Coalesce columns

Coalesce columns — `coalesceColumns`

Take the first non-null value across several columns into a new column — a fallback chain for consolidating redundant fields.

Use cases

Pick the first available phone number: mobile → home → work.
Merge values from differently-named source systems into one column.
Fall back to a default-bearing column when a primary is missing.

What it does

For each row, the columns are checked left-to-right and the first non-null value is written to the new column. If every column is null for a row, the result is null.

Configuration

Config key	Type	Required	Description
`columns`	string[]	Yes	Columns in priority order (≥ 2)
`new_column`	string	Yes	Name of the result column
`keep_original`	boolean	No	Keep the source columns (default true)

Generated Python code

df_2 = df_1.assign(phone=lambda _d: _d['mobile'].where(pd.notna, _d['home']).where(pd.notna, _d['work']))

Tips & common mistakes

Priority is the column order — put the most-trusted source first.
To concatenate values instead of picking one, use Combine columns.