iUddlmZddlmZddlmZddlmZddl m Z er"ddl m Z m Z ddlmZddlmZdd lmZmZdd lmZe Gd d Zy )) annotations) TYPE_CHECKING) functions)wrap_s) expr_dispatch)CallableSequence)Series)PySeries)IntoExprIntoExprColumn)ExprceZdZdZdZd.dZd/dZd/dZd/dZd/dZ d0d1dZ d0d1d Z d/d Z d d d2d Z d/dZd/dZddd3dZd/dZ d4d d d5dZd6d dd7dZd6d dd7dZddd3dZd d dd d8dZd/dZd/dZd/dZd dd9d Zd/d!Zd/d"Zddd:d#Zddd$d;d%Zdd&dd)Z!d0d?d*Z"d d+d@d,Z#dAd-Z$y)BArrayNameSpacez$Namespace for array related methods.arrc&|j|_yN)_s)selfseriess U/var/www/pod-logistic/pod-ai/venv/lib/python3.12/site-packages/polars/series/array.py__init__zArrayNameSpace.__init__s "IIcy)a" Compute the min values of the sub-arrays. Examples -------- >>> s = pl.Series("a", [[1, 2], [4, 3]], dtype=pl.Array(pl.Int64, 2)) >>> s.arr.min() shape: (2,) Series: 'a' [i64] [ 1 3 ] Nrs rminzArrayNameSpace.minrcy)a" Compute the max values of the sub-arrays. Examples -------- >>> s = pl.Series("a", [[1, 2], [4, 3]], dtype=pl.Array(pl.Int64, 2)) >>> s.arr.max() shape: (2,) Series: 'a' [i64] [ 2 4 ] Nrrs rmaxzArrayNameSpace.max+rrcy)a Compute the sum values of the sub-arrays. Notes ----- If there are no non-null elements in a row, the output is `0`. Examples -------- >>> s = pl.Series([[1, 2], [4, 3]], dtype=pl.Array(pl.Int64, 2)) >>> s.arr.sum() shape: (2,) Series: '' [i64] [ 3 7 ] Nrrs rsumzArrayNameSpace.sum;rrcy)a/ Compute the mean of the values of the sub-arrays. Examples -------- >>> s = pl.Series("a", [[1, 2], [4, 3]], dtype=pl.Array(pl.Int64, 2)) >>> s.arr.mean() shape: (2,) Series: 'a' [f64] [ 1.5 3.5 ] Nrrs rmeanzArrayNameSpace.meanOrrcy)a7 Compute the std of the values of the sub-arrays. Examples -------- >>> s = pl.Series("a", [[1, 2], [4, 3]], dtype=pl.Array(pl.Int64, 2)) >>> s.arr.std() shape: (2,) Series: 'a' [f64] [ 0.707107 0.707107 ] Nrrddofs rstdzArrayNameSpace.std_rrcy)a5 Compute the var of the values of the sub-arrays. Examples -------- >>> s = pl.Series("a", [[1, 2], [4, 3]], dtype=pl.Array(pl.Int64, 2)) >>> s.arr.var() shape: (2,) Series: 'a' [f64] [ 0.5 0.5 ] Nrr&s rvarzArrayNameSpace.varorrcy)a3 Compute the median of the values of the sub-arrays. Examples -------- >>> s = pl.Series("a", [[1, 2], [4, 3]], dtype=pl.Array(pl.Int64, 2)) >>> s.arr.median() shape: (2,) Series: 'a' [f64] [ 1.5 3.5 ] Nrrs rmedianzArrayNameSpace.medianrrF)maintain_ordercy)a Get the unique/distinct values in the array. Parameters ---------- maintain_order Maintain order of data. This requires more work. Returns ------- Series Series of data type :class:`List`. Examples -------- >>> s = pl.Series([[1, 1, 2], [3, 4, 5]], dtype=pl.Array(pl.Int64, 3)) >>> s.arr.unique() shape: (2,) Series: '' [list[i64]] [ [1, 2] [3, 4, 5] ] Nr)rr-s runiquezArrayNameSpace.uniquerrcy)a4 Count the number of unique values in every sub-arrays. Examples -------- >>> s = pl.Series("a", [[1, 2], [4, 4]], dtype=pl.Array(pl.Int64, 2)) >>> s.arr.n_unique() shape: (2,) Series: 'a' [u32] [ 2 1 ] Nrrs rn_uniquezArrayNameSpace.n_uniquerrcy)a Convert an Array column into a List column with the same inner data type. Returns ------- Series Series of data type :class:`List`. Examples -------- >>> s = pl.Series([[1, 2], [3, 4]], dtype=pl.Array(pl.Int8, 2)) >>> s.arr.to_list() shape: (2,) Series: '' [list[i8]] [ [1, 2] [3, 4] ] Nrrs rto_listzArrayNameSpace.to_listrrT) ignore_nullscy)a Evaluate whether any boolean value is true for every subarray. Parameters ---------- ignore_nulls * If set to `True` (default), null values are ignored. If there are no non-null values, the output is `False`. * If set to `False`, `Kleene logic`_ is used to deal with nulls: if the column contains any null values and no `True` values, the output is null. .. _Kleene logic: https://en.wikipedia.org/wiki/Three-valued_logic Returns ------- Series Series of data type :class:`Boolean`. Examples -------- >>> s = pl.Series( ... [[True, True], [False, True], [False, False], [None, None], None], ... dtype=pl.Array(pl.Boolean, 2), ... ) >>> s.arr.any() shape: (5,) Series: '' [bool] [ true true false false null ] Nrrr4s ranyzArrayNameSpace.anyrrcy)a Return the number of elements in each array. Returns ------- Series Series of data type :class:`UInt32`. Examples -------- >>> s = pl.Series("a", [[1, 2], [4, 3]], dtype=pl.Array(pl.Int64, 2)) >>> s.arr.len() shape: (2,) Series: 'a' [u32] [ 2 2 ] Nrrs rlenzArrayNameSpace.lenrrN)as_arraycy)u Slice the sub-arrays. Parameters ---------- offset The starting index of the slice. length The length of the slice. as_array Return the result as a Series of data type :class:`.Array`. Returns ------- Series Series of data type :class:`.List` or :class:`.Array` if `as_array=True`. Examples -------- >>> s = pl.Series( ... [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]], ... dtype=pl.Array(pl.Int64, 6), ... ) >>> s.arr.slice(1) shape: (2,) Series: '' [list[i64]] [ [2, 3, … 6] [8, 9, … 12] ] >>> s.arr.slice(1, 3, as_array=True) shape: (2,) Series: '' [array[i64, 3]] [ [2, 3, 4] [8, 9, 10] ] >>> s.arr.slice(-2) shape: (2,) Series: '' [list[i64]] [ [5, 6] [11, 12] ] Nr)roffsetlengthr:s rslicezArrayNameSpace.slice rrcy)u# Get the first `n` elements of the sub-arrays. Parameters ---------- n Number of values to return for each sublist. as_array Return result as a fixed-length `Array`, otherwise as a `List`. If true `n` must be a constant value. Examples -------- >>> s = pl.Series( ... [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]], ... dtype=pl.Array(pl.Int64, 6), ... ) >>> s.arr.head() shape: (2,) Series: '' [list[i64]] [ [1, 2, … 5] [7, 8, … 11] ] >>> s.arr.head(3, as_array=True) shape: (2,) Series: '' [array[i64, 3]] [ [1, 2, 3] [7, 8, 9] ] Nrrnr:s rheadzArrayNameSpace.head>rrcy)u$ Slice the last `n` values of every sublist. Parameters ---------- n Number of values to return for each sublist. as_array Return result as a fixed-length `Array`, otherwise as a `List`. If true `n` must be a constant value. Examples -------- >>> s = pl.Series( ... [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]], ... dtype=pl.Array(pl.Int64, 6), ... ) >>> s.arr.tail() shape: (2,) Series: '' [list[i64]] [ [2, 3, … 6] [8, 9, … 12] ] >>> s.arr.tail(3, as_array=True) shape: (2,) Series: '' [array[i64, 3]] [ [4, 5, 6] [10, 11, 12] ] Nrr@s