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Parameters ---------- start Lower bound of the range. end Upper bound of the range. num_samples Number of samples in the output sequence. closed : {'both', 'left', 'right', 'none'} Define which sides of the interval are closed (inclusive). eager Evaluate immediately and return a `Series`. If set to `False` (default), return an expression instead. .. warning:: This functionality is experimental. It may be changed at any point without it being considered a breaking change. Notes ----- `linear_space` works with numeric and temporal dtypes. When the `start` and `end` parameters are `Date` dtypes, the output sequence consists of equally-spaced `Datetime` elements with millisecond precision. Returns ------- Expr or Series Column of data type `:class:Time`. Examples -------- >>> pl.linear_space(start=0, end=1, num_samples=3, eager=True) shape: (3,) Series: 'literal' [f64] [ 0.0 0.5 1.0 ] >>> pl.linear_space(start=0, end=1, num_samples=3, closed="left", eager=True) shape: (3,) Series: 'literal' [f64] [ 0.0 0.333333 0.666667 ] >>> pl.linear_space(start=0, end=1, num_samples=3, closed="right", eager=True) shape: (3,) Series: 'literal' [f64] [ 0.333333 0.666667 1.0 ] >>> pl.linear_space(start=0, end=1, num_samples=3, closed="none", eager=True) shape: (3,) Series: 'literal' [f64] [ 0.25 0.5 0.75 ] >>> from datetime import time >>> pl.linear_space( ... start=time(hour=1), end=time(hour=12), num_samples=3, eager=True ... ) shape: (3,) Series: 'literal' [time] [ 01:00:00 06:30:00 12:00:00 ] `Date` endpoints generate a sequence of `Datetime` values: >>> from datetime import date >>> pl.linear_space( ... start=date(2025, 1, 1), ... end=date(2025, 2, 1), ... num_samples=3, ... closed="right", ... eager=True, ... ) shape: (3,) Series: 'literal' [datetime[ms]] [ 2025-01-11 08:00:00 2025-01-21 16:00:00 2025-02-01 00:00:00 ] When `eager=False` (default), an expression is produced. You can generate a sequence using the length of the dataframe: >>> df = pl.DataFrame({"a": [1, 2, 3, 4, 5]}) >>> df.with_columns(pl.linear_space(0, 1, pl.len()).alias("ls")) shape: (5, 2) β”Œβ”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β” β”‚ a ┆ ls β”‚ β”‚ --- ┆ --- β”‚ β”‚ i64 ┆ f64 β”‚ β•žβ•β•β•β•β•β•ͺ══════║ β”‚ 1 ┆ 0.0 β”‚ β”‚ 2 ┆ 0.25 β”‚ β”‚ 3 ┆ 0.5 β”‚ β”‚ 4 ┆ 0.75 β”‚ β”‚ 5 ┆ 1.0 β”‚ β””β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”˜ )rr ΪplrrΪFΪselectΪ to_series)rrrrrΪresults rrr<s^€τv " %Σ (€Eά  Σ $€Cά'¨ Σ4€Kά ”sΧ'Ρ'¨¨s°KΐΣHΣ I€Fα ܏x‰x˜ΣΧ)Ρ)Σ+Π+ΰ €Mr)rΪas_arrayrcσ—yrr©rrrrr'rs rΪ linear_spacesr*Βs€π r)rr'cσ—yrrr)s rr*r*Ξs€πrcσ—yrrr)s rr*r*Ϊs€πrc σΦ—t|«}t|«}t|«}ttj|||||««}|r#t j |«j «S|S)u{ Generate a sequence of evenly-spaced values for each row