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

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

String can be a character sequence or regular expression.

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() .

Number of replacements to make from start.

Determines if replace is case sensitive:

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

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

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

• 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 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, regex=True)
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]
>>> ser = pd.Series(['foo 123', 'bar baz', np.nan])
>>> ser.str.replace(r'[a-z]+', repl, regex=True)
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()
>>> ser = pd.Series(['One Two Three', 'Foo Bar Baz'])
>>> ser.str.replace(pat, repl, regex=True)
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', regex=True)
0    foo
1    bar
2    NaN
dtype: object