cudf.core.column.string.StringMethods.replace#

StringMethods.replace(pat: str | Sequence, repl: str | Sequence, n: int = -1, case=None, flags: int = 0, regex: bool = True) → SeriesOrIndex[source]#

Replace occurrences of pattern/regex in the Series/Index with some other string. Equivalent to str.replace() or re.sub().

Parameters:

patstr or list-like: String(s) to be replaced as a character sequence or regular expression.
replstr or list-like: String(s) to be used as replacement.
nint, default -1 (all): Number of replacements to make from the start.
regexbool, default True: If True, assumes the pattern is a regular expression. If False, treats the pattern as a literal string.

Returns:

Series/Index of str dtype: A copy of the object with all matching occurrences of pat replaced by repl.

Examples

>>> import cudf
>>> s = cudf.Series(['foo', 'fuz', None])
>>> s
0     foo
1     fuz
2    <NA>
dtype: object

When pat is a string and regex is True (the default), the given pat is compiled as a regex. When repl is a string, it replaces matching regex patterns as with re.sub(). NaN value(s) in the Series are left as is:

>>> s.str.replace('f.', 'ba', regex=True)
0     bao
1     baz
2    <NA>
dtype: object

When pat is a string and regex is False, every pat is replaced with repl as with str.replace():

>>> s.str.replace('f.', 'ba', regex=False)
0     foo
1     fuz
2    <NA>
dtype: object

Pandas Compatibility Note

pandas.Series.str.replace()

The parameters case and flags are not yet supported and will raise a NotImplementedError if anything other than the default value is set.