使用python将多个列合并到pyspark数据帧中的一列中

Question

我需要将数据框的多个列合并为一个列，其中list（或tuple）作为python中使用pyspark的列的值。

Input dataframe:

+-------+-------+-------+-------+-------+
| name  |mark1  |mark2  |mark3  | Grade |
+-------+-------+-------+-------+-------+
| Jim   | 20    | 30    | 40    |  "C"  |
+-------+-------+-------+-------+-------+
| Bill  | 30    | 35    | 45    |  "A"  |
+-------+-------+-------+-------+-------+
| Kim   | 25    | 36    | 42    |  "B"  |
+-------+-------+-------+-------+-------+

Output dataframe should be

+-------+-----------------+
| name  |marks            |
+-------+-----------------+
| Jim   | [20,30,40,"C"]  |
+-------+-----------------+
| Bill  | [30,35,45,"A"]  |
+-------+-----------------+
| Kim   | [25,36,42,"B"]  |
+-------+-----------------+

Answer 1

看看这个文档： https ： //spark.apache.org/docs/2.1.0/ml-features.html#vectorassembler

from pyspark.ml.linalg import Vectors
from pyspark.ml.feature import VectorAssembler

assembler = VectorAssembler(
    inputCols=["mark1", "mark2", "mark3"],
    outputCol="marks")

output = assembler.transform(dataset)
output.select("name", "marks").show(truncate=False)

Answer 2

如果这仍然相关，则可以使用StringIndexer将字符串值编码为浮点替换。

Answer 3

列可以与sparks数组函数合并：

import pyspark.sql.functions as f

columns = [f.col("mark1"), ...] 

output = input.withColumn("marks", f.array(columns)).select("name", "marks")

您可能需要更改条目的类型才能使合并成功

Answer 4

您可以在以下选项中执行此操作：

from pyspark.sql.functions import *    
df.select( 'name' ,
        concat( 
            col("mark1"), lit(","), 
            col("mark2"), lit(","), 
            col("mark3"), lit(","),
            col("Grade")
        ).alias('marks')  
    )

如果[]必要，可以添加点亮功能。

from pyspark.sql.functions import *    
df.select( 'name' ,
        concat(lit("["), 
            col("mark1"), lit(","), 
            col("mark2"), lit(","), 
            col("mark3"), lit(","),
            col("Grade"), lit("]")
        ).alias('marks')  
    )