pandas.Series.str.replace

Series.str.replace(self, pat, repl, n=-1, case=None, flags=0, regex=True)[source]

Replace each occurrence of pattern/regex in the Series/Index.

Equivalent to str.replace() or re.sub(), depending on the regex value.

Parameters
patstr or compiled regex

String can be a character sequence or regular expression.

replstr or callable

Replacement string or a callable. The callable is passed the regex match object and must return a replacement string to be used. See re.sub().

nint, default -1 (all)

Number of replacements to make from start.

casebool, default None

Determines if replace is case sensitive:

  • If True, case sensitive (the default if pat is a string)

  • Set to False for case insensitive

  • Cannot be set if pat is a compiled regex.

flagsint, default 0 (no flags)

Regex module flags, e.g. re.IGNORECASE. Cannot be set if pat is a compiled regex.

regexbool, default True

Determines if assumes the passed-in pattern is a regular expression:

  • If True, assumes the passed-in pattern is a regular expression.

  • If False, treats the pattern as a literal string

  • Cannot be set to False if pat is a compiled regex or repl is a callable.

New in version 0.23.0.

Returns
Series or Index of object

A copy of the object with all matching occurrences of pat replaced by repl.

Raises
ValueError

  • if regex is False and repl is a callable or pat is a compiled regex

  • if pat is a compiled regex and case or flags is set

Notes

When pat is a compiled regex, all flags should be included in the compiled regex. Use of case, flags, or regex=False with a compiled regex will raise an error.

Examples

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:

>>> pd.Series(['foo', 'fuz', np.nan]).str.replace('f.', 'ba', regex=True)
0    bao
1    baz
2    NaN
dtype: object

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

>>> pd.Series(['f.o', 'fuz', np.nan]).str.replace('f.', 'ba', regex=False)
0    bao
1    fuz
2    NaN
dtype: object

When repl is a callable, it is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string.

To get the idea:

>>> pd.Series(['foo', 'fuz', np.nan]).str.replace('f', repr)
0    <re.Match object; span=(0, 1), match='f'>oo
1    <re.Match object; span=(0, 1), match='f'>uz
2                                            NaN
dtype: object

Reverse every lowercase alphabetic word:

>>> repl = lambda m: m.group(0)[::-1]
>>> pd.Series(['foo 123', 'bar baz', np.nan]).str.replace(r'[a-z]+', repl)
0    oof 123
1    rab zab
2        NaN
dtype: object

Using regex groups (extract second group and swap case):

>>> pat = r"(?P<one>\w+) (?P<two>\w+) (?P<three>\w+)"
>>> repl = lambda m: m.group('two').swapcase()
>>> pd.Series(['One Two Three', 'Foo Bar Baz']).str.replace(pat, repl)
0    tWO
1    bAR
dtype: object

Using a compiled regex with flags

>>> import re
>>> regex_pat = re.compile(r'FUZ', flags=re.IGNORECASE)
>>> pd.Series(['foo', 'fuz', np.nan]).str.replace(regex_pat, 'bar')
0    foo
1    bar
2    NaN
dtype: object
pandas.Series.str.repeat pandas.Series.str.rfind