pandas.Series.str.split#
- Series.str.split(pat=None, *, n=- 1, expand=False, regex=None)[source]#
Split strings around given separator/delimiter.
Splits the string in the Series/Index from the beginning, at the specified delimiter string.
- Parameters
- patstr or compiled regex, optional
String or regular expression to split on. If not specified, split on whitespace.
- nint, default -1 (all)
Limit number of splits in output.
None
, 0 and -1 will be interpreted as return all splits.- expandbool, default False
Expand the split strings into separate columns.
If
True
, return DataFrame/MultiIndex expanding dimensionality.If
False
, return Series/Index, containing lists of strings.
- regexbool, default None
Determines if the passed-in pattern is a regular expression:
If
True
, assumes the passed-in pattern is a regular expressionIf
False
, treats the pattern as a literal string.If
None
and pat length is 1, treats pat as a literal string.If
None
and pat length is not 1, treats pat as a regular expression.Cannot be set to False if pat is a compiled regex
New in version 1.4.0.
- Returns
- Series, Index, DataFrame or MultiIndex
Type matches caller unless
expand=True
(see Notes).
- Raises
- ValueError
if regex is False and pat is a compiled regex
See also
Series.str.split
Split strings around given separator/delimiter.
Series.str.rsplit
Splits string around given separator/delimiter, starting from the right.
Series.str.join
Join lists contained as elements in the Series/Index with passed delimiter.
str.split
Standard library version for split.
str.rsplit
Standard library version for rsplit.
Notes
The handling of the n keyword depends on the number of found splits:
If found splits > n, make first n splits only
If found splits <= n, make all splits
If for a certain row the number of found splits < n, append None for padding up to n if
expand=True
If using
expand=True
, Series and Index callers return DataFrame and MultiIndex objects, respectively.Use of regex =False with a pat as a compiled regex will raise an error.
Examples
>>> s = pd.Series( ... [ ... "this is a regular sentence", ... "https://docs.python.org/3/tutorial/index.html", ... np.nan ... ] ... ) >>> s 0 this is a regular sentence 1 https://docs.python.org/3/tutorial/index.html 2 NaN dtype: object
In the default setting, the string is split by whitespace.
>>> s.str.split() 0 [this, is, a, regular, sentence] 1 [https://docs.python.org/3/tutorial/index.html] 2 NaN dtype: object
Without the n parameter, the outputs of rsplit and split are identical.
>>> s.str.rsplit() 0 [this, is, a, regular, sentence] 1 [https://docs.python.org/3/tutorial/index.html] 2 NaN dtype: object
The n parameter can be used to limit the number of splits on the delimiter. The outputs of split and rsplit are different.
>>> s.str.split(n=2) 0 [this, is, a regular sentence] 1 [https://docs.python.org/3/tutorial/index.html] 2 NaN dtype: object
>>> s.str.rsplit(n=2) 0 [this is a, regular, sentence] 1 [https://docs.python.org/3/tutorial/index.html] 2 NaN dtype: object
The pat parameter can be used to split by other characters.
>>> s.str.split(pat="/") 0 [this is a regular sentence] 1 [https:, , docs.python.org, 3, tutorial, index... 2 NaN dtype: object
When using
expand=True
, the split elements will expand out into separate columns. If NaN is present, it is propagated throughout the columns during the split.>>> s.str.split(expand=True) 0 1 2 3 4 0 this is a regular sentence 1 https://docs.python.org/3/tutorial/index.html None None None None 2 NaN NaN NaN NaN NaN
For slightly more complex use cases like splitting the html document name from a url, a combination of parameter settings can be used.
>>> s.str.rsplit("/", n=1, expand=True) 0 1 0 this is a regular sentence None 1 https://docs.python.org/3/tutorial index.html 2 NaN NaN
Remember to escape special characters when explicitly using regular expressions.
>>> s = pd.Series(["foo and bar plus baz"]) >>> s.str.split(r"and|plus", expand=True) 0 1 2 0 foo bar baz
Regular expressions can be used to handle urls or file names. When pat is a string and
regex=None
(the default), the given pat is compiled as a regex only iflen(pat) != 1
.>>> s = pd.Series(['foojpgbar.jpg']) >>> s.str.split(r".", expand=True) 0 1 0 foojpgbar jpg
>>> s.str.split(r"\.jpg", expand=True) 0 1 0 foojpgbar
When
regex=True
, pat is interpreted as a regex>>> s.str.split(r"\.jpg", regex=True, expand=True) 0 1 0 foojpgbar
A compiled regex can be passed as pat
>>> import re >>> s.str.split(re.compile(r"\.jpg"), expand=True) 0 1 0 foojpgbar
When
regex=False
, pat is interpreted as the string itself>>> s.str.split(r"\.jpg", regex=False, expand=True) 0 0 foojpgbar.jpg