# sdf_separate_column

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##### Separate a Vector Column into Scalar Columns

Given a vector column in a Spark DataFrame, split that into n separate columns, each column made up of the different elements in the column column.

##### Usage
sdf_separate_column(x, column, into = NULL)
##### Arguments
x

A spark_connection, ml_pipeline, or a tbl_spark.

column

The name of a (vector-typed) column.

into

A specification of the columns that should be generated from column. This can either be a vector of column names, or an R list mapping column names to the (1-based) index at which a particular vector element should be extracted.

##### Aliases
• sdf_separate_column
This is generally used in combination with ft_regex_tokenizer, to split a column containing comma separated values (or other patterns) into multipl columns.  mydf %>% ft_regex_tokenizer(input.col="mycolumn", output.col="mycolumnSplit", pattern=";") %>% sdf_separate_column("mycolumnSplit", into=c("column1", "column2")