Class StringMethods (1.16.0)

StringMethods(
    data=None,
    index: vendored_pandas_typing.Axes | None = None,
    dtype: typing.Optional[
        bigframes.dtypes.DtypeString | bigframes.dtypes.Dtype
    ] = None,
    name: str | None = None,
    copy: typing.Optional[bool] = None,
    *,
    session: typing.Optional[bigframes.session.Session] = None
)

Vectorized string functions for Series and Index.

NAs stay NA unless handled otherwise by a particular method. Patterned after Python's string methods, with some inspiration from R's stringr package.

Methods

capitalize

capitalize() -> bigframes.series.Series

Convert strings in the Series/Index to be capitalized.

Equivalent to str.capitalize.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['lower',
...                 'CAPITALS',
...                 'this is a sentence',
...                 'SwApCaSe'])
>>> s.str.capitalize()
0                 Lower
1              Capitals
2    This is a sentence
3              Swapcase
dtype: string

Returns
Type	Description
`bigframes.series.Series`	Series with captitalized strings.

cat

cat(
    others: typing.Union[str, bigframes.series.Series],
    *,
    join: typing.Literal["outer", "left"] = "left"
) -> bigframes.series.Series

Concatenate strings in the Series/Index with given separator.

If others is specified, this function concatenates the Series/Index and elements of others element-wise.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

You can concatenate each string in a Series to another string.

>>> s = bpd.Series(['Jane', 'John'])
>>> s.str.cat(" Doe")
0    Jane Doe
1    John Doe
dtype: string

You can concatenate another Series. By default left join is performed to align the corresponding elements.

>>> s.str.cat(bpd.Series([" Doe", " Foe", " Roe"]))
0    Jane Doe
1    John Foe
dtype: string

>>> s.str.cat(bpd.Series([" Doe", " Foe", " Roe"], index=[2, 0, 1]))
0    Jane Foe
1    John Roe
dtype: string

You can enforce an outer join.

>>> s.str.cat(bpd.Series([" Doe", " Foe", " Roe"]), join="outer")
0    Jane Doe
1    John Foe
2        <NA>
dtype: string

Parameters
Name	Description
`others`	`str or Series` A string or a Series of strings.
`join`	`{'left', 'outer'}, default 'left'` Determines the join-style between the calling Series and any Series in `others` (objects without an index need to match the length of the calling Series). To disable alignment, use `.values` on any Series/Index/DataFrame in `others`.

Returns
Type	Description
`bigframes.series.Series`	Series with concatenated strings.

center

center(width: int, fillchar: str = " ") -> bigframes.series.Series

Pad left and right side of strings in the Series/Index.

Equivalent to str.center.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> ser = bpd.Series(['dog', 'bird', 'mouse'])
>>> ser.str.center(8, fillchar='.')
0    ..dog...
1    ..bird..
2    .mouse..
dtype: string

Parameters
Name	Description
`width`	`int` Minimum width of resulting string; additional characters will be filled with character defined in `fillchar`.
`fillchar`	`str, default ' '` Additional character for filling, default is whitespace.

Returns
Type	Description
`bigframes.series.Series`	Returns Series or Index with minimum number of char in object.

contains

contains(
    pat, case: bool = True, flags: int = 0, *, regex: bool = True
) -> bigframes.series.Series

Test if pattern or regex is contained within a string of a Series or Index.

Return boolean Series or Index based on whether a given pattern or regex is contained within a string of a Series or Index.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

Returning a Series of booleans using only a literal pattern.

>>> s1 = bpd.Series(['Mouse', 'dog', 'house and parrot', '23', None])
>>> s1.str.contains('og')
0    False
1     True
2    False
3    False
4     <NA>
dtype: boolean

Specifying case sensitivity using case.

>>> s1.str.contains('oG', case=True)
0    False
1    False
2    False
3    False
4     <NA>
dtype: boolean

Returning 'house' or 'dog' when either expression occurs in a string.

>>> s1.str.contains('house|dog', regex=True)
0    False
1     True
2     True
3    False
4     <NA>
dtype: boolean

Ignoring case sensitivity using flags with regex.

