use std::ops::Neg;
use polars::lazy::dsl;
use polars::prelude::*;
use polars::series::ops::NullBehavior;
use polars_core::chunked_array::cast::CastOptions;
use polars_core::series::IsSorted;
use pyo3::class::basic::CompareOp;
use pyo3::prelude::*;
use crate::conversion::{parse_fill_null_strategy, vec_extract_wrapped, Wrap};
use crate::error::PyPolarsErr;
use crate::map::lazy::map_single;
use crate::PyExpr;
#[pymethods]
impl PyExpr {
fn __richcmp__(&self, other: Self, op: CompareOp) -> Self {
match op {
CompareOp::Eq => self.eq(other),
CompareOp::Ne => self.neq(other),
CompareOp::Gt => self.gt(other),
CompareOp::Lt => self.lt(other),
CompareOp::Ge => self.gt_eq(other),
CompareOp::Le => self.lt_eq(other),
}
}
fn __add__(&self, rhs: Self) -> PyResult<Self> {
Ok(dsl::binary_expr(self.inner.clone(), Operator::Plus, rhs.inner).into())
}
fn __sub__(&self, rhs: Self) -> PyResult<Self> {
Ok(dsl::binary_expr(self.inner.clone(), Operator::Minus, rhs.inner).into())
}
fn __mul__(&self, rhs: Self) -> PyResult<Self> {
Ok(dsl::binary_expr(self.inner.clone(), Operator::Multiply, rhs.inner).into())
}
fn __truediv__(&self, rhs: Self) -> PyResult<Self> {
Ok(dsl::binary_expr(self.inner.clone(), Operator::TrueDivide, rhs.inner).into())
}
fn __mod__(&self, rhs: Self) -> PyResult<Self> {
Ok(dsl::binary_expr(self.inner.clone(), Operator::Modulus, rhs.inner).into())
}
fn __floordiv__(&self, rhs: Self) -> PyResult<Self> {
Ok(dsl::binary_expr(self.inner.clone(), Operator::FloorDivide, rhs.inner).into())
}
fn __neg__(&self) -> PyResult<Self> {
Ok(self.inner.clone().neg().into())
}
fn to_str(&self) -> String {
format!("{:?}", self.inner)
}
fn eq(&self, other: Self) -> Self {
self.inner.clone().eq(other.inner).into()
}
fn eq_missing(&self, other: Self) -> Self {
self.inner.clone().eq_missing(other.inner).into()
}
fn neq(&self, other: Self) -> Self {
self.inner.clone().neq(other.inner).into()
}
fn neq_missing(&self, other: Self) -> Self {
self.inner.clone().neq_missing(other.inner).into()
}
fn gt(&self, other: Self) -> Self {
self.inner.clone().gt(other.inner).into()
}
fn gt_eq(&self, other: Self) -> Self {
self.inner.clone().gt_eq(other.inner).into()
}
fn lt_eq(&self, other: Self) -> Self {
self.inner.clone().lt_eq(other.inner).into()
}
fn lt(&self, other: Self) -> Self {
self.inner.clone().lt(other.inner).into()
}
fn alias(&self, name: &str) -> Self {
self.inner.clone().alias(name).into()
}
fn not_(&self) -> Self {
self.inner.clone().not().into()
}
fn is_null(&self) -> Self {
self.inner.clone().is_null().into()
}
fn is_not_null(&self) -> Self {
self.inner.clone().is_not_null().into()
}
fn is_infinite(&self) -> Self {
self.inner.clone().is_infinite().into()
}
fn is_finite(&self) -> Self {
self.inner.clone().is_finite().into()
}
fn is_nan(&self) -> Self {
self.inner.clone().is_nan().into()
}
fn is_not_nan(&self) -> Self {
self.inner.clone().is_not_nan().into()
}
fn min(&self) -> Self {
self.inner.clone().min().into()
}
fn max(&self) -> Self {
self.inner.clone().max().into()
}
#[cfg(feature = "propagate_nans")]
fn nan_max(&self) -> Self {
self.inner.clone().nan_max().into()
}
#[cfg(feature = "propagate_nans")]
fn nan_min(&self) -> Self {
self.inner.clone().nan_min().into()
}
fn mean(&self) -> Self {
self.inner.clone().mean().into()
}
fn median(&self) -> Self {
self.inner.clone().median().into()
}
fn sum(&self) -> Self {
self.inner.clone().sum().into()
}
fn n_unique(&self) -> Self {
self.inner.clone().n_unique().into()
}
