df.select(col("column_name")) # 重命名列 df.select(col("column_name").alias("new_column_name")) 2.字符串操作 concat:连接多个字符串。 substring:从字符串中提取子串。 trim:去除字符串两端的空格。 ltrim:去除字符串左端的空格。 rtrim:去除字符串右端的空格。 upper/lower:将字符串转换为大写/小写。
df.withColumn("new_column", concat(df["first_name"], lit(" "), df["last_name"])) 通过使用 withColumn() 方法,你可以按照需要对 DataFrame 进行列级别的变换和操作。它提供了一种灵活的方式来构建和转换 DataFrame,以适应特定的数据处理需求。when() otherwise()在PySpark 中,when() 函数用于执行条件...
--Returning a Column that contains <value> in every row: F.lit(<value>) -- Example df = df.withColumn("test",F.lit(1)) -- Example for null values: you have to give a type to the column since None has no type df = df.withColumn("null_column",F.lit(None).cast("string")) ...
concat()function of Pyspark SQL is used to concatenate multiple DataFrame columns into a single column. It can also be used to concatenate column types string, binary, and compatible array columns. pyspark.sql.functions.concat(*cols) Below is the example of using Pysaprk conat() function on ...
# -*- coding: UTF-8 -*- import json import safety_dispatch.common.common_constant as const from safety_dispatch.common.utils.date_utils import DateUtilsHelper from pyspark.sql.functions import udf, when, split, lit, explode, concat, concat_ws from pyspark.sql.types import StringType, LongTyp...
spark.sql("select name, concat_ws(',',languagesAtSchool) as languagesAtSchool," + \ " currentState from ARRAY_STRING") \ .show(truncate=False) Complete Example Below is a complete PySpark DataFrame example of converting an array of String column to a String using a Scala example. ...
from pyspark.sql import functions as f def generate_udf(constant_var): def test(col1, col2): if col1 == col2: return col1 else: return constant_var return f.udf(test, StringType()) df.withColumn('new_column',generate_udf('default_value')(f.col('userID'), f.col('movieID'))...
90.pyspark.sql.functions.to_utc_timestamp(timestamp, tz) 91.pyspark.sql.functions.year(col) 92.pyspark.sql.functions.when(condition, value) 93.pyspark.sql.functions.udf(f, returnType=StringType) 参考链接 github.com/QInzhengk/Math-Model-and-Machine-Learning 公众号:数学建模与人工智能 RDD和DataF...
df_with_nested_column = df.withColumn("address", struct(df["city"])) 在上述代码中,我们使用struct(df["city"])创建了一个名为"address"的嵌套列,其中包含了原始DataFrame中的"city"列。 如果要添加多个嵌套列,可以在struct函数中传递多个列名,例如: ...
b = a.withColumn("Concated_Value", concat(a.Name.substr(-3,3),lit("--"),a.Name.substr(1,3))).show() This will concatenate the last 3 values of a substring with the first 3 values and display the output in a new Column. If the string length is the same or smaller then all...