具有不同列的 Pysaprk 多组分组 [英] Pysaprk multi groupby with different column

问题描述

我有如下数据

year    name    percent     sex
1880    John    0.081541    boy
1881    William 0.080511    boy
1881    John    0.050057    boy

我需要使用不同的列进行分组和计数

I need to groupby and count using different columns

df_year = df.groupby('year').count()
df_name = df.groupby('name').count()
df_sex = df.groupby('sex').count()

然后我必须创建一个窗口来获取每列的前 3 个数据

then I have to create a Window to get the top-3 data by each column

window = Window.partitionBy('year').orderBy(col("count").desc())
top4_res = df_year.withColumn('topn', func.row_number().over(window)).
                                              filter(col('topn') <= 4).repartition(1)

假设我有数百列要进行分组和计数以及 topk_3 操作.

suppose I have hundreds of columns to groupby and count and topk_3 operation.

我可以一次性完成吗?

或者有什么更好的方法吗?

or is there any better ways to do it?

推荐答案

我不确定这是否能满足您的要求，但如果您对单个数据框没问题，我认为它可以为您提供一个开始，如果否则.您可以堆叠这 3 列(或更多)，然后分组并计算:

I am not sure if this will meet your requirement but if you are okay with a single dataframe, i think it can give you a start, let me know if otherwise. You can stack these 3 columns (or more) and then groupby and take count :

cols = ['year','name','sex']
e = f"""stack({len(cols)},{','.join(map(','.join,
             (zip([f'"{i}"' for i in cols],cols))))}) as (col,val)"""

(df.select(*[F.col(i).cast('string') for i in cols]).selectExpr(e)
 .groupBy(*['col','val']).agg(F.count("col").alias("Counts")).orderBy('col')).show()

+----+-------+------+
| col|    val|Counts|
+----+-------+------+
|name|   John|     2|
|name|William|     1|
| sex|    boy|     3|
|year|   1881|     2|
|year|   1880|     1|
+----+-------+------+

如果你想要一个宽的形式，你也可以旋转，但我认为长的形式会有所帮助:

If you want a wide form you can also pivot but i think long form would be helpful:

(df.select(*[F.col(i).cast('string') for i in cols]).selectExpr(e)
 .groupBy('col').pivot('val').agg(F.count('val')).show())

+----+----+----+----+-------+----+
| col|1880|1881|John|William| boy|
+----+----+----+----+-------+----+
|name|null|null|   2|      1|null|
|year|   1|   2|null|   null|null|
| sex|null|null|null|   null|   3|
+----+----+----+----+-------+----+

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