concat

Returns a DataFrame with the union of rows from several given DataFrames.

concat is available for:

DataFrame:

df.concat(df1, df2)

DataColumn:

val a by columnOf(1, 2)
val b by columnOf(3, 4)
a.concat(b)

Iterable<DataFrame>:

listOf(df1, df2).concat()

Iterable<DataRow>:

val rows = listOf(df[2], df[4], df[5])
rows.concat()

Iterable<DataColumn>:

val a by columnOf(1, 2)
val b by columnOf(3, 4)
listOf(a, b).concat()

groupBy:

df.groupBy { name }.concat()

FrameColumn:

val x = dataFrameOf("a", "b")(
    1, 2,
    3, 4
)
val y = dataFrameOf("b", "c")(
    5, 6,
    7, 8
)
val frameColumn by columnOf(x, y)
frameColumn.concat()

If you want to take the union of columns (not rows) from several DataFrames, see add.

Schema unification

If input DataFrames have different schemas, every column in the resulting DataFrames will get the lowest common type of the original columns with the same name.

For example, if one DataFrame has a column A: Int and another DataFrame has a column A: Double, the resulting DataFrame will have a column A: Number.

Missing columns in dataframes will be filled with null.

Last modified: 29 March 2024