pandas.Series.str.replace#

Series.str.replace(pat, repl=None, n=-1, case=None, flags=0, regex=False)[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, compiled regex, or a dict

String can be a character sequence or regular expression. Dictionary contains <key : value> pairs of strings to be replaced along with the updated value.

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. Must have a value of None if pat is a dict 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 False

Determines if 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.

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
if pat is a dictionary and repl is not None.

See also

Series.str.replace: Method to replace occurrences of a substring with another substring.
Series.str.extract: Extract substrings using a regular expression.
Series.str.findall: Find all occurrences of a pattern or regex in each string.
Series.str.split: Split each string by a specified delimiter or pattern.

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 dictionary, every key in pat is replaced with its corresponding value:

>>> pd.Series(["A", "B", np.nan]).str.replace(pat={"A": "a", "B": "b"})
0    a
1    b
2    NaN
dtype: object

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

pandas.Series.str.replace#

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