duplicateRows

Returns a DataFrame where every row is repeated n times.

The copies of a row come right after it, so the order of the rows stays the same: with n = 2, rows A, B become A, A, B, B. Values in column groups and frame columns are repeated together with their rows. The column names and types stay the same.

Don't confuse this with distinct, which removes repeated rows.

For more information: See duplicateRows on the documentation website.

See also:

• duplicateRows(n) { filter: RowFilter<T> } — repeats only the rows that match a condition.

• duplicate — puts copies of the whole DataFrame into a FrameColumn.

• duplicate — makes a DataFrame out of copies of a single DataRow.

Example

In the example, df has the columns name and age and three rows: Alice, 15, Bob, 20 and Charlie, 30.

// Alice, Alice, Alice, Bob, Bob, Bob, Charlie, Charlie, Charlie
df.duplicateRows(3)

Parameters

Throws

Returns a DataFrame where each row that matches the filter is repeated n times.

Rows that do not match the filter appear once, as before. The copies of a row come right after it, so the order of the rows stays the same. Values in column groups and frame columns are repeated together with their rows. The column names and types stay the same.

The filter is a RowFilter — a lambda that receives each DataRow as both this and it and returns true for the rows to repeat.

It allows you to define conditions using the row's values directly, including through extension properties for convenient and type-safe access.

For more information: See duplicateRows on the documentation website. See RowFilter on the documentation website.

See also:

• duplicateRows(n: Int) — repeats every row.

• filter — keeps only the rows that match a condition.

Example

In the example, df has the columns name and age and three rows: Alice, 15, Bob, 20 and Charlie, 30.

// Alice, Bob, Bob, Bob, Charlie, Charlie, Charlie
df.duplicateRows(3) { age > 18 }

Parameters

Throws