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d d d.d$d%Zd-d&d'Zd(S )/ΪExprNameNameSpacez;Namespace for expressions that operate on expression names.ΪnameΪexprr ΪreturnΪNonec C s |j | _ d S )N)Ϊ_pyexpr)Ϊselfr © r ϊG/home/app/Keep/.python/lib/python3.10/site-packages/polars/expr/name.pyΪ__init__ s zExprNameNameSpace.__init__c C σ t | j ‘ S )uΥ
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)
ββββββββ¬βββββββββββ
β a β b β
β --- β --- β
β f64 β f64 β
ββββββββͺβββββββββββ‘
β 10.0 β 3.333333 β
β 5.0 β 2.5 β
ββββββββ΄βββββββββββ
Undo an alias operation.
>>> df.with_columns((pl.col("a") * 9).alias("c").name.keep())
shape: (2, 2)
βββββββ¬ββββββ
β a β b β
β --- β --- β
β i64 β i64 β
βββββββͺββββββ‘
β 9 β 3 β
β 18 β 4 β
βββββββ΄ββββββ
)r r Z name_keep©r
r r r Ϊkeep s +zExprNameNameSpace.keepΪfunctionϊCallable[[str], str]c C σ t | j |‘S )u°
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)
βββββββββββββ¬ββββββββββββ¬ββββββ¬ββββββ
β A_reverse β B_reverse β a β b β
β --- β --- β --- β --- β
β i64 β str β i64 β str β
βββββββββββββͺββββββββββββͺββββββͺββββββ‘
β 3 β z β 1 β x β
β 2 β y β 2 β y β
β 1 β x β 3 β z β
βββββββββββββ΄ββββββββββββ΄ββββββ΄ββββββ
)r r Zname_map©r
r r r r ΪmapB s *zExprNameNameSpace.mapΪprefixΪstrc C r )uΘ
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)
βββββββ¬ββββββ¬ββββββββββββ¬ββββββββββββ
β a β b β reverse_a β reverse_b β
β --- β --- β --- β --- β
β i64 β str β i64 β str β
βββββββͺββββββͺββββββββββββͺββββββββββββ‘
β 1 β x β 3 β z β
β 2 β y β 2 β y β
β 3 β z β 1 β x β
βββββββ΄ββββββ΄ββββββββββββ΄ββββββββββββ
)r r Z name_prefix©r
r r r r r n σ "zExprNameNameSpace.prefixΪsuffixc C r )uΘ
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)
βββββββ¬ββββββ¬ββββββββββββ¬ββββββββββββ
β a β b β a_reverse β b_reverse β
β --- β --- β --- β --- β
β i64 β str β i64 β str β
βββββββͺββββββͺββββββββββββͺββββββββββββ‘
β 1 β x β 3 β z β
β 2 β y β 2 β y β
β 3 β z β 1 β x β
βββββββ΄ββββββ΄ββββββββββββ΄ββββββββββββ
)r r Z name_suffix©r
r r r r r r zExprNameNameSpace.suffixc C r )uπ
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)
ββββββββ¬βββββββ¬βββββββ¬βββββββ
β ColX β ColY β colx β coly β
β --- β --- β --- β --- β
β i64 β str β i64 β str β
ββββββββͺβββββββͺβββββββͺβββββββ‘
β 1 β x β 1 β x β
β 2 β y β 2 β y β
β 3 β z β 3 β z β
ββββββββ΄βββββββ΄βββββββ΄βββββββ
)r r Zname_to_lowercaser r r r Ϊ to_lowercaseΆ σ z ExprNameNameSpace.to_lowercasec C r )uπ
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)
ββββββββ¬βββββββ¬βββββββ¬βββββββ
β ColX β ColY β COLX β COLY β
β --- β --- β --- β --- β
β i64 β str β i64 β str β
ββββββββͺβββββββͺβββββββͺβββββββ‘
β 1 β x β 1 β x β
β 2 β y β 2 β y β
β 3 β z β 3 β z β
ββββββββ΄βββββββ΄βββββββ΄βββββββ
)r r Zname_to_uppercaser r r r Ϊ to_uppercaseΧ r z ExprNameNameSpace.to_uppercasec C r )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 Zname_map_fieldsr r r r Ϊ
map_fieldsψ σ z ExprNameNameSpace.map_fieldsc C r )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 Zname_prefix_fieldsr r r r Ϊ
prefix_fields r# z ExprNameNameSpace.prefix_fieldsF)ΪliteralΪpatternΪvaluer% Ϊboolc C s t | j |||‘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)
βββββββββββ¬ββββββββββ
β col_foo β col_bar β
β --- β --- β
β i64 β str β
βββββββββββͺββββββββββ‘
β 1 β x β
β 2 β y β
β 3 β z β
βββββββββββ΄ββββββββββ
>>> 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)
βββββββ¬ββββββ
β boo β baz β
β --- β --- β
β i64 β i64 β
βββββββͺββββββ‘
β 1 β 2 β
βββββββ΄ββββββ
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+)$", ":$1"))
shape: (1, 3)
βββββββ¬ββββββ¬βββββββββββ
β x:1 β x:2 β group_id β
β --- β --- β --- β
β i64 β i64 β str β
βββββββͺββββββͺβββββββββββ‘
β 1 β 2 β xyz β
βββββββ΄ββββββ΄βββββββββββ
The `${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)
βββββββββ¬ββββββ¬ββββββ¬ββββββ¬ββββββ
β index β hat β hut β sam β sum β
β --- β --- β --- β --- β --- β
β u32 β i64 β i64 β i64 β i64 β
βββββββββͺββββββͺββββββͺββββββͺββββββ‘
β 0 β 1 β 2 β 1 β 2 β
βββββββββ΄ββββββ΄ββββββ΄ββββββ΄ββββββ
)r r Z name_replace)r
r& r' r% r r r Ϊreplace, s czExprNameNameSpace.replacec C r )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 Zname_suffix_fieldsr r r r Ϊ
suffix_fields r# z ExprNameNameSpace.suffix_fieldsN)r r r
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