我有一个只有一行的df。
id |id2 |score|score2|
----------------------
0 |1 |4 |2 |
,我想在底部添加一行百分比,即每个数字除以7
0/7 |1/7 |4/7 |2/7 |
但是我想出的解决方案非常慢
temp = [i/7 for i in df.collect()[0]]
row = sc.parallelize(Row(temp)).toDF()
df.union(row)
这花费了21秒钟来运行,几乎所有代码都是最后两行代码。有一个更好的方法吗?我的另一个想法是转置表格,然后可以使用df.withColumn()轻松完成。理想情况下,我也想用0过滤掉该列,但是我还没有真正研究过
答案 0 :(得分:1)
检查一下,让我知道是否有帮助
from pyspark.sql import SparkSession
from pyspark.sql import functions as F
spark = SparkSession.builder \
.appName('practice')\
.getOrCreate()
sc= spark.sparkContext
df = sc.parallelize([
(0,1,4,2)]).toDF(["id", "id2","score","score2"])
df2 = df.select(*[(F.col(column)/7).alias(column) for column in df.columns])
df3 = df.union(df2)
df3.show()
+---+-------------------+------------------+------------------+
| id| id2| score| score2|
+---+-------------------+------------------+------------------+
|0.0| 1.0| 4.0| 2.0|
|0.0|0.14285714285714285|0.5714285714285714|0.2857142857142857|
+---+-------------------+------------------+------------------+
如果要。过滤出包含0的列,您可以使用以下代码
non_zero_cols = [c for c in df.columns if df[[c]].first()[c] > 0]
df1 = df.select(*non_zero_cols)
df2 = df1.select(*[(F.col(column)/7).alias(column) for column in
df1.columns])
df3 = df1.union(df2)
df3.show()
+-------------------+------------------+------------------+
| id2| score| score2|
+-------------------+------------------+------------------+
| 1.0| 4.0| 2.0|
|0.14285714285714285|0.5714285714285714|0.2857142857142857|
+-------------------+------------------+------------------+
请检查以下具有类型列的df代码
non_zero_cols = [c for c in df.columns if df[[c]].first()[c] > 0]
df1 = df.select(*non_zero_cols, F.lit('count').alias('type') )
df2 = df1.select(*[(F.col(column)/7).alias(column) for column in
df1.columns if not column=='type'], F.lit('percent').alias('type'))
df3 = df1.union(df2)
df3.show()
+-------------------+------------------+------------------+-------+
| id2| score| score2| type|
+-------------------+------------------+------------------+-------+
| 1.0| 4.0| 2.0| count|
|0.14285714285714285|0.5714285714285714|0.2857142857142857|percent|
+-------------------+------------------+------------------+-------+