neulab/docprompting-conala huggingface dataset:
pandas.Series.str.islower   Series.str.islower()[source]
 
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.  Returns 
 Series or Index of bool

Series or Index of boolean values with the same length as the original Series/Index.      See also  Series.str.isalpha

Check whether all characters are alphabetic.  Series.str.isnumeric

Check whether all characters are numeric.  Series.str.isalnum

Check whether all characters are alphanumeric.  Series.str.isdigit

Check whether all characters are digits.  Series.str.isdecimal

Check whether all characters are decimal.  Series.str.isspace

Check whether all characters are whitespace.  Series.str.islower

Check whether all characters are lowercase.  Series.str.isupper

Check whether all characters are uppercase.  Series.str.istitle

Check whether all characters are titlecase.    Examples Checks for Alphabetic and Numeric Characters 
>>> s1 = pd.Series(['one', 'one1', '1', ''])
  
>>> s1.str.isalpha()
0     True
1    False
2    False
3    False
dtype: bool
  
>>> s1.str.isnumeric()
0    False
1    False
2     True
3    False
dtype: bool
  
>>> s1.str.isalnum()
0     True
1     True
2     True
3    False
dtype: bool
  Note that checks against characters mixed with any additional punctuation or whitespace will evaluate to false for an alphanumeric check. 
>>> s2 = pd.Series(['A B', '1.5', '3,000'])
>>> s2.str.isalnum()
0    False
1    False
2    False
dtype: bool
  More Detailed Checks for Numeric Characters There are several different but overlapping sets of numeric characters that can be checked for. 
>>> s3 = pd.Series(['23', '³', '⅕', ''])
  The s3.str.isdecimal method checks for characters used to form numbers in base 10. 
>>> s3.str.isdecimal()
0     True
1    False
2    False
3    False
dtype: bool
  The s.str.isdigit method is the same as s3.str.isdecimal but also includes special digits, like superscripted and subscripted digits in unicode. 
>>> s3.str.isdigit()
0     True
1     True
2    False
3    False
dtype: bool
  The s.str.isnumeric method is the same as s3.str.isdigit but also includes other characters that can represent quantities such as unicode fractions. 
>>> s3.str.isnumeric()
0     True
1     True
2     True
3    False
dtype: bool
  Checks for Whitespace 
>>> s4 = pd.Series([' ', '\t\r\n ', ''])
>>> s4.str.isspace()
0     True
1     True
2    False
dtype: bool
  Checks for Character Case 
>>> s5 = pd.Series(['leopard', 'Golden Eagle', 'SNAKE', ''])
  
>>> s5.str.islower()
0     True
1    False
2    False
3    False
dtype: bool
  
>>> s5.str.isupper()
0    False
1    False
2     True
3    False
dtype: bool
  The s5.str.istitle method checks for whether all words are in title case (whether only the first letter of each word is capitalized). Words are assumed to be as any sequence of non-numeric characters separated by whitespace characters. 
>>> s5.str.istitle()
0    False
1     True
2    False
3    False
dtype: bool
pandas.Series.str.isnumeric   Series.str.isnumeric()[source]
 
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.  Returns 
 Series or Index of bool

Series or Index of boolean values with the same length as the original Series/Index.      See also  Series.str.isalpha

Check whether all characters are alphabetic.  Series.str.isnumeric

Check whether all characters are numeric.  Series.str.isalnum

Check whether all characters are alphanumeric.  Series.str.isdigit

Check whether all characters are digits.  Series.str.isdecimal

Check whether all characters are decimal.  Series.str.isspace

Check whether all characters are whitespace.  Series.str.islower

Check whether all characters are lowercase.  Series.str.isupper

Check whether all characters are uppercase.  Series.str.istitle

Check whether all characters are titlecase.    Examples Checks for Alphabetic and Numeric Characters 
>>> s1 = pd.Series(['one', 'one1', '1', ''])
  