rtailzArrayNameSpace.tail`rrcy)a Evaluate whether all boolean values are true for every subarray. Parameters ---------- ignore_nulls * If set to `True` (default), null values are ignored. If there are no non-null values, the output is `True`. * If set to `False`, `Kleene logic`_ is used to deal with nulls: if the column contains any null values and no `False` values, the output is null. .. _Kleene logic: https://en.wikipedia.org/wiki/Three-valued_logic Returns ------- Series Series of data type :class:`Boolean`. Examples -------- >>> s = pl.Series( ... [[True, True], [False, True], [False, False], [None, None], None], ... dtype=pl.Array(pl.Boolean, 2), ... ) >>> s.arr.all() shape: (5,) Series: '' [bool] [ true false false true null ] Nrr6s rallzArrayNameSpace.allrr) descending nulls_last multithreadedcy)a Sort the arrays in this column. Parameters ---------- descending Sort in descending order. nulls_last Place null values last. multithreaded Sort using multiple threads. Examples -------- >>> s = pl.Series("a", [[3, 2, 1], [9, 1, 2]], dtype=pl.Array(pl.Int64, 3)) >>> s.arr.sort() shape: (2,) Series: 'a' [array[i64, 3]] [ [1, 2, 3] [1, 2, 9] ] >>> s.arr.sort(descending=True) shape: (2,) Series: 'a' [array[i64, 3]] [ [3, 2, 1] [9, 2, 1] ] Nr)rrGrHrIs rsortzArrayNameSpace.sortrrcy)a@ Reverse the arrays in this column. Examples -------- >>> s = pl.Series("a", [[3, 2, 1], [9, 1, 2]], dtype=pl.Array(pl.Int64, 3)) >>> s.arr.reverse() shape: (2,) Series: 'a' [array[i64, 3]] [ [1, 2, 3] [2, 1, 9] ] Nrrs rreversezArrayNameSpace.reverserrcy)a Retrieve the index of the minimal value in every sub-array. Returns ------- Series Series of data type :class:`UInt32` or :class:`UInt64` (depending on compilation). Examples -------- >>> s = pl.Series("a", [[3, 2, 1], [9, 1, 2]], dtype=pl.Array(pl.Int64, 3)) >>> s.arr.arg_min() shape: (2,) Series: 'a' [u32] [ 2 1 ] Nrrs rarg_minzArrayNameSpace.arg_minrrcy)a Retrieve the index of the maximum value in every sub-array. Returns ------- Series Series of data type :class:`UInt32` or :class:`UInt64` (depending on compilation). Examples -------- >>> s = pl.Series("a", [[0, 9, 3], [9, 1, 2]], dtype=pl.Array(pl.Int64, 3)) >>> s.arr.arg_max() shape: (2,) Series: 'a' [u32] [ 1 0 ] Nrrs rarg_maxzArrayNameSpace.arg_maxrr) null_on_oobcy)a Get the value by index in the sub-arrays. So index `0` would return the first item of every sublist and index `-1` would return the last item of every sublist if an index is out of bounds, it will return a `None`. Parameters ---------- index Index to return per sublist null_on_oob Behavior if an index is out of bounds: True -> set as null False -> raise an error Returns ------- Series Series of innter data type. Examples -------- >>> s = pl.Series( ... "a", [[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=pl.Array(pl.Int32, 3) ... ) >>> s.arr.get(pl.Series([1, -2, 0]), null_on_oob=True) shape: (3,) Series: 'a' [i32] [ 2 5 7 ] Nr)rindexrRs rgetzArrayNameSpace.getrrcy)a_ Get the first value of the sub-arrays. Examples -------- >>> s = pl.Series( ... "a", [[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=pl.Array(pl.Int32, 