polars_core/series/implementations/
mod.rs1#![allow(unsafe_op_in_unsafe_fn)]
2#[cfg(feature = "dtype-array")]
3mod array;
4mod binary;
5mod binary_offset;
6mod boolean;
7#[cfg(feature = "dtype-categorical")]
8mod categorical;
9#[cfg(feature = "dtype-date")]
10mod date;
11#[cfg(feature = "dtype-datetime")]
12mod datetime;
13#[cfg(feature = "dtype-decimal")]
14mod decimal;
15#[cfg(feature = "dtype-duration")]
16mod duration;
17mod floats;
18mod list;
19pub(crate) mod null;
20#[cfg(feature = "object")]
21mod object;
22mod string;
23#[cfg(feature = "dtype-struct")]
24mod struct_;
25#[cfg(feature = "dtype-time")]
26mod time;
27
28use std::any::Any;
29use std::borrow::Cow;
30
31use polars_compute::rolling::QuantileMethod;
32use polars_utils::aliases::PlSeedableRandomStateQuality;
33
34use super::*;
35use crate::chunked_array::AsSinglePtr;
36use crate::chunked_array::comparison::*;
37use crate::chunked_array::ops::compare_inner::{
38 IntoTotalEqInner, IntoTotalOrdInner, TotalEqInner, TotalOrdInner,
39};
40
41pub(crate) struct SeriesWrap<T>(pub T);
43
44impl<T: PolarsDataType> From<ChunkedArray<T>> for SeriesWrap<ChunkedArray<T>> {
45 fn from(ca: ChunkedArray<T>) -> Self {
46 SeriesWrap(ca)
47 }
48}
49
50impl<T: PolarsDataType> Deref for SeriesWrap<ChunkedArray<T>> {
51 type Target = ChunkedArray<T>;
52
53 fn deref(&self) -> &Self::Target {
54 &self.0
55 }
56}
57
58unsafe impl<T: PolarsDataType + 'static> IntoSeries for ChunkedArray<T>
59where
60 SeriesWrap<ChunkedArray<T>>: SeriesTrait,
61{
62 fn into_series(self) -> Series
63 where
64 Self: Sized,
65 {
66 Series(Arc::new(SeriesWrap(self)))
67 }
68}
69
70macro_rules! impl_dyn_series {
71 ($ca: ident, $pdt:ty) => {
72 impl private::PrivateSeries for SeriesWrap<$ca> {
73 fn compute_len(&mut self) {
74 self.0.compute_len()
75 }
76
77 fn _field(&self) -> Cow<Field> {
78 Cow::Borrowed(self.0.ref_field())
79 }
80
81 fn _dtype(&self) -> &DataType {
82 self.0.ref_field().dtype()
83 }
84
85 fn _get_flags(&self) -> StatisticsFlags {
86 self.0.get_flags()
87 }
88
89 fn _set_flags(&mut self, flags: StatisticsFlags) {
90 self.0.set_flags(flags)
91 }
92
93 unsafe fn equal_element(
94 &self,
95 idx_self: usize,
96 idx_other: usize,
97 other: &Series,
98 ) -> bool {
99 self.0.equal_element(idx_self, idx_other, other)
100 }
101
102 #[cfg(feature = "zip_with")]
103 fn zip_with_same_type(
104 &self,
105 mask: &BooleanChunked,
106 other: &Series,
107 ) -> PolarsResult<Series> {
108 ChunkZip::zip_with(&self.0, mask, other.as_ref().as_ref())
109 .map(|ca| ca.into_series())
110 }
111 fn into_total_eq_inner<'a>(&'a self) -> Box<dyn TotalEqInner + 'a> {
112 (&self.0).into_total_eq_inner()
113 }
114 fn into_total_ord_inner<'a>(&'a self) -> Box<dyn TotalOrdInner + 'a> {
115 (&self.0).into_total_ord_inner()
116 }
117
118 fn vec_hash(
119 &self,