>>> s1.str.isalpha()
0     True
1    False
2    False
3    False
dtype: bool
  
>>> s1.str.isnumeric()
0    False
1    False
2     True
3    False
dtype: bool
  
>>> s1.str.isalnum()
0     True
1     True
2     True
3    False
dtype: bool
  Note that checks against characters mixed with any additional punctuation or whitespace will evaluate to false for an alphanumeric check. 
>>> s2 = pd.Series(['A B', '1.5', '3,000'])
>>> s2.str.isalnum()
0    False
1    False
2    False
dtype: bool
  More Detailed Checks for Numeric Characters There are several different but overlapping sets of numeric characters that can be checked for. 
>>> s3 = pd.Series(['23', '³', '⅕', ''])
  The s3.str.isdecimal method checks for characters used to form numbers in base 10. 
>>> s3.str.isdecimal()
0     True
1    False
2    False
3    False
dtype: bool
  The s.str.isdigit method is the same as s3.str.isdecimal but also includes special digits, like superscripted and subscripted digits in unicode. 
>>> s3.str.isdigit()
0     True
1     True
2    False
3    False
dtype: bool
  The s.str.isnumeric method is the same as s3.str.isdigit but also includes other characters that can represent quantities such as unicode fractions. 
>>> s3.str.isnumeric()
0     True
1     True
2     True
3    False
dtype: bool
  Checks for Whitespace 
>>> s4 = pd.Series([' ', '\t\r\n ', ''])
>>> s4.str.isspace()
0     True
1     True
2    False
dtype: bool
  Checks for Character Case 
>>> s5 = pd.Series(['leopard', 'Golden Eagle', 'SNAKE', ''])
  
>>> s5.str.islower()
0     True
1    False
2    False
3    False
dtype: bool
  
>>> s5.str.isupper()
0    False
1    False
2     True
3    False
dtype: bool
  The s5.str.istitle method checks for whether all words are in title case (whether only the first letter of each word is capitalized). Words are assumed to be as any sequence of non-numeric characters separated by whitespace characters. 
>>> s5.str.istitle()
0    False
1     True
2    False
3    False
dtype: bool
pandas.Series.str.isspace   Series.str.isspace()[source]
 
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.  Returns 
 Series or Index of bool

Series or Index of boolean values with the same length as the original Series/Index.      See also  Series.str.isalpha

Check whether all characters are alphabetic.  Series.str.isnumeric

Check whether all characters are numeric.  Series.str.isalnum

Check whether all characters are alphanumeric.  Series.str.isdigit

Check whether all characters are digits.  Series.str.isdecimal

Check whether all characters are decimal.  Series.str.isspace

Check whether all characters are whitespace.  Series.str.islower

Check whether all characters are lowercase.  Series.str.isupper

Check whether all characters are uppercase.  Series.str.istitle

Check whether all characters are titlecase.    Examples Checks for Alphabetic and Numeric Characters 
>>> s1 = pd.Series(['one', 'one1', '1', ''])
  
>>> s1.str.isalpha()
0     True
1    False
2    False
3    False
dtype: bool
  
>>> s1.str.isnumeric()
0    False
1    False
2     True
3    False
dtype: bool
  
>>> s1.str.isalnum()
0     True
1     True
2     True
3    False
dtype: bool
  Note that checks against characters mixed with any additional punctuation or whitespace will evaluate to false for an alphanumeric check. 
>>> s2 = pd.Series(['A B', '1.5', '3,000'])
>>> s2.str.isalnum()
0    False
1    False
2    False
dtype: bool
  More Detailed Checks for Numeric Characters There are several different but overlapping sets of numeric characters that can be checked for. 
>>> s3 = pd.Series(['23', '³', '⅕', ''])
  The s3.str.isdecimal method checks for characters used to form numbers in base 10. 
>>> s3.str.isdecimal()
0     True
1    False
2    False
3    False
dtype: bool
  The s.str.isdigit method is the same as s3.str.isdecimal but also includes special digits, like superscripted and subscripted digits in unicode. 
>>> s3.str.isdigit()
0     True
1     True
2    False
3    False
dtype: bool
  The s.str.isnumeric method is the same as s3.str.isdigit but also includes other characters that can represent quantities such as unicode fractions. 
>>> s3.str.isnumeric()
0     True
1     True
2     True
3    False
dtype: bool
  Checks for Whitespace 
>>> s4 = pd.Series([' ', '\t\r\n ', ''])
>>> s4.str.isspace()
0     True
1     True
2    False
dtype: bool
  Checks for Character Case 
>>> s5 = pd.Series(['leopard', 'Golden Eagle', 'SNAKE', ''])
  
>>> s5.str.islower()
0     True
1    False
2    False
3    False
dtype: bool
  
>>> s5.str.isupper()
0    False
1    False
2     True
3    False
dtype: bool
  The s5.str.istitle method checks for whether all words are in title case (whether only the first letter of each word is capitalized). Words are assumed to be as any sequence of non-numeric characters separated by whitespace characters. 
>>> s5.str.istitle()
0    False
1     True
2    False
3    False
dtype: bool
pandas.Series.str.istitle   Series.str.istitle()[source]
 
Check whether all characters in each string are titlecase. This is equivalent to running the Python string method str.istitle() for each element of the Series/Index. If a string has zero characters, False is returned for that check.  Returns 
 Series or Index of bool

