使用spark将每行中的值转换为新列

Question

我正在使用python中的Spark从XML文件创建数据帧。我想要做的是将每一行中的值转换为新列，并使其成为伪变量。

下面是一个示例。

输入：

 id  |         classes          |
-----+--------------------------+
 132 |  economics,engineering   |
 201 |  engineering             |
 123 |  sociology,philosophy    |
 222 |  philosophy              |
--------------------------------

输出：

 id  | economics | engineering | sociology | philosophy
-----+-----------+-------------+-----------+-----------
 132 |    1      |     1       |      0    |     0
 201 |    0      |     1       |      0    |     0
 123 |    0      |     0       |      1    |     1
 222 |    0      |     0       |      0    |     1
--------------------------------------------------------

Answer 1

将列分解为多行引用：Explode in PySpark

import pyspark.sql.functions as F

df = spark.createDataFrame([(132, "economics,engineering"),(201, "engineering"),(123, "sociology,philosophy"),(222, "philosophy")], ["id", "classes"])

+---+--------------------+
| id|             classes|
+---+--------------------+
|132|economics,enginee...|
|201|         engineering|
|123|sociology,philosophy|
|222|          philosophy|
+---+--------------------+


explodeCol = df.select(col("id"), F.explode(F.split(col("classes"), ",")).alias("branch"))
+---+-----------+
| id|     branch|
+---+-----------+
|132|  economics|
|132|engineering|
|201|engineering|
|123|  sociology|
|123| philosophy|
|222| philosophy|
+---+-----------+

explodeCol.groupBy("id").pivot("branch").agg(F.sum(lit(1))).na.fill(0).show()
+---+---------+-----------+----------+---------+
| id|economics|engineering|philosophy|sociology|
+---+---------+-----------+----------+---------+
|222|        0|          0|         1|        0|
|201|        0|          1|         0|        0|
|132|        1|          1|         0|        0|
|123|        0|          0|         1|        1|
+---+---------+-----------+----------+---------+

有关更详细Spark文档，请参阅http://spark.apache.org/docs/2.4.0/api/python/pyspark.sql.html