120 random_state: PlSeedableRandomStateQuality,
121 buf: &mut Vec<u64>,
122 ) -> PolarsResult<()> {
123 self.0.vec_hash(random_state, buf)?;
124 Ok(())
125 }
126
127 fn vec_hash_combine(
128 &self,
129 build_hasher: PlSeedableRandomStateQuality,
130 hashes: &mut [u64],
131 ) -> PolarsResult<()> {
132 self.0.vec_hash_combine(build_hasher, hashes)?;
133 Ok(())
134 }
135
136 #[cfg(feature = "algorithm_group_by")]
137 unsafe fn agg_min(&self, groups: &GroupsType) -> Series {
138 self.0.agg_min(groups)
139 }
140
141 #[cfg(feature = "algorithm_group_by")]
142 unsafe fn agg_max(&self, groups: &GroupsType) -> Series {
143 self.0.agg_max(groups)
144 }
145
146 #[cfg(feature = "algorithm_group_by")]
147 unsafe fn agg_sum(&self, groups: &GroupsType) -> Series {
148 use DataType::*;
149 match self.dtype() {
150 Int8 | UInt8 | Int16 | UInt16 => self
151 .cast(&Int64, CastOptions::Overflowing)
152 .unwrap()
153 .agg_sum(groups),
154 _ => self.0.agg_sum(groups),
155 }
156 }
157
158 #[cfg(feature = "algorithm_group_by")]
159 unsafe fn agg_std(&self, groups: &GroupsType, ddof: u8) -> Series {
160 self.0.agg_std(groups, ddof)
161 }
162
163 #[cfg(feature = "algorithm_group_by")]
164 unsafe fn agg_var(&self, groups: &GroupsType, ddof: u8) -> Series {
165 self.0.agg_var(groups, ddof)
166 }
167
168 #[cfg(feature = "algorithm_group_by")]
169 unsafe fn agg_list(&self, groups: &GroupsType) -> Series {
170 self.0.agg_list(groups)
171 }
172
173 #[cfg(feature = "bitwise")]
174 unsafe fn agg_and(&self, groups: &GroupsType) -> Series {
175 self.0.agg_and(groups)
176 }
177 #[cfg(feature = "bitwise")]
178 unsafe fn agg_or(&self, groups: &GroupsType) -> Series {
179 self.0.agg_or(groups)
180 }
181 #[cfg(feature = "bitwise")]
182 unsafe fn agg_xor(&self, groups: &GroupsType) -> Series {
183 self.0.agg_xor(groups)
184 }
185
186 fn subtract(&self, rhs: &Series) -> PolarsResult<Series> {
187 NumOpsDispatch::subtract(&self.0, rhs)
188 }
189 fn add_to(&self, rhs: &Series) -> PolarsResult<Series> {
190 NumOpsDispatch::add_to(&self.0, rhs)
191 }
192 fn multiply(&self, rhs: &Series) -> PolarsResult<Series> {
193 NumOpsDispatch::multiply(&self.0, rhs)
194 }
195 fn divide(&self, rhs: &Series) -> PolarsResult<Series> {
196 NumOpsDispatch::divide(&self.0, rhs)
197 }
198 fn remainder(&self, rhs: &Series) -> PolarsResult<Series> {
199 NumOpsDispatch::remainder(&self.0, rhs)
200 }
201 #[cfg(feature = "algorithm_group_by")]
202 fn group_tuples(&self, multithreaded: bool, sorted: bool) -> PolarsResult<GroupsType> {
203 IntoGroupsType::group_tuples(&self.0, multithreaded, sorted)
204 }
205
206 fn arg_sort_multiple(
207 &self,
208 by: &[Column],
209 options: &SortMultipleOptions,
210 ) -> PolarsResult<IdxCa> {
211 self.0.arg_sort_multiple(by, options)
212 }
213 }
214
215 impl SeriesTrait for SeriesWrap<$ca> {