3) ... ) >>> s.arr.first() shape: (3,) Series: 'a' [i32] [ 1 4 7 ] Nrrs rfirstzArrayNameSpace.first4rrcy)a] Get the last value of the sub-arrays. Examples -------- >>> s = pl.Series( ... "a", [[1, 2, 3], [4, 5, 6], [7, 9, 8]], dtype=pl.Array(pl.Int32, 3) ... ) >>> s.arr.last() shape: (3,) Series: 'a' [i32] [ 3 6 8 ] Nrrs rlastzArrayNameSpace.lastHrrcy)a+ Join all string items in a sub-array and place a separator between them. This errors if inner type of array `!= String`. Parameters ---------- separator string to separate the items with ignore_nulls Ignore null values (default). If set to ``False``, null values will be propagated. If the sub-list contains any null values, the output is ``None``. Returns ------- Series Series of data type :class:`String`. Examples -------- >>> s = pl.Series([["x", "y"], ["a", "b"]], dtype=pl.Array(pl.String, 2)) >>> s.arr.join(separator="-") shape: (2,) Series: '' [str] [ "x-y" "a-b" ] Nr)r separatorr4s rjoinzArrayNameSpace.join\rr) empty_as_null keep_nullscy)a Returns a column with a separate row for every array element. Parameters ---------- empty_as_null Explode an empty array into a `null`. keep_nulls Explode a `null` array into a `null`. Returns ------- Series Series with the data type of the array elements. Examples -------- >>> s = pl.Series("a", [[1, 2, 3], [4, 5, 6]], dtype=pl.Array(pl.Int64, 3)) >>> s.arr.explode() shape: (6,) Series: 'a' [i64] [ 1 2 3 4 5 6 ] Nr)rr]r^s rexplodezArrayNameSpace.explode~rr) nulls_equalcy)a Check if sub-arrays contain the given item. Parameters ---------- item Item that will be checked for membership nulls_equal : bool, default True If True, treat null as a distinct value. Null values will not propagate. Returns ------- Series Series of data type :class:`Boolean`. Examples -------- >>> s = pl.Series( ... "a", [[3, 2, 1], [1, 2, 3], [4, 5, 6]], dtype=pl.Array(pl.Int32, 3) ... ) >>> s.arr.contains(1) shape: (3,) Series: 'a' [bool] [ true true false ] Nr)ritemras rcontainszArrayNameSpace.containsrrcy)a Count how often the value produced by `element` occurs. Parameters ---------- element An expression that produces a single value Examples -------- >>> s = pl.Series("a", [[1, 2, 3], [2, 2, 2]], dtype=pl.Array(pl.Int64, 3)) >>> s.arr.count_matches(2) shape: (2,) Series: 'a' [u32] [ 1 3 ] Nr)relements r count_matcheszArrayNameSpace.count_matchesrrct|j}|jjt j |j jj|jS)u Convert the series of type `Array` to a series of type `Struct`. Parameters ---------- fields If the name and number of the desired fields is known in advance a list of field names can be given, which will be assigned by index. Otherwise, to dynamically assign field names, a custom function can be used; if neither are set, fields will be `field_0, field_1 .. field_n`. Examples -------- Convert array to struct with default field name assignment: >>> s1 = pl.Series("n", [[0, 1, 2], [3, 4, 5]], dtype=pl.Array(pl.Int8, 3)) >>> s2 = s1.arr.to_struct() >>> s2 shape: (2,) Series: 'n' [struct[3]] [ {0,1,2} {3,4,5} ] >>> s2.struct.fields ['field_0', 'field_1', 'field_2'] Convert array to