我有一个与此相似的数据框:
values = [
("2019-10-01", "004", 1.0),
("2019-10-02", "005", None),
("2019-10-03", "004", 2.0),
("2019-10-04", "004", 1.0),
("2019-10-05", "006", None)
]
df = spark.createDataFrame(values, ['time', 'mode', 'value'])
我想用上一个非空值填充最后一栏中的“无”。
("2019-10-01", "004", 1.0),
("2019-10-02", "005", 1.0),
("2019-10-03", "004", 2.0),
("2019-10-04", "004", 1.0),
("2019-10-05", "006", 1.0)
我尝试过:
import pyspark.sql.functions as f
from pyspark.sql.window import Window
df_2 = df.withColumn("value2", f.last('value', ignorenulls=True).over(Window.orderBy('time').rowsBetween(Window.unboundedPreceding, 0)))
这不起作用,因为新列中仍然有空值。 如何向前填充最后一列?
答案 0 :(得分:0)
您的窗口操作只有一个小错误,请尝试以下操作:
from pyspark.sql import functions as f, Window
window_last = Window.orderBy("time")
df_2 = df.withColumn("value2", f.last("value", ignorenulls=True).over(window_last))
结果:
+----------+----+-----+------+
| time|mode|value|value2|
+----------+----+-----+------+
|2019-10-01| 004| 1.0| 1.0|
|2019-10-02| 005| null| 1.0|
|2019-10-03| 004| 2.0| 2.0|
|2019-10-04| 004| 1.0| 1.0|
|2019-10-05| 006| null| 1.0|
+----------+----+-----+------+