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Implementation:Eventual Inc Daft DataFrame With Column

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

Overview

Concrete tool for adding or replacing a column in a DataFrame using a computed expression provided by the Daft library.

Description

The with_column method on Daft's DataFrame class adds a new column with the given name and expression to the DataFrame. If a column with the same name already exists, it is replaced. Internally, this is equivalent to calling with_columns({column_name: expr}), which itself performs a SELECT of all existing columns plus the new expression aliased to the given name.

Usage

Use df.with_column() when you need to add a single computed column to an existing DataFrame. For adding multiple columns at once, consider df.with_columns() instead.

Code Reference

Source Location

  • Repository: Daft
  • File: daft/dataframe/dataframe.py
  • Lines: L2408-2441

Signature

def with_column(self, column_name: str, expr: Expression) -> DataFrame

Import

import daft

# Method on DataFrame - no separate import needed
df.with_column("new_col", daft.col("x") + 1)

I/O Contract

Inputs

Name Type Required Description
column_name str Yes Name of the new column (or existing column to replace)
expr Expression Yes Expression to compute the column values

Outputs

Name Type Description
return DataFrame A new DataFrame with all existing columns plus the new (or replaced) column

Usage Examples

Basic Usage

import daft

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

# Add a computed column
new_df = df.with_column("x+1", df["x"] + 1)
new_df.show()
# Output:
# x: [1, 2, 3]
# x+1: [2, 3, 4]

Replace Existing Column

import daft

df = daft.from_pydict({"x": [1, 2, 3], "y": [10, 20, 30]})

# Replace column "y" with a new expression
new_df = df.with_column("y", df["y"] * 2)
new_df.show()
# Output:
# x: [1, 2, 3]
# y: [20, 40, 60]

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