fn arg_unique(&self) -> Self {
self.inner.clone().arg_unique().into()
}
fn unique(&self) -> Self {
self.inner.clone().unique().into()
}
fn unique_stable(&self) -> Self {
self.inner.clone().unique_stable().into()
}
fn first(&self) -> Self {
self.inner.clone().first().into()
}
fn last(&self) -> Self {
self.inner.clone().last().into()
}
fn implode(&self) -> Self {
self.inner.clone().implode().into()
}
fn quantile(&self, quantile: Self, interpolation: Wrap<QuantileMethod>) -> Self {
self.inner
.clone()
.quantile(quantile.inner, interpolation.0)
.into()
}
#[pyo3(signature = (breaks, labels, left_closed, include_breaks))]
#[cfg(feature = "cutqcut")]
fn cut(
&self,
breaks: Vec<f64>,
labels: Option<Vec<String>>,
left_closed: bool,
include_breaks: bool,
) -> Self {
self.inner
.clone()
.cut(breaks, labels, left_closed, include_breaks)
.into()
}
#[pyo3(signature = (probs, labels, left_closed, allow_duplicates, include_breaks))]
#[cfg(feature = "cutqcut")]
fn qcut(
&self,
probs: Vec<f64>,
labels: Option<Vec<String>>,
left_closed: bool,
allow_duplicates: bool,
include_breaks: bool,
) -> Self {
self.inner
.clone()
.qcut(probs, labels, left_closed, allow_duplicates, include_breaks)
.into()
}
#[pyo3(signature = (n_bins, labels, left_closed, allow_duplicates, include_breaks))]
#[cfg(feature = "cutqcut")]
fn qcut_uniform(
&self,
n_bins: usize,
labels: Option<Vec<String>>,
left_closed: bool,
allow_duplicates: bool,
include_breaks: bool,
) -> Self {
self.inner
.clone()
.qcut_uniform(
n_bins,
labels,
left_closed,
allow_duplicates,
include_breaks,
)
.into()
}
#[cfg(feature = "rle")]
fn rle(&self) -> Self {
self.inner.clone().rle().into()
}
#[cfg(feature = "rle")]
fn rle_id(&self) -> Self {
self.inner.clone().rle_id().into()
}
fn agg_groups(&self) -> Self {
self.inner.clone().agg_groups().into()
}
fn count(&self) -> Self {
self.inner.clone().count().into()
}
fn len(&self) -> Self {
self.inner.clone().len().into()
}
fn value_counts(&self, sort: bool, parallel: bool, name: String, normalize: bool) -> Self {
self.inner
.clone()
.value_counts(sort, parallel, name.as_str(), normalize)
.into()
}
fn unique_counts(&self) -> Self {
self.inner.clone().unique_counts().into()
}
fn null_count(&self) -> Self {
self.inner.clone().null_count().into()
}
fn cast(&self, dtype: Wrap<DataType>, strict: bool, wrap_numerical: bool) -> Self {
let dt = dtype.0;
let options = if wrap_numerical {
CastOptions::Overflowing
} else if strict {
CastOptions::Strict
} else {
CastOptions::NonStrict
};
let expr = self.inner.clone().cast_with_options(dt, options);
expr.into()
}
fn sort_with(&self, descending: bool, nulls_last: bool) -> Self {
self.inner
.clone()
.sort(SortOptions {
descending,
nulls_last,
multithreaded: true,
maintain_order: false,
limit: None,
})
.into()
}
fn arg_sort(&self, descending: bool, nulls_last: bool) -> Self {
self.inner
.clone()
.arg_sort(SortOptions {
descending,
nulls_last,
multithreaded: true,
maintain_order: false,
limit: None,
})
.into()
}
#[cfg(feature = "top_k")]
fn top_k(&self, k: Self) -> Self {
self.inner.clone().top_k(k.inner).into()
}
#[cfg(feature = "top_k")]
fn top_k_by(&self, by: Vec<Self>, k: Self, reverse: Vec<bool>) -> Self {
let by = by.into_iter().map(|e| e.inner).collect::<Vec<_>>();
self.inner.clone().top_k_by(k.inner, by, reverse).into()
}
#[cfg(feature = "top_k")]
fn bottom_k(&self, k: Self) -> Self {
self.inner.clone().bottom_k(k.inner).into()
}
#[cfg(feature = "top_k")]
fn bottom_k_by(&self, by: Vec<Self>, k: Self, reverse: Vec<bool>) -> Self {
