You could create a new column based on the expression: IF (condition1, value1, old_column_value)
On Mon, Nov 23, 2015 at 11:57 AM, Vishnu Viswanath <vishnu.viswanat...@gmail.com> wrote: > Thanks for the reply Davies > > I think replace, replaces a value with another value. But what I want to do > is fill in the null value of a column.( I don't have a to_replace here ) > > Regards, > Vishnu > > On Mon, Nov 23, 2015 at 1:37 PM, Davies Liu <dav...@databricks.com> wrote: >> >> DataFrame.replace(to_replace, value, subset=None) >> >> >> http://spark.apache.org/docs/latest/api/python/pyspark.sql.html#pyspark.sql.DataFrame.replace >> >> On Mon, Nov 23, 2015 at 11:05 AM, Vishnu Viswanath >> <vishnu.viswanat...@gmail.com> wrote: >> > Hi >> > >> > Can someone tell me if there is a way I can use the fill method in >> > DataFrameNaFunctions based on some condition. >> > >> > e.g., df.na.fill("value1","column1","condition1") >> > df.na.fill("value2","column1","condition2") >> > >> > i want to fill nulls in column1 with values - either value 1 or value 2, >> > based on some condition. >> > >> > Thanks, > > > > > -- > Thanks and Regards, > Vishnu Viswanath > +1 309 550 2311 > www.vishnuviswanath.com --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