Series or Index of boolean values with the same length as the original Series/Index.      See also  Series.str.isalpha

Check whether all characters are alphabetic.  Series.str.isnumeric

Check whether all characters are numeric.  Series.str.isalnum

Check whether all characters are alphanumeric.  Series.str.isdigit

Check whether all characters are digits.  Series.str.isdecimal

Check whether all characters are decimal.  Series.str.isspace

Check whether all characters are whitespace.  Series.str.islower

Check whether all characters are lowercase.  Series.str.isupper

Check whether all characters are uppercase.  Series.str.istitle

Check whether all characters are titlecase.    Examples Checks for Alphabetic and Numeric Characters 
>>> s1 = pd.Series(['one', 'one1', '1', ''])
  
>>> s1.str.isalpha()
0     True
1    False
2    False
3    False
dtype: bool
  
>>> s1.str.isnumeric()
0    False
1    False
2     True
3    False
dtype: bool
  
>>> s1.str.isalnum()
0     True
1     True
2     True
3    False
dtype: bool
  Note that checks against characters mixed with any additional punctuation or whitespace will evaluate to false for an alphanumeric check. 
>>> s2 = pd.Series(['A B', '1.5', '3,000'])
>>> s2.str.isalnum()
0    False
1    False
2    False
dtype: bool
  More Detailed Checks for Numeric Characters There are several different but overlapping sets of numeric characters that can be checked for. 
>>> s3 = pd.Series(['23', '³', '⅕', ''])
  The s3.str.isdecimal method checks for characters used to form numbers in base 10. 
>>> s3.str.isdecimal()
0     True
1    False
2    False
3    False
dtype: bool
  The s.str.isdigit method is the same as s3.str.isdecimal but also includes special digits, like superscripted and subscripted digits in unicode. 
>>> s3.str.isdigit()
0     True
1     True
2    False
3    False
dtype: bool
  The s.str.isnumeric method is the same as s3.str.isdigit but also includes other characters that can represent quantities such as unicode fractions. 
>>> s3.str.isnumeric()
0     True
1     True
2     True
3    False
dtype: bool
  Checks for Whitespace 
>>> s4 = pd.Series([' ', '\t\r\n ', ''])
>>> s4.str.isspace()
0     True
1     True
2    False
dtype: bool
  Checks for Character Case 
>>> s5 = pd.Series(['leopard', 'Golden Eagle', 'SNAKE', ''])
  
>>> s5.str.islower()
0     True
1    False
2    False
3    False
dtype: bool
  
>>> s5.str.isupper()
0    False
1    False
2     True
3    False
dtype: bool
  The s5.str.istitle method checks for whether all words are in title case (whether only the first letter of each word is capitalized). Words are assumed to be as any sequence of non-numeric characters separated by whitespace characters. 
>>> s5.str.istitle()
0    False
1     True
2    False
3    False
dtype: bool
pandas.Series.str.isupper   Series.str.isupper()[source]
 
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.  Returns 
 Series or Index of bool

Series or Index of boolean values with the same length as the original Series/Index.      See also  Series.str.isalpha

Check whether all characters are alphabetic.  Series.str.isnumeric

Check whether all characters are numeric.  Series.str.isalnum

Check whether all characters are alphanumeric.  Series.str.isdigit

Check whether all characters are digits.  Series.str.isdecimal

Check whether all characters are decimal.  Series.str.isspace

Check whether all characters are whitespace.  Series.str.islower

Check whether all characters are lowercase.  Series.str.isupper

Check whether all characters are uppercase.  Series.str.istitle

Check whether all characters are titlecase.    Examples Checks for Alphabetic and Numeric Characters 
>>> s1 = pd.Series(['one', 'one1', '1', ''])
  