216 #[cfg(feature = "rolling_window")]
217 fn rolling_map(
218 &self,
219 _f: &dyn Fn(&Series) -> Series,
220 _options: RollingOptionsFixedWindow,
221 ) -> PolarsResult<Series> {
222 ChunkRollApply::rolling_map(&self.0, _f, _options).map(|ca| ca.into_series())
223 }
224
225 fn rename(&mut self, name: PlSmallStr) {
226 self.0.rename(name);
227 }
228
229 fn chunk_lengths(&self) -> ChunkLenIter {
230 self.0.chunk_lengths()
231 }
232 fn name(&self) -> &PlSmallStr {
233 self.0.name()
234 }
235
236 fn chunks(&self) -> &Vec<ArrayRef> {
237 self.0.chunks()
238 }
239 unsafe fn chunks_mut(&mut self) -> &mut Vec<ArrayRef> {
240 self.0.chunks_mut()
241 }
242 fn shrink_to_fit(&mut self) {
243 self.0.shrink_to_fit()
244 }
245
246 fn slice(&self, offset: i64, length: usize) -> Series {
247 self.0.slice(offset, length).into_series()
248 }
249
250 fn split_at(&self, offset: i64) -> (Series, Series) {
251 let (a, b) = self.0.split_at(offset);
252 (a.into_series(), b.into_series())
253 }
254
255 fn append(&mut self, other: &Series) -> PolarsResult<()> {
256 polars_ensure!(self.0.dtype() == other.dtype(), append);
257 self.0.append(other.as_ref().as_ref())?;
258 Ok(())
259 }
260 fn append_owned(&mut self, other: Series) -> PolarsResult<()> {
261 polars_ensure!(self.0.dtype() == other.dtype(), append);
262 self.0.append_owned(other.take_inner())
263 }
264
265 fn extend(&mut self, other: &Series) -> PolarsResult<()> {
266 polars_ensure!(self.0.dtype() == other.dtype(), extend);
267 self.0.extend(other.as_ref().as_ref())?;
268 Ok(())
269 }
270
271 fn filter(&self, filter: &BooleanChunked) -> PolarsResult<Series> {
272 ChunkFilter::filter(&self.0, filter).map(|ca| ca.into_series())
273 }
274
275 fn _sum_as_f64(&self) -> f64 {
276 self.0._sum_as_f64()
277 }
278
279 fn mean(&self) -> Option<f64> {
280 self.0.mean()
281 }
282
283 fn median(&self) -> Option<f64> {
284 self.0.median()
285 }
286
287 fn std(&self, ddof: u8) -> Option<f64> {
288 self.0.std(ddof)
289 }
290
291 fn var(&self, ddof: u8) -> Option<f64> {
292 self.0.var(ddof)
293 }
294
295 fn take(&self, indices: &IdxCa) -> PolarsResult<Series> {
296 Ok(self.0.take(indices)?.into_series())
297 }
298
299 unsafe fn take_unchecked(&self, indices: &IdxCa) -> Series {
300 self.0.take_unchecked(indices).into_series()
301 }
302
303 fn take_slice(&self, indices: &[IdxSize]) -> PolarsResult<Series> {
304 Ok(self.0.take(indices)?.into_series())
305 }
306
307 unsafe fn take_slice_unchecked(&self, indices: &[IdxSize]) -> Series {
308 self.0.take_unchecked(indices).into_series()
309 }
310
311 fn len(&self) -> usize {
312 self.0.len()
313 }
314
315 fn rechunk(&self) -> Series {
316 self.0.rechunk().into_owned().into_series()
317 }
318
319 fn new_from_index(&self, index: usize, length: usize) -> Series {
320 ChunkExpandAtIndex::new_from_index(&self.0, index, length).into_series()