>>> import re
>>> s1.str.contains('PARROT', flags=re.IGNORECASE, regex=True)
0    False
1    False
2     True
3    False
4     <NA>
dtype: boolean

Returning any digit using regular expression.

>>> s1.str.contains('\d', regex=True)
0    False
1    False
2    False
3     True
4     <NA>
dtype: boolean

Ensure pat is a not a literal pattern when regex is set to True. Note in the following example one might expect only s2[1] and s2[3] to return True. However, '.0' as a regex matches any character followed by a 0.

>>> s2 = bpd.Series(['40', '40.0', '41', '41.0', '35'])
>>> s2.str.contains('.0', regex=True)
0     True
1     True
2    False
3     True
4    False
dtype: boolean

Parameters
Name	Description
`pat`	`str, re.Pattern` Character sequence or regular expression.
`case`	`bool, default True` If True, case sensitive.
`flags`	`int, default 0` Flags to pass through to the re module, e.g. re.IGNORECASE.
`regex`	`bool, default True` If True, assumes the pat is a regular expression. If False, treats the pat as a literal string.

Returns
Type	Description
`bigframes.series.Series`	A Series or Index of boolean values indicating whether the given pattern is contained within the string of each element of the Series or Index.

endswith

endswith(pat: typing.Union[str, tuple[str, ...]]) -> bigframes.series.Series

Test if the end of each string element matches a pattern.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['bat', 'bear', 'caT', bpd.NA])
>>> s
0     bat
1    bear
2     caT
3    <NA>
dtype: string

>>> s.str.endswith('t')
0     True
1    False
2    False
3     <NA>
dtype: boolean

>>> s.str.endswith(('t', 'T'))
0     True
1    False
2     True
3     <NA>
dtype: boolean

Parameter
Name	Description
`pat`	`str, tuple[str, ...]` Character sequence or tuple of strings. Regular expressions are not accepted.

Returns
Type	Description
`bigframes.series.Series`	A Series of booleans indicating whether the given pattern matches the end of each string element.

extract

extract(pat: str, flags: int = 0) -> bigframes.dataframe.DataFrame

Extract capture groups in the regex pat as columns in a DataFrame.

For each subject string in the Series, extract groups from the first match of regular expression pat.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

A pattern with two groups will return a DataFrame with two columns. Non-matches will be NaN.

>>> s = bpd.Series(['a1', 'b2', 'c3'])
>>> s.str.extract(r'([ab])(\d)')
      0     1
0     a     1
1     b     2
2  <NA>  <NA>
<BLANKLINE>
[3 rows x 2 columns]

Named groups will become column names in the result.

>>> s.str.extract(r'(?P<letter>[ab])(?P<digit>\d)')
  letter digit
0      a     1
1      b     2
2   <NA>  <NA>
<BLANKLINE>
[3 rows x 2 columns]

A pattern with one group will return a DataFrame with one column.

>>> s.str.extract(r'[ab](\d)')
      0
0     1
1     2
2  <NA>
<BLANKLINE>
[3 rows x 1 columns]

Parameters
Name	Description
`pat`	`str` Regular expression pattern with capturing groups.
`flags`	`int, default 0 (no flags)` Flags from the `re` module, e.g. `re.IGNORECASE`, that modify regular expression matching for things like case, spaces, etc. For more details, see `re`.

Returns
Type	Description
`bigframes.dataframe.DataFrame`	A DataFrame with one row for each subject string, and one column for each group. Any capture group names in regular expression pat will be used for column names; otherwise capture group numbers will be used.

find

find(
    sub: str, start: typing.Optional[int] = None, end: typing.Optional[int] = None
) -> bigframes.series.Series

Return lowest indexes in each strings in the Series/Index.

Each of returned indexes corresponds to the position where the substring is fully contained between [start:end]. Return -1 on failure. Equivalent to standard str.find.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> ser = bpd.Series(["cow_", "duck_", "do_ve"])
>>> ser.str.find("_")
0    3
1    4
2    2
dtype: Int64

Parameters
Name	Description
`sub`	`str` Substring being searched.
`start`	`int, default 0` Left edge index.
`end`	`int, default None` Right edge index.