let by = by.into_iter().map(|e| e.inner).collect::<Vec<_>>();
self.inner.clone().bottom_k_by(k.inner, by, reverse).into()
}
#[cfg(feature = "peaks")]
fn peak_min(&self) -> Self {
self.inner.clone().peak_min().into()
}
#[cfg(feature = "peaks")]
fn peak_max(&self) -> Self {
self.inner.clone().peak_max().into()
}
fn arg_max(&self) -> Self {
self.inner.clone().arg_max().into()
}
fn arg_min(&self) -> Self {
self.inner.clone().arg_min().into()
}
#[cfg(feature = "index_of")]
fn index_of(&self, element: Self) -> Self {
self.inner.clone().index_of(element.inner).into()
}
#[cfg(feature = "search_sorted")]
fn search_sorted(&self, element: Self, side: Wrap<SearchSortedSide>) -> Self {
self.inner
.clone()
.search_sorted(element.inner, side.0)
.into()
}
fn gather(&self, idx: Self) -> Self {
self.inner.clone().gather(idx.inner).into()
}
fn get(&self, idx: Self) -> Self {
self.inner.clone().get(idx.inner).into()
}
fn sort_by(
&self,
by: Vec<Self>,
descending: Vec<bool>,
nulls_last: Vec<bool>,
multithreaded: bool,
maintain_order: bool,
) -> Self {
let by = by.into_iter().map(|e| e.inner).collect::<Vec<_>>();
self.inner
.clone()
.sort_by(
by,
SortMultipleOptions {
descending,
nulls_last,
multithreaded,
maintain_order,
limit: None,
},
)
.into()
}
fn backward_fill(&self, limit: FillNullLimit) -> Self {
self.inner.clone().backward_fill(limit).into()
}
fn forward_fill(&self, limit: FillNullLimit) -> Self {
self.inner.clone().forward_fill(limit).into()
}
#[pyo3(signature = (n, fill_value=None))]
fn shift(&self, n: Self, fill_value: Option<Self>) -> Self {
let expr = self.inner.clone();
let out = match fill_value {
Some(v) => expr.shift_and_fill(n.inner, v.inner),
None => expr.shift(n.inner),
};
out.into()
}
fn fill_null(&self, expr: Self) -> Self {
self.inner.clone().fill_null(expr.inner).into()
}
fn fill_null_with_strategy(&self, strategy: &str, limit: FillNullLimit) -> PyResult<Self> {
let strategy = parse_fill_null_strategy(strategy, limit)?;
Ok(self.inner.clone().fill_null_with_strategy(strategy).into())
}
fn fill_nan(&self, expr: Self) -> Self {
self.inner.clone().fill_nan(expr.inner).into()
}
fn drop_nulls(&self) -> Self {
self.inner.clone().drop_nulls().into()
}
fn drop_nans(&self) -> Self {
self.inner.clone().drop_nans().into()
}
fn filter(&self, predicate: Self) -> Self {
self.inner.clone().filter(predicate.inner).into()
}
fn reverse(&self) -> Self {
self.inner.clone().reverse().into()
}
fn std(&self, ddof: u8) -> Self {
self.inner.clone().std(ddof).into()
}
fn var(&self, ddof: u8) -> Self {
self.inner.clone().var(ddof).into()
}
fn is_unique(&self) -> Self {
self.inner.clone().is_unique().into()
}
fn is_between(&self, lower: Self, upper: Self, closed: Wrap<ClosedInterval>) -> Self {
self.inner
.clone()
.is_between(lower.inner, upper.inner, closed.0)
.into()
}
#[cfg(feature = "approx_unique")]
fn approx_n_unique(&self) -> Self {
self.inner.clone().approx_n_unique().into()
}
fn is_first_distinct(&self) -> Self {
self.inner.clone().is_first_distinct().into()
}
fn is_last_distinct(&self) -> Self {
self.inner.clone().is_last_distinct().into()
}
fn explode(&self) -> Self {
self.inner.clone().explode().into()
}
fn gather_every(&self, n: usize, offset: usize) -> Self {
self.inner.clone().gather_every(n, offset).into()
}
fn slice(&self, offset: Self, length: Self) -> Self {
self.inner.clone().slice(offset.inner, length.inner).into()
}
fn append(&self, other: Self, upcast: bool) -> Self {