321 }
322
323 fn cast(&self, dtype: &DataType, options: CastOptions) -> PolarsResult<Series> {
324 self.0.cast_with_options(dtype, options)
325 }
326
327 #[inline]
328 unsafe fn get_unchecked(&self, index: usize) -> AnyValue {
329 self.0.get_any_value_unchecked(index)
330 }
331
332 fn sort_with(&self, options: SortOptions) -> PolarsResult<Series> {
333 Ok(ChunkSort::sort_with(&self.0, options).into_series())
334 }
335
336 fn arg_sort(&self, options: SortOptions) -> IdxCa {
337 ChunkSort::arg_sort(&self.0, options)
338 }
339
340 fn null_count(&self) -> usize {
341 self.0.null_count()
342 }
343
344 fn has_nulls(&self) -> bool {
345 self.0.has_nulls()
346 }
347
348 #[cfg(feature = "algorithm_group_by")]
349 fn unique(&self) -> PolarsResult<Series> {
350 ChunkUnique::unique(&self.0).map(|ca| ca.into_series())
351 }
352
353 #[cfg(feature = "algorithm_group_by")]
354 fn n_unique(&self) -> PolarsResult<usize> {
355 ChunkUnique::n_unique(&self.0)
356 }
357
358 #[cfg(feature = "algorithm_group_by")]
359 fn arg_unique(&self) -> PolarsResult<IdxCa> {
360 ChunkUnique::arg_unique(&self.0)
361 }
362
363 fn is_null(&self) -> BooleanChunked {
364 self.0.is_null()
365 }
366
367 fn is_not_null(&self) -> BooleanChunked {
368 self.0.is_not_null()
369 }
370
371 fn reverse(&self) -> Series {
372 ChunkReverse::reverse(&self.0).into_series()
373 }
374
375 fn as_single_ptr(&mut self) -> PolarsResult<usize> {
376 self.0.as_single_ptr()
377 }
378
379 fn shift(&self, periods: i64) -> Series {
380 ChunkShift::shift(&self.0, periods).into_series()
381 }
382
383 fn sum_reduce(&self) -> PolarsResult<Scalar> {
384 Ok(ChunkAggSeries::sum_reduce(&self.0))
385 }
386 fn max_reduce(&self) -> PolarsResult<Scalar> {
387 Ok(ChunkAggSeries::max_reduce(&self.0))
388 }
389 fn min_reduce(&self) -> PolarsResult<Scalar> {
390 Ok(ChunkAggSeries::min_reduce(&self.0))
391 }
392 fn median_reduce(&self) -> PolarsResult<Scalar> {
393 Ok(QuantileAggSeries::median_reduce(&self.0))
394 }
395 fn var_reduce(&self, ddof: u8) -> PolarsResult<Scalar> {
396 Ok(VarAggSeries::var_reduce(&self.0, ddof))
397 }
398 fn std_reduce(&self, ddof: u8) -> PolarsResult<Scalar> {
399 Ok(VarAggSeries::std_reduce(&self.0, ddof))
400 }
401 fn quantile_reduce(
402 &self,
403 quantile: f64,
404 method: QuantileMethod,
405 ) -> PolarsResult<Scalar> {
406 QuantileAggSeries::quantile_reduce(&self.0, quantile, method)
407 }
408
409 #[cfg(feature = "bitwise")]
410 fn and_reduce(&self) -> PolarsResult<Scalar> {
411 let dt = <$pdt as PolarsDataType>::get_dtype();
412 let av = self.0.and_reduce().map_or(AnyValue::Null, Into::into);
413
414 Ok(Scalar::new(dt, av))
415 }
416
417 #[cfg(feature = "bitwise")]
418 fn or_reduce(&self) -> PolarsResult<Scalar> {
419 let dt = <$pdt as PolarsDataType>::get_dtype();
420 let av = self.0.or_reduce().map_or(AnyValue::Null, Into::into);