Returns
Type	Description
`bigframes.series.Series`	Series with lowest indexes in each strings.

fullmatch

fullmatch(pat, case=True, flags=0) -> bigframes.series.Series

Determine if each string entirely matches a regular expression.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> ser = bpd.Series(["cat", "duck", "dove"])
>>> ser.str.fullmatch(r'd.+')
0    False
1     True
2     True
dtype: boolean

Parameters
Name	Description
`pat`	`str` Character sequence or regular expression.
`case`	`bool` If True, case sensitive.
`flags`	`int, default 0` Regex module flags, e.g. re.IGNORECASE.

Returns
Type	Description
`bigframes.series.Series`	Series of boolean values

get

get(i: int) -> bigframes.series.Series

Extract element from each component at specified position or with specified key.

Extract element from lists, tuples, dict, or strings in each element in the Series/Index.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(["apple", "banana", "fig"])
>>> s.str.get(3)
0       l
1       a
2    <NA>
dtype: string

Parameter
Name	Description
`i`	`int` Position or key of element to extract.

Returns
Type	Description
`bigframes.series.Series`	Series

isalnum

isalnum() -> bigframes.series.Series

Check whether all characters in each string are alphanumeric.

This is equivalent to running the Python string method str.isalnum for each element of the Series/Index. If a string has zero characters, False is returned for that check.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s1 = bpd.Series(['one', 'one1', '1', ''])
>>> s1.str.isalnum()
0     True
1     True
2     True
3    False
dtype: boolean

Note that checks against characters mixed with any additional punctuation or whitespace will evaluate to false for an alphanumeric check.

>>> s2 = bpd.Series(['A B', '1.5', '3,000'])
>>> s2.str.isalnum()
0    False
1    False
2    False
dtype: boolean

Returns
Type	Description
`bigframes.series.Series`	Series or Index of boolean values with the same length as the original Series/Index.

isalpha

isalpha() -> bigframes.series.Series

Check whether all characters in each string are alphabetic.

This is equivalent to running the Python string method str.isalpha for each element of the Series/Index. If a string has zero characters, False is returned for that check.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s1 = bpd.Series(['one', 'one1', '1', ''])
>>> s1.str.isalpha()
0     True
1    False
2    False
3    False
dtype: boolean

Returns
Type	Description
`bigframes.series.Series`	Series with the same length as the originalSeries/Index.

isdecimal

isdecimal() -> bigframes.series.Series

Check whether all characters in each string are decimal.

This is equivalent to running the Python string method str.isdecimal for each element of the Series/Index. If a string has zero characters, False is returned for that check.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

The isdecimal method checks for characters used to form numbers in base 10.

>>> s = bpd.Series(['23', '³', '⅕', ''])
>>> s.str.isdecimal()
0     True
1    False
2    False
3    False
dtype: boolean

Returns
Type	Description
`bigframes.series.Series`	Series or Index of boolean values with the same length as the original Series/Index.

isdigit

isdigit() -> bigframes.series.Series

Check whether all characters in each string are digits.

This is equivalent to running the Python string method str.isdigit for each element of the Series/Index. If a string has zero characters, False is returned for that check.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['23', '1a', '1/5', ''])
>>> s.str.isdigit()
0     True
1    False
2    False
3    False
dtype: boolean

Returns
Type	Description
`bigframes.series.Series`	Series with the same length as the originalSeries/Index.

islower

islower() -> bigframes.series.Series

Check whether all characters in each string are lowercase.

This is equivalent to running the Python string method str.islower for each element of the Series/Index. If a string has zero characters, False is returned for that check.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['leopard', 'Golden Eagle', 'SNAKE', ''])
>>> s.str.islower()
0     True
1    False
2    False
3    False
dtype: boolean

Returns
Type	Description
`bigframes.series.Series`	Series or Index of boolean values with the same length as the original Series/Index.

isnumeric

isnumeric() -> bigframes.series.Series

Check whether all characters in each string are numeric.