self.inner.clone().append(other.inner, upcast).into()
}
fn rechunk(&self) -> Self {
self.inner
.clone()
.map(|s| Ok(Some(s.rechunk())), GetOutput::same_type())
.into()
}
fn round(&self, decimals: u32) -> Self {
self.inner.clone().round(decimals).into()
}
fn round_sig_figs(&self, digits: i32) -> Self {
self.clone().inner.round_sig_figs(digits).into()
}
fn floor(&self) -> Self {
self.inner.clone().floor().into()
}
fn ceil(&self) -> Self {
self.inner.clone().ceil().into()
}
#[pyo3(signature = (min=None, max=None))]
fn clip(&self, min: Option<Self>, max: Option<Self>) -> Self {
let expr = self.inner.clone();
let out = match (min, max) {
(Some(min), Some(max)) => expr.clip(min.inner, max.inner),
(Some(min), None) => expr.clip_min(min.inner),
(None, Some(max)) => expr.clip_max(max.inner),
(None, None) => expr,
};
out.into()
}
fn abs(&self) -> Self {
self.inner.clone().abs().into()
}
#[cfg(feature = "trigonometry")]
fn sin(&self) -> Self {
self.inner.clone().sin().into()
}
#[cfg(feature = "trigonometry")]
fn cos(&self) -> Self {
self.inner.clone().cos().into()
}
#[cfg(feature = "trigonometry")]
fn tan(&self) -> Self {
self.inner.clone().tan().into()
}
#[cfg(feature = "trigonometry")]
fn cot(&self) -> Self {
self.inner.clone().cot().into()
}
#[cfg(feature = "trigonometry")]
fn arcsin(&self) -> Self {
self.inner.clone().arcsin().into()
}
#[cfg(feature = "trigonometry")]
fn arccos(&self) -> Self {
self.inner.clone().arccos().into()
}
#[cfg(feature = "trigonometry")]
fn arctan(&self) -> Self {
self.inner.clone().arctan().into()
}
#[cfg(feature = "trigonometry")]
fn arctan2(&self, y: Self) -> Self {
self.inner.clone().arctan2(y.inner).into()
}
#[cfg(feature = "trigonometry")]
fn sinh(&self) -> Self {
self.inner.clone().sinh().into()
}
#[cfg(feature = "trigonometry")]
fn cosh(&self) -> Self {
self.inner.clone().cosh().into()
}
#[cfg(feature = "trigonometry")]
fn tanh(&self) -> Self {
self.inner.clone().tanh().into()
}
#[cfg(feature = "trigonometry")]
fn arcsinh(&self) -> Self {
self.inner.clone().arcsinh().into()
}
#[cfg(feature = "trigonometry")]
fn arccosh(&self) -> Self {
self.inner.clone().arccosh().into()
}
#[cfg(feature = "trigonometry")]
fn arctanh(&self) -> Self {
self.inner.clone().arctanh().into()
}
#[cfg(feature = "trigonometry")]
pub fn degrees(&self) -> Self {
self.inner.clone().degrees().into()
}
#[cfg(feature = "trigonometry")]
pub fn radians(&self) -> Self {
self.inner.clone().radians().into()
}
#[cfg(feature = "sign")]
fn sign(&self) -> Self {
self.inner.clone().sign().into()
}
fn is_duplicated(&self) -> Self {
self.inner.clone().is_duplicated().into()
}
#[pyo3(signature = (partition_by, order_by, order_by_descending, order_by_nulls_last, mapping_strategy))]
fn over(
&self,
partition_by: Vec<Self>,
order_by: Option<Vec<Self>>,
order_by_descending: bool,
order_by_nulls_last: bool,
mapping_strategy: Wrap<WindowMapping>,
) -> Self {
let partition_by = partition_by
.into_iter()
.map(|e| e.inner)
.collect::<Vec<Expr>>();
let order_by = order_by.map(|order_by| {
(
order_by.into_iter().map(|e| e.inner).collect::<Vec<Expr>>(),
SortOptions {
descending: order_by_descending,
nulls_last: order_by_nulls_last,
maintain_order: false,
..Default::default()
},
)
});
self.inner
.clone()
.over_with_options(partition_by, order_by, mapping_strategy.0)
.into()
}
fn rolling(
&self,
index_column: &str,
period: &str,
offset: &str,
closed: Wrap<ClosedWindow>,
) -> PyResult<Self> {
let options = RollingGroupOptions {
index_column: index_column.into(),
