyspark.sql.types import ArrayType, IntegerType, StructType, StructField
schema = StructType([
StructField("data", ArrayType(IntegerType()), True)
])
df = spark.createDataFrame([([],)], schema)
df.select(sf.array_remove(df.data, 1)).show()
+---------------------+
|array_remove(data, 1)|
+---------------------+
| []|
+---------------------+
示例 6：从简单数组中删除列的值
from pyspark.sql import functions as sf
df = spark.createDataFrame([([1, 2, 3, 1, 1], 1)], ['data', 'col'])
df.select(sf.array_remove(df.data, df.col)).show()
+-----------------------+
|array_remove(data, col)|
+-----------------------+
| [2, 3]|
+-----------------------+