您需要添加一列 withColumn 因为 approxQuantile 返回浮点数列表，而不是spark列。

import pyspark.sql.functions as F

df2 = df.withColumn('count_media', F.lit(df.approxQuantile('count',[0.5],0.1)[0]))

df2.show()
+-----------+-----+-----------+
|parsed_date|count|count_media|
+-----------+-----+-----------+
| 2017-12-16|    2|        2.0|
| 2017-12-16|    2|        2.0|
| 2017-12-17|    2|        2.0|
| 2017-12-17|    2|        2.0|
| 2017-12-18|    1|        2.0|
| 2017-12-19|    4|        2.0|
| 2017-12-19|    4|        2.0|
| 2017-12-19|    4|        2.0|
| 2017-12-19|    4|        2.0|
| 2017-12-20|    1|        2.0|
+-----------+-----+-----------+

您也可以使用 approx_percentile / percentile_approx spark sql中的函数：

import pyspark.sql.functions as F

df2 = df.withColumn('count_media', F.expr("approx_percentile(count, 0.5, 10) over ()"))

df2.show()
+-----------+-----+-----------+
|parsed_date|count|count_media|
+-----------+-----+-----------+
| 2017-12-16|    2|          2|
| 2017-12-16|    2|          2|
| 2017-12-17|    2|          2|
| 2017-12-17|    2|          2|
| 2017-12-18|    1|          2|
| 2017-12-19|    4|          2|
| 2017-12-19|    4|          2|
| 2017-12-19|    4|          2|
| 2017-12-19|    4|          2|
| 2017-12-20|    1|          2|
+-----------+-----+-----------+