period: Duration::try_parse(period).map_err(PyPolarsErr::from)?,
offset: Duration::try_parse(offset).map_err(PyPolarsErr::from)?,
closed_window: closed.0,
};
Ok(self.inner.clone().rolling(options).into())
}
fn and_(&self, expr: Self) -> Self {
self.inner.clone().and(expr.inner).into()
}
fn or_(&self, expr: Self) -> Self {
self.inner.clone().or(expr.inner).into()
}
fn xor_(&self, expr: Self) -> Self {
self.inner.clone().xor(expr.inner).into()
}
#[cfg(feature = "is_in")]
fn is_in(&self, expr: Self) -> Self {
self.inner.clone().is_in(expr.inner).into()
}
#[cfg(feature = "repeat_by")]
fn repeat_by(&self, by: Self) -> Self {
self.inner.clone().repeat_by(by.inner).into()
}
fn pow(&self, exponent: Self) -> Self {
self.inner.clone().pow(exponent.inner).into()
}
fn sqrt(&self) -> Self {
self.inner.clone().sqrt().into()
}
fn cbrt(&self) -> Self {
self.inner.clone().cbrt().into()
}
fn cum_sum(&self, reverse: bool) -> Self {
self.inner.clone().cum_sum(reverse).into()
}
fn cum_max(&self, reverse: bool) -> Self {
self.inner.clone().cum_max(reverse).into()
}
fn cum_min(&self, reverse: bool) -> Self {
self.inner.clone().cum_min(reverse).into()
}
fn cum_prod(&self, reverse: bool) -> Self {
self.inner.clone().cum_prod(reverse).into()
}
fn cum_count(&self, reverse: bool) -> Self {
self.inner.clone().cum_count(reverse).into()
}
fn cumulative_eval(&self, expr: Self, min_periods: usize, parallel: bool) -> Self {
self.inner
.clone()
.cumulative_eval(expr.inner, min_periods, parallel)
.into()
}
fn product(&self) -> Self {
self.inner.clone().product().into()
}
fn shrink_dtype(&self) -> Self {
self.inner.clone().shrink_dtype().into()
}
#[pyo3(signature = (lambda, output_type, agg_list, is_elementwise, returns_scalar))]
fn map_batches(
&self,
lambda: PyObject,
output_type: Option<Wrap<DataType>>,
agg_list: bool,
is_elementwise: bool,
returns_scalar: bool,
) -> Self {
map_single(
self,
lambda,
output_type,
agg_list,
is_elementwise,
returns_scalar,
)
}
fn dot(&self, other: Self) -> Self {
self.inner.clone().dot(other.inner).into()
}
fn reinterpret(&self, signed: bool) -> Self {
self.inner.clone().reinterpret(signed).into()
}
fn mode(&self) -> Self {
self.inner.clone().mode().into()
}
fn exclude(&self, columns: Vec<String>) -> Self {
self.inner.clone().exclude(columns).into()
}
fn exclude_dtype(&self, dtypes: Vec<Wrap<DataType>>) -> Self {
let dtypes = vec_extract_wrapped(dtypes);
self.inner.clone().exclude_dtype(&dtypes).into()
}
fn interpolate(&self, method: Wrap<InterpolationMethod>) -> Self {
self.inner.clone().interpolate(method.0).into()
}
fn interpolate_by(&self, by: PyExpr) -> Self {
self.inner.clone().interpolate_by(by.inner).into()
}
fn lower_bound(&self) -> Self {
self.inner.clone().lower_bound().into()
}
fn upper_bound(&self) -> Self {
self.inner.clone().upper_bound().into()
}
#[pyo3(signature = (method, descending, seed=None))]
fn rank(&self, method: Wrap<RankMethod>, descending: bool, seed: Option<u64>) -> Self {
let options = RankOptions {
method: method.0,
descending,
};
self.inner.clone().rank(options, seed).into()
}
fn diff(&self, n: i64, null_behavior: Wrap<NullBehavior>) -> Self {
self.inner.clone().diff(n, null_behavior.0).into()
}
#[cfg(feature = "pct_change")]
fn pct_change(&self, n: Self) -> Self {
self.inner.clone().pct_change(n.inner).into()
}
fn skew(&self, bias: bool) -> Self {
self.inner.clone().skew(bias).into()
}
fn kurtosis(&self, fisher: bool, bias: bool) -> Self {
self.inner.clone().kurtosis(fisher, bias).into()
