pandas.Series.str.replace

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

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

Parameters:

pat : string or compiled regex String can be a character sequence or regular expression. New in version 0.20.0: pat also accepts a compiled regex. repl : string 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(). New in version 0.20.0: repl also accepts a callable. n : int, default -1 (all) Number of replacements to make from start case : boolean, default None 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 flags : int, default 0 (no flags) re module flags, e.g. re.IGNORECASE Cannot be set if pat is a compiled regex

Returns:

replaced : Series/Index of objects

Notes

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

Examples

When repl is a string, every pat is replaced as with str.replace(). NaN value(s) in the Series are left as is.

>>> pd.Series(['foo', 'fuz', np.nan]).str.replace('f', 'b')
0    boo
1    buz
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    <_sre.SRE_Match object; span=(0, 1), match='f'>oo
1    <_sre.SRE_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

>>> 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