>>> s1.str.isalpha()
0     True
1    False
2    False
3    False
dtype: bool
  
>>> s1.str.isnumeric()
0    False
1    False
2     True
3    False
dtype: bool
  
>>> s1.str.isalnum()
0     True
1     True
2     True
3    False
dtype: bool
  Note that checks against characters mixed with any additional punctuation or whitespace will evaluate to false for an alphanumeric check. 
>>> s2 = pd.Series(['A B', '1.5', '3,000'])
>>> s2.str.isalnum()
0    False
1    False
2    False
dtype: bool
  More Detailed Checks for Numeric Characters There are several different but overlapping sets of numeric characters that can be checked for. 
>>> s3 = pd.Series(['23', '³', '⅕', ''])
  The s3.str.isdecimal method checks for characters used to form numbers in base 10. 
>>> s3.str.isdecimal()
0     True
1    False
2    False
3    False
dtype: bool
  The s.str.isdigit method is the same as s3.str.isdecimal but also includes special digits, like superscripted and subscripted digits in unicode. 
>>> s3.str.isdigit()
0     True
1     True
2    False
3    False
dtype: bool
  The s.str.isnumeric method is the same as s3.str.isdigit but also includes other characters that can represent quantities such as unicode fractions. 
>>> s3.str.isnumeric()
0     True
1     True
2     True
3    False
dtype: bool
  Checks for Whitespace 
>>> s4 = pd.Series([' ', '\t\r\n ', ''])
>>> s4.str.isspace()
0     True
1     True
2    False
dtype: bool
  Checks for Character Case 
>>> s5 = pd.Series(['leopard', 'Golden Eagle', 'SNAKE', ''])
  
>>> s5.str.islower()
0     True
1    False
2    False
3    False
dtype: bool
  
>>> s5.str.isupper()
0    False
1    False
2     True
3    False
dtype: bool
  The s5.str.istitle method checks for whether all words are in title case (whether only the first letter of each word is capitalized). Words are assumed to be as any sequence of non-numeric characters separated by whitespace characters. 
>>> s5.str.istitle()
0    False
1     True
2    False
3    False
dtype: bool
pandas.Series.str.join   Series.str.join(sep)[source]
 
Join lists contained as elements in the Series/Index with passed delimiter. If the elements of a Series are lists themselves, join the content of these lists using the delimiter passed to the function. This function is an equivalent to str.join().  Parameters 
 
sep:str


Delimiter to use between list entries.    Returns 
 Series/Index: object

The list entries concatenated by intervening occurrences of the delimiter.    Raises 
 AttributeError

If the supplied Series contains neither strings nor lists.      See also  str.join

Standard library version of this method.  Series.str.split

Split strings around given separator/delimiter.    Notes If any of the list items is not a string object, the result of the join will be NaN. Examples Example with a list that contains non-string elements. 
>>> s = pd.Series([['lion', 'elephant', 'zebra'],
...                [1.1, 2.2, 3.3],
...                ['cat', np.nan, 'dog'],
...                ['cow', 4.5, 'goat'],
...                ['duck', ['swan', 'fish'], 'guppy']])
>>> s
0        [lion, elephant, zebra]
1                [1.1, 2.2, 3.3]
2                [cat, nan, dog]
3               [cow, 4.5, goat]
4    [duck, [swan, fish], guppy]
dtype: object
  Join all lists using a ‘-’. The lists containing object(s) of types other than str will produce a NaN. 
>>> s.str.join('-')
0    lion-elephant-zebra
1                    NaN
2                    NaN
3                    NaN
4                    NaN
dtype: object
pandas.Series.str.len   Series.str.len()[source]
 
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).  Returns 
 Series or Index of int

A Series or Index of integer values indicating the length of each element in the Series or Index.      See also  str.len

Python built-in function returning the length of an object.  Series.size

Returns the length of the Series.    Examples Returns the length (number of characters) in a string. Returns the number of entries for dictionaries, lists or tuples. 
>>> s = pd.Series(['dog',
...                 '',
...                 5,
...                 {'foo' : 'bar'},
...                 [2, 3, 5, 7],
...                 ('one', 'two', 'three')])
>>> s
0                  dog
1
2                    5
3       {'foo': 'bar'}
4         [2, 3, 5, 7]
5    (one, two, three)
dtype: object
>>> s.str.len()
0    3.0
1    0.0
2    NaN
3    1.0
4    4.0
5    3.0
dtype: float64
pandas.Series.str.ljust   Series.str.ljust(width, fillchar=' ')[source]
 
Pad right side of strings in the Series/Index. Equivalent to str.ljust().  Parameters 
 
width:int


Minimum width of resulting string; additional characters will be filled with fillchar.  
fillchar:str


Additional character for filling, default is whitespace.    Returns 
 
filled:Series/Index of objects.
pandas.Series.str.lower   Series.str.lower()[source]
 
Convert strings in the Series/Index to lowercase. Equivalent to str.lower().  Returns 
 Series or Index of object
    See also  Series.str.lower

Converts all characters to lowercase.  Series.str.upper

Converts all characters to uppercase.  Series.str.title

Converts first character of each word to uppercase and remaining to lowercase.  Series.str.capitalize

Converts first character to uppercase and remaining to lowercase.  Series.str.swapcase

