ง
่jF: ใ ๓` d dl mZ d dlmZ d dlmZ er d dlmZ d dlm Z G d dฆ ซ Z
dS ) ้ )ฺ annotations)ฺ
TYPE_CHECKING)ฺ wrap_expr)ฺCallable)ฺExprc ๓t e Zd ZdZdZd dZd dZd d Zd!dZd"dZ d dZ
d dZ d dZ d!dZ
ddd#dZd"d Zd S )$ฺExprNameNameSpacez;Namespace for expressions that operate on expression names.ฺnameฺexprr ฺreturnฺNonec ๓ |j | _ d S )N)ฺ_pyexpr)ฺselfr s ๚U/home/longshao/multi-rider-rag/.venv/lib/python3.11/site-packages/polars/expr/name.pyฺ__init__zExprNameNameSpace.__init__ s ุ| ๓ c ๓N t | j ฆ ซ ฆ ซ S )uี
Keep the original root name of the expression.
See Also
--------
Expr.alias
map
Examples
--------
Prevent errors due to potential duplicate column names.
>>> df = pl.DataFrame(
... {
... "a": [1, 2],
... "b": [3, 4],
... }
... )
>>> df.select((pl.lit(10) / pl.all()).name.keep())
shape: (2, 2)
โโโโโโโโฌโโโโโโโโโโโ
โ a โ b โ
โ --- โ --- โ
โ f64 โ f64 โ
โโโโโโโโชโโโโโโโโโโโก
โ 10.0 โ 3.333333 โ
โ 5.0 โ 2.5 โ
โโโโโโโโดโโโโโโโโโโโ
Undo an alias operation.
>>> df.with_columns((pl.col("a") * 9).alias("c").name.keep())
shape: (2, 2)
โโโโโโโฌโโโโโโ
โ a โ b โ
โ --- โ --- โ
โ i64 โ i64 โ
โโโโโโโชโโโโโโก
โ 9 โ 3 โ
โ 18 โ 4 โ
โโโโโโโดโโโโโโ
)r r ฺ name_keepฉr s r ฺkeepzExprNameNameSpace.keep s! ๕V ื/า/ั1ิ1ั2ิ2ะ2r ฺfunction๚Callable[[str], str]c ๓P t | j |ฆ ซ ฆ ซ S )uฐ
Rename the output of an expression by mapping a function over the root name.
Parameters
----------
function
Function that maps a root name to a new name.
See Also
--------
keep
prefix
suffix
replace
Examples
--------
Remove a common suffix and convert to lower case.
>>> df = pl.DataFrame(
... {
... "A_reverse": [3, 2, 1],
... "B_reverse": ["z", "y", "x"],
... }
... )
>>> df.with_columns(
... pl.all()
... .reverse()
... .name.map(lambda c: c.removesuffix("_reverse").lower())
... )
shape: (3, 4)
โโโโโโโโโโโโโฌโโโโโโโโโโโโฌโโโโโโฌโโโโโโ
โ A_reverse โ B_reverse โ a โ b โ
โ --- โ --- โ --- โ --- โ
โ i64 โ str โ i64 โ str โ
โโโโโโโโโโโโโชโโโโโโโโโโโโชโโโโโโชโโโโโโก
โ 3 โ z โ 1 โ x โ
โ 2 โ y โ 2 โ y โ
โ 1 โ x โ 3 โ z โ
โโโโโโโโโโโโโดโโโโโโโโโโโโดโโโโโโดโโโโโโ
)r r ฺname_mapฉr r s r ฺmapzExprNameNameSpace.mapB s# ๕T ื.า.จxั8ิ8ั9ิ9ะ9r ฺprefixฺstrc ๓P t | j |ฆ ซ ฆ ซ S )uศ
Add a prefix to the root column name of the expression.
Parameters
----------
prefix
Prefix to add to the root column name.
See Also
--------
suffix
map
Examples
--------
>>> df = pl.DataFrame(
... {
... "a": [1, 2, 3],
... "b": ["x", "y", "z"],
... }
... )
>>> df.with_columns(pl.all().reverse().name.prefix("reverse_"))
shape: (3, 4)
โโโโโโโฌโโโโโโฌโโโโโโโโโโโโฌโโโโโโโโโโโโ
โ a โ b โ reverse_a โ reverse_b โ
โ --- โ --- โ --- โ --- โ
โ i64 โ str โ i64 โ str โ
โโโโโโโชโโโโโโชโโโโโโโโโโโโชโโโโโโโโโโโโก
โ 1 โ x โ 3 โ z โ
โ 2 โ y โ 2 โ y โ
โ 3 โ z โ 1 โ x โ
โโโโโโโดโโโโโโดโโโโโโโโโโโโดโโโโโโโโโโโโ
)r r ฺ name_prefixฉr r s r r zExprNameNameSpace.prefixn ๓# ๕D ื1า1ฐ&ั9ิ9ั:ิ:ะ:r ฺsuffixc ๓P t | j |ฆ ซ ฆ ซ S )uศ
Add a suffix to the root column name of the expression.
