I figured it out.
Here is how it's done:
from pyspark.sql.functions import udf
replaceFunction = udf(lambda columnValue : columnValue.replace("\n", "
").replace('\r', " "))
df.withColumn('strReplaced', replaceFunction(df["str"]))
On 10 February 2016 at 13:04, wrote:
> Hi Viktor,
>
> Try to cr
Hi Viktor,
Try to create a UDF. It's quite simple!
Ardo.
> On 10 Feb 2016, at 10:34, Viktor ARDELEAN wrote:
>
> Hello,
>
> I want to add a new String column to the dataframe based on an existing
> column values:
>
> from pyspark.sql.functions import lit
> df.withColumn('strReplaced', lit(d
Hello,
I want to add a new String column to the dataframe based on an existing
column values:
from pyspark.sql.functions import lit
df.withColumn('strReplaced', lit(df.str.replace("a", "b").replace("c", "d")))
So basically I want to add a new column named "strReplaced", that is
the same as the