Converts uppercase to lowercase and lowercase to uppercase.  Series.str.casefold

Removes all case distinctions in the string.    Examples 
>>> s = pd.Series(['lower', 'CAPITALS', 'this is a sentence', 'SwApCaSe'])
>>> s
0                 lower
1              CAPITALS
2    this is a sentence
3              SwApCaSe
dtype: object
  
>>> s.str.lower()
0                 lower
1              capitals
2    this is a sentence
3              swapcase
dtype: object
  
>>> s.str.upper()
0                 LOWER
1              CAPITALS
2    THIS IS A SENTENCE
3              SWAPCASE
dtype: object
  
>>> s.str.title()
0                 Lower
1              Capitals
2    This Is A Sentence
3              Swapcase
dtype: object
  
>>> s.str.capitalize()
0                 Lower
1              Capitals
2    This is a sentence
3              Swapcase
dtype: object
  
>>> s.str.swapcase()
0                 LOWER
1              capitals
2    THIS IS A SENTENCE
3              sWaPcAsE
dtype: object
pandas.Series.str.lstrip   Series.str.lstrip(to_strip=None)[source]
 
Remove leading characters. Strip whitespaces (including newlines) or a set of specified characters from each string in the Series/Index from left side. Equivalent to str.lstrip().  Parameters 
 
to_strip:str or None, default None


Specifying the set of characters to be removed. All combinations of this set of characters will be stripped. If None then whitespaces are removed.    Returns 
 Series or Index of object
    See also  Series.str.strip

Remove leading and trailing characters in Series/Index.  Series.str.lstrip

Remove leading characters in Series/Index.  Series.str.rstrip

Remove trailing characters in Series/Index.    Examples 
>>> s = pd.Series(['1. Ant.  ', '2. Bee!\n', '3. Cat?\t', np.nan])
>>> s
0    1. Ant.
1    2. Bee!\n
2    3. Cat?\t
3          NaN
dtype: object
  
>>> s.str.strip()
0    1. Ant.
1    2. Bee!
2    3. Cat?
3        NaN
dtype: object
  
>>> s.str.lstrip('123.')
0    Ant.
1    Bee!\n
2    Cat?\t
3       NaN
dtype: object
  
>>> s.str.rstrip('.!? \n\t')
0    1. Ant
1    2. Bee
2    3. Cat
3       NaN
dtype: object
  
>>> s.str.strip('123.!? \n\t')
0    Ant
1    Bee
2    Cat
3    NaN
dtype: object
pandas.Series.str.match   Series.str.match(pat, case=True, flags=0, na=None)[source]
 
Determine if each string starts with a match of a regular expression.  Parameters 
 
pat:str


Character sequence or regular expression.  
case:bool, default True


If True, case sensitive.  
flags:int, default 0 (no flags)


Regex module flags, e.g. re.IGNORECASE.  
na:scalar, optional


Fill value for missing values. The default depends on dtype of the array. For object-dtype, numpy.nan is used. For StringDtype, pandas.NA is used.    Returns 
 Series/Index/array of boolean values
    See also  fullmatch

Stricter matching that requires the entire string to match.  contains

Analogous, but less strict, relying on re.search instead of re.match.  extract

Extract matched groups.
pandas.Series.str.normalize   Series.str.normalize(form)[source]
 
Return the Unicode normal form for the strings in the Series/Index. For more information on the forms, see the unicodedata.normalize().  Parameters 
 
form:{‘NFC’, ‘NFKC’, ‘NFD’, ‘NFKD’}


Unicode form.    Returns 
 
normalized:Series/Index of objects
pandas.Series.str.pad   Series.str.pad(width, side='left', fillchar=' ')[source]
 
Pad strings in the Series/Index up to width.  Parameters 
 
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 
 Series or Index of object

Returns Series or Index with minimum number of char in object.      See also  Series.str.rjust

Fills the left side of strings with an arbitrary character. Equivalent to Series.str.pad(side='left').  Series.str.ljust

Fills the right side of strings with an arbitrary character. Equivalent to Series.str.pad(side='right').  Series.str.center

Fills both sides of strings with an arbitrary character. Equivalent to Series.str.pad(side='both').  Series.str.zfill

Pad strings in the Series/Index by prepending ‘0’ character. Equivalent to Series.str.pad(side='left', fillchar='0').    Examples 
>>> s = pd.Series(["caribou", "tiger"])
>>> s
0    caribou
1      tiger
dtype: object
  
>>> s.str.pad(width=10)
0       caribou
1         tiger
dtype: object
  
>>> s.str.pad(width=10, side='right', fillchar='-')
0    caribou---
1    tiger-----
dtype: object
  
>>> s.str.pad(width=10, side='both', fillchar='-')
0    -caribou--
1    --tiger---
dtype: object