Implementation:Eventual Inc Daft DataFrame Explode

Knowledge Sources	Daft Daft Docs
Domains	Data_Engineering, Data_Transformation
Last Updated	2026-02-08 00:00 GMT

Overview

Concrete tool for expanding list-type columns into individual rows provided by the Daft library.

Description

The explode method on Daft's DataFrame class takes one or more list-typed columns and produces one row per list element, duplicating all other columns. When multiple columns are exploded simultaneously, each row must contain lists of equal length. Null values and empty lists produce a single row with a Null value. An optional index_column parameter adds a column tracking the position of each element within its original list.

Usage

Use df.explode() when you need to flatten list columns into individual rows. This is a method on DataFrame instances and requires no additional imports beyond Daft itself.

Code Reference

Source Location

• Repository: Daft
• File: daft/dataframe/dataframe.py
• Lines: L3106-3225

Signature

def explode(self, *columns: ColumnInputType, index_column: ColumnInputType | None = None) -> DataFrame

Import

import daft

# Method on DataFrame - no separate import needed
df.explode("list_col")

I/O Contract

Inputs

Name	Type	Required	Description
*columns	ColumnInputType	Yes	One or more list-typed columns to explode
index_column	ColumnInputType or None	No	Optional name for an index column that tracks the position of each element within its original list

Outputs

Name	Type	Description
return	DataFrame	A new DataFrame with list columns exploded into individual rows, with all other columns duplicated

Usage Examples

Basic Usage

import daft

df = daft.from_pydict({
    "x": [[1], [2, 3]],
    "y": [["a"], ["b", "c"]],
})

# Explode multiple list columns simultaneously
result = df.explode(df["x"], df["y"])
result.collect()
# Output:
# x: [1, 2, 3]
# y: ["a", "b", "c"]

With Index Column

import daft

df = daft.from_pydict({"a": [[1, 2], [3, 4, 3]]})

# Track element positions with index_column
result = df.explode("a", index_column="idx")
result.collect()
# Output:
# a: [1, 2, 3, 4, 3]
# idx: [0, 1, 0, 1, 2]

Related Pages

Implements Principle

• Principle:Eventual_Inc_Daft_List_Explosion

Requires Environment

• Environment:Eventual_Inc_Daft_Python_PyArrow_Core