This is equivalent to running the Python string method str.isnumeric for each element of the Series/Index. If a string has zero characters, False is returned for that check.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s1 = bpd.Series(['one', 'one1', '1', ''])
>>> s1.str.isnumeric()
0    False
1    False
2     True
3    False
dtype: boolean

Returns
Type	Description
`bigframes.series.Series`	Series or Index of boolean values with the same length as the original Series/Index.

isspace

isspace() -> bigframes.series.Series

Check whether all characters in each string are whitespace.

This is equivalent to running the Python string method str.isspace for each element of the Series/Index. If a string has zero characters, False is returned for that check.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series([' ', '\t\r\n ', ''])
>>> s.str.isspace()
0     True
1     True
2    False
dtype: boolean

Returns
Type	Description
`bigframes.series.Series`	Series or Index of boolean values with the same length as the original Series/Index.

isupper

isupper() -> bigframes.series.Series

Check whether all characters in each string are uppercase.

This is equivalent to running the Python string method str.isupper for each element of the Series/Index. If a string has zero characters, False is returned for that check.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['leopard', 'Golden Eagle', 'SNAKE', ''])
>>> s.str.isupper()
0    False
1    False
2     True
3    False
dtype: boolean

Returns
Type	Description
`bigframes.series.Series`	Series or Index of boolean values with the same length as the original Series/Index.

len

len() -> bigframes.series.Series

Compute the length of each element in the Series/Index.

The element may be a sequence (such as a string, tuple or list) or a collection (such as a dictionary).

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

Returns the length (number of characters) in a string.

>>> s = bpd.Series(['dog', '', bpd.NA])
>>> s.str.len()
0       3
1       0
2    <NA>
dtype: Int64

Returns
Type	Description
`bigframes.series.Series`	A Series or Index of integer values indicating the length of each element in the Series or Index.

ljust

ljust(width, fillchar=" ") -> bigframes.series.Series

Pad right side of strings in the Series/Index up to width.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> ser = bpd.Series(['dog', 'bird', 'mouse'])
>>> ser.str.ljust(8, fillchar='.')
0    dog.....
1    bird....
2    mouse...
dtype: string

Parameters
Name	Description
`width`	`int` Minimum width of resulting string; additional characters will be filled with character defined in `fillchar`.
`fillchar`	`str, default ' '` Additional character for filling, default is whitespace.

Returns
Type	Description
`bigframes.series.Series`	Returns Series or Index with minimum number of char in object.

lower

lower() -> bigframes.series.Series

Convert strings in the Series/Index to lowercase.

Equivalent to str.lower.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['lower',
...                 'CAPITALS',
...                 'this is a sentence',
...                 'SwApCaSe'])
>>> s.str.lower()
0                 lower
1              capitals
2    this is a sentence
3              swapcase
dtype: string

Returns
Type	Description
`bigframes.series.Series`	Series with lowercase.

lstrip

lstrip() -> bigframes.series.Series

Remove leading characters.

Strip whitespaces (including newlines) or a set of specified characters from each string in the Series/Index from left side. Replaces any non-strings in Series with NaNs. Equivalent to str.lstrip.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['Ant', '  Bee ', '\tCat\n', bpd.NA])
>>> s
0       Ant
1      Bee
2       Cat
<BLANKLINE>
3      <NA>
dtype: string

>>> s.str.lstrip()
0     Ant
1    Bee
2    Cat
<BLANKLINE>
3    <NA>
dtype: string

Returns
Type	Description
`bigframes.series.Series`	Series without leading characters.

match

match(pat, case=True, flags=0) -> bigframes.series.Series

Determine if each string starts with a match of a regular expression.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> ser = bpd.Series(["horse", "eagle", "donkey"])
>>> ser.str.match("e")
0   False
1   True
2   False
dtype: boolean

Parameters
Name	Description
`pat`	`str` Character sequence or regular expression.
`case`	`bool` If True, case sensitive.
`flags`	`int, default 0` Regex module flags, e.g. re.IGNORECASE.