Parameters
----------
suffix
Suffix to add to the root column name.
See Also
--------
prefix
map
Examples
--------
>>> df = pl.DataFrame(
... {
... "a": [1, 2, 3],
... "b": ["x", "y", "z"],
... }
... )
>>> df.with_columns(pl.all().reverse().name.suffix("_reverse"))
shape: (3, 4)
โโโโโโโฌโโโโโโฌโโโโโโโโโโโโฌโโโโโโโโโโโโ
โ a โ b โ a_reverse โ b_reverse โ
โ --- โ --- โ --- โ --- โ
โ i64 โ str โ i64 โ str โ
โโโโโโโชโโโโโโชโโโโโโโโโโโโชโโโโโโโโโโโโก
โ 1 โ x โ 3 โ z โ
โ 2 โ y โ 2 โ y โ
โ 3 โ z โ 1 โ x โ
โโโโโโโดโโโโโโดโโโโโโโโโโโโดโโโโโโโโโโโโ
)r r ฺ name_suffixฉr r$ s r r$ zExprNameNameSpace.suffix r# r c ๓N t | j ฆ ซ ฆ ซ S )u๐
Make the root column name lowercase.
See Also
--------
prefix
suffix
to_uppercase
map
Examples
--------
>>> df = pl.DataFrame(
... {
... "ColX": [1, 2, 3],
... "ColY": ["x", "y", "z"],
... }
... )
>>> df.with_columns(pl.all().name.to_lowercase())
shape: (3, 4)
โโโโโโโโฌโโโโโโโฌโโโโโโโฌโโโโโโโ
โ ColX โ ColY โ colx โ coly โ
โ --- โ --- โ --- โ --- โ
โ i64 โ str โ i64 โ str โ
โโโโโโโโชโโโโโโโชโโโโโโโชโโโโโโโก
โ 1 โ x โ 1 โ x โ
โ 2 โ y โ 2 โ y โ
โ 3 โ z โ 3 โ z โ
โโโโโโโโดโโโโโโโดโโโโโโโดโโโโโโโ
)r r ฺname_to_lowercaser s r ฺ to_lowercasez ExprNameNameSpace.to_lowercaseถ ๓ ๕> ื7า7ั9ิ9ั:ิ:ะ:r c ๓N t | j ฆ ซ ฆ ซ S )u๐
Make the root column name uppercase.
See Also
--------
prefix
suffix
to_lowercase
map
Examples
--------
>>> df = pl.DataFrame(
... {
... "ColX": [1, 2, 3],
... "ColY": ["x", "y", "z"],
... }
... )
>>> df.with_columns(pl.all().name.to_uppercase())
shape: (3, 4)
โโโโโโโโฌโโโโโโโฌโโโโโโโฌโโโโโโโ
โ ColX โ ColY โ COLX โ COLY โ
โ --- โ --- โ --- โ --- โ
โ i64 โ str โ i64 โ str โ
โโโโโโโโชโโโโโโโชโโโโโโโชโโโโโโโก
โ 1 โ x โ 1 โ x โ
โ 2 โ y โ 2 โ y โ
โ 3 โ z โ 3 โ z โ
โโโโโโโโดโโโโโโโดโโโโโโโดโโโโโโโ
)r r ฺname_to_uppercaser s r ฺ to_uppercasez ExprNameNameSpace.to_uppercaseื r+ r c ๓P t | j |ฆ ซ ฆ ซ S )aL
Rename fields of a struct by mapping a function over the field name(s).
Notes
-----
This only takes effect for struct columns.
Parameters
----------
function
Function that maps a field name to a new name.
See Also
--------
prefix_fields
suffix_fields
Examples
--------
>>> df = pl.DataFrame({"x": {"a": 1, "b": 2}})
>>> df.select(pl.col("x").name.map_fields(lambda x: x.upper())).schema
Schema({'x': Struct({'A': Int64, 'B': Int64})})
)r r ฺname_map_fieldsr s r ฺ
map_fieldsz ExprNameNameSpace.map_fields๘ s" ๕0 ื5า5ฐhั?ิ?ั@ิ@ะ@r c ๓P t | j |ฆ ซ ฆ ซ S )a%
Add a prefix to all field names of a struct.
Notes
-----
This only takes effect for struct columns.
Parameters
----------
prefix
Prefix to add to the field name.
See Also
--------
map_fields
suffix_fields
Examples
--------
>>> df = pl.DataFrame({"x": {"a": 1, "b": 2}})
>>> df.select(pl.col("x").name.prefix_fields("prefix_")).schema
Schema({'x': Struct({'prefix_a': Int64, 'prefix_b': Int64})})
)r r ฺname_prefix_fieldsr" s r ฺ
prefix_fieldsz ExprNameNameSpace.prefix_fields ๓" ๕0 ื8า8ธั@ิ@ัAิAะAr F)ฺliteralฺpatternฺvaluer6 ฺboolc ๓T t | j |||ฆ ซ ฆ ซ S )u/
Replace matching regex/literal substring in the name with a new value.
