如果未调用Column.otherwise(),则对于不匹配的条件将返回None df = spark.createDataFrame( [(2, "Alice"), (5, "Bob")], ["age", "name"])df.show()+---+---+|age| name|+---+---+| 2|Alice|| 5| Bob|+---+---+# 查询条件进行筛选,当when不配合otherwise 默认使用null代替df.select...
Column.eqNullSafe(other: Union[Column, LiteralType, DecimalLiteral, DateTimeLiteral]) → Column 1. 对空值的相等测试。 df1 = spark.createDataFrame([ Row(id=1, value='foo'), Row(id=2, value=None) ]) df1.select( df1['value'] == 'foo', df1['value'].eqNullSafe('foo'), df1['value...
root|-- firstname: string (nullable = true)|-- middlename: string (nullable = true)|-- lastname: string (nullable = true)|-- id: string (nullable = true)|-- gender: string (nullable = true)|-- salary: integer (nullable = true)+---+---+---+---+---+---+|firstname|midd...
1、 agg(expers:column*) 返回dataframe类型 ,同数学计算求值 df.agg(max("age"), avg("salary")) df.groupBy().agg(max("age"), avg("salary")) 2、 agg(exprs: Map[String, String]) 返回dataframe类型 ,同数学计算求值 map类型的 df.agg(Map("age" -> "max", "salary" -> "avg")) df....
"schema":"PanderaSchema", "column":"meta", "check":"dtype('MapType(StringType(), StringType(), True)')", "error":"expected column 'meta' to have type MapType(StringType(), StringType(), True), got MapType(StringType(), StringType(), False)" } ] }, "DATA...
PySpark 提供pyspark.sql.types import StructField类来定义列,包括列名(String)、列类型(DataType)、可空列(Boolean)和元数据(MetaData)。 将PySpark StructType & StructField 与 DataFrame 一起使用 在创建 PySpark DataFrame 时,我们可以使用 StructType 和 StructField 类指定结构。StructType 是 StructField 的集合...
|-- day: string (nullable = true) |-- tasks: array (nullable = true) | |-- element: string (containsNull = true) +---+---+ |day | tasks | +---+---+ |星期天 |[抽烟, 喝酒, 去烫头] | +---+---+ 接下来获得该数组的大小,对其进行排序,并检查在该...
通过使用expr()和regexp_replace()可以用另一个DataFrame column中的值替换列值。 df=spark.createDataFrame([("ABCDE_XYZ","XYZ","FGH")],("col1","col2","col3"))df.withColumn("new_column",F.expr("regexp_replace(col1, col2, col3)").alias("replaced_value")).show() ...
To create a new column, use the withColumn method. The following example creates a new column that contains a boolean value based on whether the customer account balance c_acctbal exceeds 1000:Python Копирај df_customer_flag = df_customer.withColumn("balance_flag", col("c_acct...
Pardon, as I am still a novice with Spark. I am working with a Spark dataframe, with a column where each element contains a nested float array of variable lengths, typically 1024, 2048, or 4096. (These are vibration waveform signatures of different duration.) ...