421
422 Ok(Scalar::new(dt, av))
423 }
424
425 #[cfg(feature = "bitwise")]
426 fn xor_reduce(&self) -> PolarsResult<Scalar> {
427 let dt = <$pdt as PolarsDataType>::get_dtype();
428 let av = self.0.xor_reduce().map_or(AnyValue::Null, Into::into);
429
430 Ok(Scalar::new(dt, av))
431 }
432
433 #[cfg(feature = "approx_unique")]
434 fn approx_n_unique(&self) -> PolarsResult<IdxSize> {
435 Ok(ChunkApproxNUnique::approx_n_unique(&self.0))
436 }
437
438 fn clone_inner(&self) -> Arc<dyn SeriesTrait> {
439 Arc::new(SeriesWrap(Clone::clone(&self.0)))
440 }
441
442 #[cfg(feature = "checked_arithmetic")]
443 fn checked_div(&self, rhs: &Series) -> PolarsResult<Series> {
444 self.0.checked_div(rhs)
445 }
446
447 fn as_any(&self) -> &dyn Any {
448 &self.0
449 }
450
451 fn as_any_mut(&mut self) -> &mut dyn Any {
452 &mut self.0
453 }
454
455 fn as_phys_any(&self) -> &dyn Any {
456 &self.0
457 }
458
459 fn as_arc_any(self: Arc<Self>) -> Arc<dyn Any + Send + Sync> {
460 self as _
461 }
462 }
463 };
464}
465
466#[cfg(feature = "dtype-u8")]
467impl_dyn_series!(UInt8Chunked, UInt8Type);
468#[cfg(feature = "dtype-u16")]
469impl_dyn_series!(UInt16Chunked, UInt16Type);
470impl_dyn_series!(UInt32Chunked, UInt32Type);
471impl_dyn_series!(UInt64Chunked, UInt64Type);
472#[cfg(feature = "dtype-i8")]
473impl_dyn_series!(Int8Chunked, Int8Type);
474#[cfg(feature = "dtype-i16")]
475impl_dyn_series!(Int16Chunked, Int16Type);
476impl_dyn_series!(Int32Chunked, Int32Type);
477impl_dyn_series!(Int64Chunked, Int64Type);
478#[cfg(feature = "dtype-i128")]
479impl_dyn_series!(Int128Chunked, Int128Type);
480
481impl<T: PolarsNumericType> private::PrivateSeriesNumeric for SeriesWrap<ChunkedArray<T>> {
482 fn bit_repr(&self) -> Option<BitRepr> {
483 Some(self.0.to_bit_repr())
484 }
485}
486
487impl private::PrivateSeriesNumeric for SeriesWrap<StringChunked> {
488 fn bit_repr(&self) -> Option<BitRepr> {
489 None
490 }
491}
492impl private::PrivateSeriesNumeric for SeriesWrap<BinaryChunked> {
493 fn bit_repr(&self) -> Option<BitRepr> {
494 None
495 }
496}
497impl private::PrivateSeriesNumeric for SeriesWrap<BinaryOffsetChunked> {
498 fn bit_repr(&self) -> Option<BitRepr> {
499 None
500 }
501}
502impl private::PrivateSeriesNumeric for SeriesWrap<ListChunked> {
503 fn bit_repr(&self) -> Option<BitRepr> {
504 None
505 }
506}
507#[cfg(feature = "dtype-array")]
508impl private::PrivateSeriesNumeric for SeriesWrap<ArrayChunked> {
509 fn bit_repr(&self) -> Option<BitRepr> {
510 None
511 }
512}
513impl private::PrivateSeriesNumeric for SeriesWrap<BooleanChunked> {
514 fn bit_repr(&self) -> Option<BitRepr> {
515 let repr = self
516 .0
517 .cast_with_options(&DataType::UInt32, CastOptions::NonStrict)
518 .unwrap()
519 .u32()
520 .unwrap()
521 .clone();
522
523 Some(BitRepr::Small(repr))
524 }
525}