struct with field name assignment by function/index: >>> s3 = s1.arr.to_struct(fields=lambda idx: f"n{idx:02}") >>> s3.struct.fields ['n00', 'n01', 'n02'] Convert array to struct with field name assignment by index from a list of names: >>> s1.arr.to_struct(fields=["one", "two", "three"]).struct.unnest() shape: (2, 3) ┌─────┬─────┬───────┐ │ one ┆ two ┆ three │ │ --- ┆ --- ┆ --- │ │ i8 ┆ i8 ┆ i8 │ ╞═════╪═════╪═══════╡ │ 0 ┆ 1 ┆ 2 │ │ 3 ┆ 4 ┆ 5 │ └─────┴─────┴───────┘ ) rrto_frameselectFcolnamer to_struct to_series)rfieldsss rrnzArrayNameSpace.to_structsOf 477Ozz|""155=#4#4#>#>v#FGQQSSrcy)a Shift array values by the given number of indices. Parameters ---------- n Number of indices to shift forward. If a negative value is passed, values are shifted in the opposite direction instead. Notes ----- This method is similar to the `LAG` operation in SQL when the value for `n` is positive. With a negative value for `n`, it is similar to `LEAD`. Examples -------- By default, array values are shifted forward by one index. >>> s = pl.Series([[1, 2, 3], [4, 5, 6]], dtype=pl.Array(pl.Int64, 3)) >>> s.arr.shift() shape: (2,) Series: '' [array[i64, 3]] [ [null, 1, 2] [null, 4, 5] ] Pass a negative value to shift in the opposite direction instead. >>> s.arr.shift(-2) shape: (2,) Series: '' [array[i64, 3]] [ [3, null, null] [6, null, null] ] Nr)rrAs rshiftzArrayNameSpace.shift rr)as_listcy)a Run any polars expression against the arrays' elements. Parameters ---------- expr Expression to run. Note that you can select an element with `pl.element()` as_list Collect the resulting data as a list. This allows for expressions which output a variable amount of data. Examples -------- >>> s = pl.Series("a", [[1, 4], [8, 5], [3, 2]], pl.Array(pl.Int64, 2)) >>> s.arr.eval(pl.element().rank()) shape: (3,) Series: 'a' [array[f64, 2]] [ [1.0, 2.0] [2.0, 1.0] [2.0, 1.0] ] Nr)rexprrts revalzArrayNameSpace.eval1rrcy)a Run any polars aggregation expression against the arrays' elements. Parameters ---------- expr Expression to run. Note that you can select an element with `pl.element()`. Examples -------- >>> s = pl.Series( ... "a", [[1, None], [42, 13], [None, None]], pl.Array(pl.Int64, 2) ... ) >>> s.arr.agg(pl.element().null_count()) shape: (3,) Series: 'a' [u32] [ 1 0 2 ] >>> s.arr.agg(pl.element().drop_nulls()) shape: (3,) Series: 'a' [list[i64]] [ [1] [42, 13] [] ] Nr)rrvs raggzArrayNameSpace.aggJrr)rr returnNone)rzr ))r'intrzr )r-boolrzr )r4r~rzr r)r< int | Exprr=zint | Expr | Noner:r~rzr ))rArr:r~rzr )rGr~rHr~rIr~rzr )rTint | IntoExprColumnrRr~rzr )r[r r4r~rzr )r]r~r^r~rzr )rcr rar~rzr )rfr rzr )rpz+Callable[[int], str] | Sequence[str] | Nonerzr )rArrzr )rvrrtr~rzr )rvrrzr )%__name__ __module__ __qualname____doc__ _accessorrrr r"r$r(r*r,r/r1r3r7r9r>rBrDrFrKrMrOrQrUrWrYr\r`rdrgrnrsrwryrrrrrsv.I&   (    05 4  *+/$ L 0%)3  3 3 "3  3  3 j  %  D  %  D+/$ R! " % %  %  %  % N " . .GL$ L ( (GK  D04 @?C @ 0?C4T;4T 4Tl% N38 2 rrN) __future__rtypingrpolarsrrkpolars._utils.wraprpolars.series.utilsrcollections.abcrr r polars._plrr polars._typingr r polars.expr.exprrrrrrrsB" !%-2$7%U  U  U  r