}
#[cfg(feature = "dtype-array")]
fn reshape(&self, dims: Vec<i64>) -> Self {
self.inner.clone().reshape(&dims).into()
}
fn to_physical(&self) -> Self {
self.inner.clone().to_physical().into()
}
#[pyo3(signature = (seed))]
fn shuffle(&self, seed: Option<u64>) -> Self {
self.inner.clone().shuffle(seed).into()
}
#[pyo3(signature = (n, with_replacement, shuffle, seed))]
fn sample_n(&self, n: Self, with_replacement: bool, shuffle: bool, seed: Option<u64>) -> Self {
self.inner
.clone()
.sample_n(n.inner, with_replacement, shuffle, seed)
.into()
}
#[pyo3(signature = (frac, with_replacement, shuffle, seed))]
fn sample_frac(
&self,
frac: Self,
with_replacement: bool,
shuffle: bool,
seed: Option<u64>,
) -> Self {
self.inner
.clone()
.sample_frac(frac.inner, with_replacement, shuffle, seed)
.into()
}
fn ewm_mean(&self, alpha: f64, adjust: bool, min_periods: usize, ignore_nulls: bool) -> Self {
let options = EWMOptions {
alpha,
adjust,
bias: false,
min_periods,
ignore_nulls,
};
self.inner.clone().ewm_mean(options).into()
}
fn ewm_mean_by(&self, times: PyExpr, half_life: &str) -> PyResult<Self> {
let half_life = Duration::try_parse(half_life).map_err(PyPolarsErr::from)?;
Ok(self
.inner
.clone()
.ewm_mean_by(times.inner, half_life)
.into())
}
fn ewm_std(
&self,
alpha: f64,
adjust: bool,
bias: bool,
min_periods: usize,
ignore_nulls: bool,
) -> Self {
let options = EWMOptions {
alpha,
adjust,
bias,
min_periods,
ignore_nulls,
};
self.inner.clone().ewm_std(options).into()
}
fn ewm_var(
&self,
alpha: f64,
adjust: bool,
bias: bool,
min_periods: usize,
ignore_nulls: bool,
) -> Self {
let options = EWMOptions {
alpha,
adjust,
bias,
min_periods,
ignore_nulls,
};
self.inner.clone().ewm_var(options).into()
}
fn extend_constant(&self, value: PyExpr, n: PyExpr) -> Self {
self.inner
.clone()
.extend_constant(value.inner, n.inner)
.into()
}
fn any(&self, ignore_nulls: bool) -> Self {
self.inner.clone().any(ignore_nulls).into()
}
fn all(&self, ignore_nulls: bool) -> Self {
self.inner.clone().all(ignore_nulls).into()
}
fn log(&self, base: f64) -> Self {
self.inner.clone().log(base).into()
}
fn log1p(&self) -> Self {
self.inner.clone().log1p().into()
}
fn exp(&self) -> Self {
self.inner.clone().exp().into()
}
fn entropy(&self, base: f64, normalize: bool) -> Self {
self.inner.clone().entropy(base, normalize).into()
}
fn hash(&self, seed: u64, seed_1: u64, seed_2: u64, seed_3: u64) -> Self {
self.inner.clone().hash(seed, seed_1, seed_2, seed_3).into()
}
fn set_sorted_flag(&self, descending: bool) -> Self {
let is_sorted = if descending {
IsSorted::Descending
} else {
IsSorted::Ascending
};
self.inner.clone().set_sorted_flag(is_sorted).into()
}
fn replace(&self, old: PyExpr, new: PyExpr) -> Self {
self.inner.clone().replace(old.inner, new.inner).into()
}
#[pyo3(signature = (old, new, default=None, return_dtype=None))]
fn replace_strict(
&self,
old: PyExpr,
new: PyExpr,
default: Option<PyExpr>,
return_dtype: Option<Wrap<DataType>>,
) -> Self {
self.inner
.clone()
.replace_strict(
old.inner,
new.inner,
default.map(|e| e.inner),
return_dtype.map(|dt| dt.0),
)
.into()
}
#[cfg(feature = "hist")]
#[pyo3(signature = (bins, bin_count, include_category, include_breakpoint))]
fn hist(
&self,
bins: Option<PyExpr>,
bin_count: Option<usize>,
include_category: bool,
include_breakpoint: bool,
) -> Self {
let bins = bins.map(|e| e.inner);
self.inner
.clone()
.hist(bins, bin_count, include_category, include_breakpoint)
.into()
}
}