Returns
Type	Description
`bigframes.series.Series`	Series of boolean values

pad

pad(width, side="left", fillchar=" ") -> bigframes.series.Series

Pad strings in the Series/Index up to width.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(["caribou", "tiger"])
>>> s
0    caribou
1      tiger
dtype: string

>>> s.str.pad(width=10)
0       caribou
1         tiger
dtype: string

>>> s.str.pad(width=10, side='right', fillchar='-')
0    caribou---
1    tiger-----
dtype: string

>>> s.str.pad(width=10, side='both', fillchar='-')
0    -caribou--
1    --tiger---
dtype: string

Parameters
Name	Description
`width`	`int` Minimum width of resulting string; additional characters will be filled with character defined in `fillchar`.
`side`	`{'left', 'right', 'both'}, default 'left'` Side from which to fill resulting string.
`fillchar`	`str, default ' '` Additional character for filling, default is whitespace.

Returns
Type	Description
`bigframes.series.Series`	Returns Series or Index with minimum number of char in object.

repeat

repeat(repeats: int) -> bigframes.series.Series

Duplicate each string in the Series or Index.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['a', 'b', 'c'])
>>> s
0    a
1    b
2    c
dtype: string

>>> s.str.repeat(repeats=2)
0    aa
1    bb
2    cc
dtype: string

Returns
Type	Description
`bigframes.series.Series`	Series or Index of repeated string objects specified by input parameter repeats.

replace

replace(
    pat: typing.Union[str, re.Pattern],
    repl: str,
    *,
    case: typing.Optional[bool] = None,
    flags: int = 0,
    regex: bool = False
) -> bigframes.series.Series

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

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

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

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:

>>> s = bpd.Series(['foo', 'fuz', bpd.NA])
>>> s.str.replace('f.', 'ba', regex=True)
0     bao
1     baz
2    <NA>
dtype: string

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

>>> s = bpd.Series(['f.o', 'fuz', bpd.NA])
>>> s.str.replace('f.', 'ba', regex=False)
0     bao
1     fuz
2    <NA>
dtype: string

Parameters
Name	Description
`pat`	`str, re.Pattern` String can be a character sequence or regular expression.
`repl`	`str` Replacement string.
`case`	`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.
`flags`	`int, default 0` Regex module flags, e.g. re.IGNORECASE. Cannot be set if `pat` is a compiled regex.

Returns
Type	Description
`bigframes.series.Series`	A copy of the object with all matching occurrences of `pat` replaced by `repl`.

reverse

reverse() -> bigframes.series.Series

Reverse strings in the Series.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(["apple", "banana", "", bpd.NA])
>>> s.str.reverse()
0     elppa
1    ananab
2
3      <NA>
dtype: string

Returns
Type	Description
`bigframes.series.Series`	A Series of booleans indicating whether the given pattern matches the start of each string element.

rjust

rjust(width, fillchar=" ") -> bigframes.series.Series

Pad left side of strings in the Series/Index up to width.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> ser = bpd.Series(['dog', 'bird', 'mouse'])
>>> ser.str.rjust(8, fillchar='.')
0    .....dog
1    ....bird
2    ...mouse
dtype: string

Parameters
Name	Description
`width`	`int` Minimum width of resulting string; additional characters will be filled with character defined in `fillchar`.
`fillchar`	`str, default ' '` Additional character for filling, default is whitespace.

Returns
Type	Description
`bigframes.series.Series`	Returns Series or Index with minimum number of char in object.

rstrip

rstrip() -> bigframes.series.Series

Remove trailing characters.

Strip whitespaces (including newlines) or a set of specified characters from each string in the Series/Index from right side. Replaces any non-strings in Series with NaNs. Equivalent to str.rstrip.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['Ant', '  Bee ', '\tCat\n', bpd.NA])
>>> s
0       Ant
1      Bee
2       Cat
<BLANKLINE>
3      <NA>
dtype: string

>>> s.str.rstrip()
0      Ant
1      Bee
2       Cat
3     <NA>
dtype: string

Returns
Type	Description
`bigframes.series.Series`	Series without trailing characters.

slice

slice(
    start: typing.Optional[int] = None, stop: typing.Optional[int] = None
) -> bigframes.series.Series

Slice substrings from each element in the Series or Index.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(["koala", "dog", "chameleon"])
>>> s
0        koala
1          dog
2    chameleon
dtype: string

>>> s.str.slice(start=1)
0        oala
1          og
2    hameleon
dtype: string

>>> s.str.slice(stop=2)
0    ko
1    do
2    ch
dtype: string

>>> s.str.slice(start=2, stop=5)
0    ala
1      g
2    ame
dtype: string

Parameters
Name	Description
`start`	`int, optional` Start position for slice operation.
`stop`	`int, optional` Stop position for slice operation.
`step`	`int, optional` Step size for slice operation.

split

split(
    pat: str = " ", regex: typing.Optional[bool] = None
) -> bigframes.series.Series

Split strings around given separator/delimiter.