between `start` and `end`. The number of values in each sequence is determined by `num_samples`. Parameters ---------- start Lower bound of the range. end Upper bound of the range. num_samples Number of samples in the output sequence. closed : {'both', 'left', 'right', 'none'} Define which sides of the interval are closed (inclusive). as_array Return result as a fixed-length `Array`. `num_samples` must be a constant. eager Evaluate immediately and return a `Series`. If set to `False` (default), return an expression instead. .. warning:: This functionality is experimental. It may be changed at any point without it being considered a breaking change. Returns ------- Expr or Series Column of data type `List(dtype)`. See Also -------- linear_space : Generate a single sequence of linearly-spaced values. Examples -------- >>> df = pl.DataFrame({"start": [1, -1], "end": [3, 2], "num_samples": [4, 5]}) >>> df.with_columns(ls=pl.linear_spaces("start", "end", "num_samples")) shape: (2, 4) β”Œβ”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ start ┆ end ┆ num_samples ┆ ls β”‚ β”‚ --- ┆ --- ┆ --- ┆ --- β”‚ β”‚ i64 ┆ i64 ┆ i64 ┆ list[f64] β”‚ β•žβ•β•β•β•β•β•β•β•ͺ═════β•ͺ═════════════β•ͺ════════════════════════║ β”‚ 1 ┆ 3 ┆ 4 ┆ [1.0, 1.666667, … 3.0] β”‚ β”‚ -1 ┆ 2 ┆ 5 ┆ [-1.0, -0.25, … 2.0] β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ >>> df.with_columns(ls=pl.linear_spaces("start", "end", 3, as_array=True)) shape: (2, 4) β”Œβ”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ start ┆ end ┆ num_samples ┆ ls β”‚ β”‚ --- ┆ --- ┆ --- ┆ --- β”‚ β”‚ i64 ┆ i64 ┆ i64 ┆ array[f64, 3] β”‚ β•žβ•β•β•β•β•β•β•β•ͺ═════β•ͺ═════════════β•ͺ══════════════════║ β”‚ 1 ┆ 3 ┆ 4 ┆ [1.0, 2.0, 3.0] β”‚ β”‚ -1 ┆ 2 ┆ 5 ┆ [-1.0, 0.5, 2.0] β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ )rr r"r*r#r$r%)rrrrr'rr&s rr*r*ζs`€τF " %Σ (€Eά  Σ $€Cά'¨ Σ4€Kά ”sΧ(Ρ(¨°°[ΐ&Θ(ΣSΣ T€Fα ܏x‰x˜ΣΧ)Ρ)Σ+Π+ΰ €Mr) rϊ+NumericLiteral | TemporalLiteral | IntoExprrr.rϊint | IntoExprrr rϊLiteral[False]Ϊreturnr ) rr.rr.rr/rr rϊ Literal[True]r1r ) rr.rr.rr/rr rΪboolr1ϊ Expr | Series)rϊ1NumericLiteral | TemporalLiteral | IntoExprColumnrr5rϊint | IntoExprColumnrr r'r3rr0r1r )rr5rr5rr6rr r'r3rr2r1r )rr5rr5rr6rr r'r3rr3r1r4)Ϊ __future__rΪ contextlibΪtypingrrΪpolarsrr#Ϊpolars._utils.parserΪpolars._utils.unstablerΪpolars._utils.wrapr ΪsuppressΪ ImportErrorΪ polars.polarsr"r r r Ϊpolars._typingr rrrrrr*rrrϊrBs$πέ"γί*ε!έ5έ+έ(ΰ€ZΧΡ˜Σ%ρ έχ υαί#χυπ π !Ψρ Ψ 6πΰ 4ππ ππ π π π π ςσ ππ π !ρ Ψ 6πΰ 4ππ ππ π π π π ςσ ππ π !ρ Ψ 6πΰ 4ππ ππ π π π πςσ πρ ƒπ $Ψρ BΨ 6πBΰ 4πBπ πBπ π Bπ π BπςBσ πBπJ π !ΨΨρΨ <πΰ :ππ&ππ π π π π ππ ςσ ππ π !Ψρ Ψ <πΰ :ππ&ππ π π π π ππ ςσ ππ π !Ψρ Ψ <πΰ :ππ&ππ π π π π ππςσ ππ $ΨΨρKΨ <πKΰ :πKπ&πKπ π Kπ π Kπ πKπτKχw π ϊs ½D3Δ3D<