Parameters
----------
pattern
A valid regular expression pattern, compatible with the `regex crate
`_.
value
String that will replace the matched substring.
literal
Treat `pattern` as a literal string, not a regex.
Notes
-----
* To modify regular expression behaviour (such as case-sensitivity) with flags,
use the inline `(?iLmsuxU)` syntax. See the regex crate's section on
`grouping and flags `_
for additional information about the use of inline expression modifiers.
* The dollar sign (`$`) is a special character related to capture groups; if you
want to replace some target pattern with characters that include a literal `$`
you should escape it by doubling it up as `$$`, or set `literal=True` if you
do not need a full regular expression pattern match. Otherwise, you will be
referencing a (potentially non-existent) capture group.
See Also
--------
Expr.str.replace
Examples
--------
>>> df = pl.DataFrame(
... {
... "n_foo": [1, 2, 3],
... "n_bar": ["x", "y", "z"],
... }
... )
>>> df.select(pl.all().name.replace(r"^n_", "col_"))
shape: (3, 2)
โโโโโโโโโโโฌโโโโโโโโโโ
โ col_foo โ col_bar โ
โ --- โ --- โ
โ i64 โ str โ
โโโโโโโโโโโชโโโโโโโโโโก
โ 1 โ x โ
โ 2 โ y โ
โ 3 โ z โ
โโโโโโโโโโโดโโโโโโโโโโ
>>> df.select(pl.all().name.replace(r"(a|e|i|o|u)", "@")).schema
Schema({'n_f@@': Int64, 'n_b@r': String})
Apply case-insensitive string replacement using the `(?i)` flag.
>>> pl.DataFrame({"Foo": [1], "faz": [2]}).select(
... pl.all().name.replace(r"(?i)^f", "b")
... )
shape: (1, 2)
โโโโโโโฌโโโโโโ
โ boo โ baz โ
โ --- โ --- โ
โ i64 โ i64 โ
โโโโโโโชโโโโโโก
โ 1 โ 2 โ
โโโโโโโดโโโโโโ
Capture groups are supported. Use `$1` or `${1}` in the `value` string to refer
to the first capture group in the pattern, `$2` or `${2}` to refer to the
second capture group, and so on. You can also use named capture groups.
>>> df = pl.DataFrame({"x_1": [1], "x_2": [2], "group_id": ["xyz"]})
>>> df.select(pl.all().name.replace(r"_(\d+)$", ":$1"))
shape: (1, 3)
โโโโโโโฌโโโโโโฌโโโโโโโโโโโ
โ x:1 โ x:2 โ group_id โ
โ --- โ --- โ --- โ
โ i64 โ i64 โ str โ
โโโโโโโชโโโโโโชโโโโโโโโโโโก
โ 1 โ 2 โ xyz โ
โโโโโโโดโโโโโโดโโโโโโโโโโโ
The `${1}` form is used to disambiguate the group reference from surrounding
text.
>>> df = pl.DataFrame({"hat": [1], "hut": [2]}).with_row_index()
>>> df.with_columns(pl.all().name.replace(r"^h(.)t", "s$1m")) # doctest: +SKIP
# ComputeError: the name 's' passed to `LazyFrame.with_columns` is duplicate
>>> df.with_columns(pl.all().name.replace(r"^h(.)t", "s${1}m"))
shape: (1, 5)
โโโโโโโโโฌโโโโโโฌโโโโโโฌโโโโโโฌโโโโโโ
โ index โ hat โ hut โ sam โ sum โ
โ --- โ --- โ --- โ --- โ --- โ
โ u32 โ i64 โ i64 โ i64 โ i64 โ
โโโโโโโโโชโโโโโโชโโโโโโชโโโโโโชโโโโโโก
โ 0 โ 1 โ 2 โ 1 โ 2 โ
โโโโโโโโโดโโโโโโดโโโโโโดโโโโโโดโโโโโโ
)r r ฺ name_replace)r r7 r8 r6 s r ฺreplacezExprNameNameSpace.replace, s' ๕F ื2า2ฐ7ธEภ7ัKิKัLิLะLr c ๓P t | j |ฆ ซ ฆ ซ S )a%
Add a suffix to all field names of a struct.
Notes
-----
This only takes effect for struct columns.
Parameters
----------
suffix
Suffix to add to the field name.
See Also
--------
map_fields
prefix_fields
Examples
--------
>>> df = pl.DataFrame({"x": {"a": 1, "b": 2}})
>>> df.select(pl.col("x").name.suffix_fields("_suffix")).schema
Schema({'x': Struct({'a_suffix': Int64, 'b_suffix': Int64})})
)r r ฺname_suffix_fieldsr' s r ฺ
suffix_fieldsz ExprNameNameSpace.suffix_fields r5 r N)r r r r
)r r )r r r r )r r r r )r$ r r r )r7 r r8 r r6 r9 r r )ฺ__name__ฺ
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