Examples:

>>> import bigframes.pandas as bpd
>>> import numpy as np
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(
...     [
...         "a regular sentence",
...         "https://docs.python.org/index.html",
...         np.nan
...     ]
... )
>>> s.str.split()
0                ['a' 'regular' 'sentence']
1    ['https://docs.python.org/index.html']
2                                        []
dtype: list<item: string>[pyarrow]

The pat parameter can be used to split by other characters.

>>> s.str.split("//", regex=False)
0                     ['a regular sentence']
1    ['https:' 'docs.python.org/index.html']
2                                         []
dtype: list<item: string>[pyarrow]

Parameters
Name	Description
`pat`	`str, default " "` String to split on. If not specified, split on whitespace.
`regex`	`bool, default None` Determines if the passed-in pattern is a regular expression. Regular expressions aren't currently supported. Please set `regex=False` when `pat` length is not 1.

Returns
Type	Description
`bigframes.series.Series`	Type matches caller.

startswith

startswith(pat: typing.Union[str, tuple[str, ...]]) -> bigframes.series.Series

Test if the start of each string element matches a pattern.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['bat', 'Bear', 'caT', bpd.NA])
>>> s
0     bat
1    Bear
2     caT
3    <NA>
dtype: string

>>> s.str.startswith('b')
0     True
1    False
2    False
3     <NA>
dtype: boolean

>>> s.str.startswith(('b', 'B'))
0     True
1     True
2    False
3     <NA>
dtype: boolean

Parameter
Name	Description
`pat`	`str, tuple[str, ...]` Character sequence or tuple of strings. Regular expressions are not accepted.

Returns
Type	Description
`bigframes.series.Series`	A Series of booleans indicating whether the given pattern matches the start of each string element.

strip

strip() -> bigframes.series.Series

Remove leading and trailing characters.

Strip whitespaces (including newlines) or a set of specified characters from each string in the Series/Index from left and right sides. Replaces any non-strings in Series with NaNs. Equivalent to str.strip.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['Ant', '  Bee ', '\tCat\n', bpd.NA])
>>> s
0       Ant
1      Bee
2       Cat
<BLANKLINE>
3      <NA>
dtype: string

>>> s.str.strip()
0     Ant
1     Bee
2     Cat
3    <NA>
dtype: string

Returns
Type	Description
`bigframes.series.Series`	Series or Index without leading and trailing characters.

upper

upper() -> bigframes.series.Series

Convert strings in the Series/Index to uppercase.

Equivalent to str.upper.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['lower',
...                 'CAPITALS',
...                 'this is a sentence',
...                 'SwApCaSe'])
>>> s.str.upper()
0                 LOWER
1              CAPITALS
2    THIS IS A SENTENCE
3              SWAPCASE
dtype: string

Returns
Type	Description
`bigframes.series.Series`	Series with uppercase strings.

zfill

zfill(width: int) -> bigframes.series.Series

Pad strings in the Series/Index by prepending '0' characters.

Strings in the Series/Index are padded with '0' characters on the left of the string to reach a total string length width. Strings in the Series/Index with length greater or equal to width are unchanged.

Examples:

>>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series(['-1', '1', '1000', bpd.NA])
>>> s
0      -1
1       1
2    1000
3    <NA>
dtype: string

>>> s.str.zfill(3)
0     -01
1     001
2    1000
3    <NA>
dtype: string

Parameter
Name	Description
`width`	`int` Minimum length of resulting string; strings with length less than `width` be prepended with '0' characters.

Returns
Type	Description
`bigframes.series.Series`	Series of objects.