String transform

String transform — `stringTransform`

Apply a string operation to a column.

Use cases

Normalize casing (lower/upper/title/capitalize) and trim whitespace (strip).
Replace a substring, measure length (len), or zero-pad codes (pad).

What it does

Applies the chosen operation to every value in the target column in place. Chain multiple String transform nodes (one per operation) for multi-step cleaning.

Before

name	email
Ada L	[email protected]
Grace H	[email protected]

2 rows · 2 cols

String transform: lower(email), then strip(name)

After

name	email
Ada L	[email protected]
Grace H	[email protected]

2 rows · 2 cols

Configuration

Config key	Type	Required	Description
`column`	string	Yes	Column to transform
`operation`	string	Yes	`lower`, `upper`, `strip`, `title`, `capitalize`, `len`, `replace`, `pad`
`find`	string	Conditional	Required for `replace`
`replace_with`	string	No	Replacement for `replace` (default empty)
`width`	int	Conditional	Target width, required for `pad`
`fill_char`	string	No	Pad character (default space)
`side`	string	No	`left` (default) or `right` for `pad`

Generated Python code

df_2 = df_1.assign(region=lambda _d: _d['region'].astype('string').str.strip())

Tips & common mistakes

capitalize vs title: capitalize upper-cases only the first character of the whole string; title upper-cases the first letter of every word.
replace needs find; pad needs width — the form blocks saving otherwise.
len produces an integer column (character counts), not text.