[英]Is it possible to groupBy a Spark's dataframe when not all values are present in column?
[英]Removing alphabets from alphanumeric values present in column of dataframe of spark
dataframe兩列的樣子。
SKU | COMPSKU
PT25M | PT10M
PT3H | PT20M
TH | QR12
S18M | JH
火花與 scala
我怎樣才能刪除所有字母並且只保留數字..
預期 output:
25|10
3|20
0|12
18|0
你也可以這樣做。
df.withColumn(
"SKU",
when(regexp_replace(col("SKU"),"[a-zA-Z]","")==="",0
).otherwise(regexp_replace(col("SKU"),"[a-zA-Z]",""))
).withColumn(
"COMPSKU",
when(regexp_replace(col("COMPSKU"),"[a-zA-Z]","")==="", 0
).otherwise(regexp_replace(col("COMPSKU"),"[a-zA-Z]",""))
).show()
/*
+-----+-------+
| SKU|COMPSKU|
+-----+-------+
| 25 | 10 |
| 3 | 20 |
| 0 | 12 |
| 18 | 0 |
+-----+-------+
*/
嘗試使用regexp_replace
function 然后使用 case when otherwise stateme
用 0 替換空值。
Example:
df.show()
/*
+-----+-------+
| SKU|COMPSKU|
+-----+-------+
|PT25M| PT10M|
| PT3H| PT20M|
| TH| QR12|
| S18M| JH|
+-----+-------+
*/
df.withColumn("SKU",regexp_replace(col("SKU"),"[a-zA-Z]","")).
withColumn("COMPSKU",regexp_replace(col("COMPSKU"),"[a-zA-Z]","")).
withColumn("SKU",when(length(trim(col("SKU")))===0,lit(0)).otherwise(col("SKU"))).
withColumn("COMPSKU",when(length(trim(col("COMPSKU")))===0,lit(0)).otherwise(col("COMPSKU"))).
show()
/*
+---+-------+
|SKU|COMPSKU|
+---+-------+
| 25| 10|
| 3| 20|
| 0| 12|
| 18| 0|
+---+-------+
*/
聲明:本站的技術帖子網頁,遵循CC BY-SA 4.0協議,如果您需要轉載,請注明本站網址或者原文地址。任何問題請咨詢:yoyou2525@163.com.