polars_core/series/implementations/
decimal.rs1use polars_compute::rolling::QuantileMethod;
2
3use super::*;
4use crate::prelude::*;
5
6unsafe impl IntoSeries for DecimalChunked {
7 fn into_series(self) -> Series {
8 Series(Arc::new(SeriesWrap(self)))
9 }
10}
11
12impl private::PrivateSeriesNumeric for SeriesWrap<DecimalChunked> {
13 fn bit_repr(&self) -> Option<BitRepr> {
14 None
15 }
16}
17
18impl SeriesWrap<DecimalChunked> {
19 fn apply_physical_to_s<F: Fn(&Int128Chunked) -> Int128Chunked>(&self, f: F) -> Series {
20 f(&self.0)
21 .into_decimal_unchecked(self.0.precision(), self.0.scale())
22 .into_series()
23 }
24
25 fn apply_physical<T, F: Fn(&Int128Chunked) -> T>(&self, f: F) -> T {
26 f(&self.0)
27 }
28
29 fn scale_factor(&self) -> u128 {
30 10u128.pow(self.0.scale() as u32)
31 }
32
33 fn apply_scale(&self, mut scalar: Scalar) -> Scalar {
34 if scalar.is_null() {
35 return scalar;
36 }
37
38 debug_assert_eq!(scalar.dtype(), &DataType::Float64);
39 let v = scalar
40 .value()
41 .try_extract::<f64>()
42 .expect("should be f64 scalar");
43 scalar.update((v / self.scale_factor() as f64).into());
44 scalar
45 }
46
47 fn agg_helper<F: Fn(&Int128Chunked) -> Series>(&self, f: F) -> Series {
48 let agg_s = f(&self.0);
49 match agg_s.dtype() {
50 DataType::Int128 => {
51 let ca = agg_s.i128().unwrap();
52 let ca = ca.as_ref().clone();
53 let precision = self.0.precision();
54 let scale = self.0.scale();
55 ca.into_decimal_unchecked(precision, scale).into_series()
56 },
57 DataType::List(dtype) if matches!(dtype.as_ref(), DataType::Int128) => {
58 let dtype = self.0.dtype();
59 let ca = agg_s.list().unwrap();
60 let arr = ca.downcast_iter().next().unwrap();
61 let precision = self.0.precision();
63 let scale = self.0.scale();
64 let s = unsafe {
65 Series::from_chunks_and_dtype_unchecked(
66 PlSmallStr::EMPTY,
67 vec![arr.values().clone()],
68 dtype,
69 )
70 }
71 .into_decimal(precision, scale)
72 .unwrap();
73 let new_values = s.array_ref(0).clone();
74 let dtype = DataType::Int128;
75 let arrow_dtype =
76 ListArray::<i64>::default_datatype(dtype.to_arrow(CompatLevel::newest()));
77 let new_arr = ListArray::<i64>::new(
78 arrow_dtype,
79 arr.offsets().clone(),
80 new_values,
81 arr.validity().cloned(),
82 );
83 unsafe {
84 ListChunked::from_chunks_and_dtype_unchecked(
85 agg_s.name().clone(),
86 vec![Box::new(new_arr)],
87 DataType::List(Box::new(DataType::Decimal(precision, Some(scale)))),
88 )
89 .into_series()
90 }
91 },
92 _ => unreachable!(),
93 }
94 }
95}
96
97impl private::PrivateSeries for SeriesWrap<DecimalChunked> {
98 fn compute_len(&mut self) {
99 self.0.compute_len()
100 }
101
102 fn _field(&self) -> Cow<Field> {
103 Cow::Owned(self.0.field())
104 }
105
106 fn _dtype(&self) -> &DataType {
107 self.0.dtype()
108 }
109 fn _get_flags(&self) -> StatisticsFlags {
110 self.0.get_flags()
111 }
112 fn _set_flags(&mut self, flags: StatisticsFlags) {
113 self.0.set_flags(flags)
114 }
115
116 #[cfg(feature = "zip_with")]
117 fn zip_with_same_type(&self, mask: &BooleanChunked, other: &Series) -> PolarsResult<Series> {
118 let other = other.decimal()?;
119
120 Ok(self
121 .0
122 .physical()
123 .zip_with(mask, other.physical())?
124 .into_decimal_unchecked(self.0.precision(), self.0.scale())
125 .into_series())
126 }
127 fn into_total_eq_inner<'a>(&'a self) -> Box<dyn TotalEqInner + 'a> {
128 (&self.0).into_total_eq_inner()
129 }
130 fn into_total_ord_inner<'a>(&'a self) -> Box<dyn TotalOrdInner + 'a> {
131 (&self.0).into_total_ord_inner()
132 }
133
134 fn vec_hash(
135 &self,
136 random_state: PlSeedableRandomStateQuality,
137 buf: &mut Vec<u64>,
138 ) -> PolarsResult<()> {
139 self.0.vec_hash(random_state, buf)?;
140 Ok(())
141 }
142
143 fn vec_hash_combine(
144 &self,
145 build_hasher: PlSeedableRandomStateQuality,
146 hashes: &mut [u64],
147 ) -> PolarsResult<()> {
148 self.0.vec_hash_combine(build_hasher, hashes)?;
149 Ok(())
150 }
151
152 #[cfg(feature = "algorithm_group_by")]
153 unsafe fn agg_sum(&self, groups: &GroupsType) -> Series {
154 self.agg_helper(|ca| ca.agg_sum(groups))
155 }
156
157 #[cfg(feature = "algorithm_group_by")]
158 unsafe fn agg_min(&self, groups: &GroupsType) -> Series {
159 self.agg_helper(|ca| ca.agg_min(groups))
160 }
161
162 #[cfg(feature = "algorithm_group_by")]
163 unsafe fn agg_max(&self, groups: &GroupsType) -> Series {
164 self.agg_helper(|ca| ca.agg_max(groups))
165 }
166
167 #[cfg(feature = "algorithm_group_by")]
168 unsafe fn agg_list(&self, groups: &GroupsType) -> Series {
169 self.agg_helper(|ca| ca.agg_list(groups))
170 }
171
172 fn subtract(&self, rhs: &Series) -> PolarsResult<Series> {
173 let rhs = rhs.decimal()?;
174 ((&self.0) - rhs).map(|ca| ca.into_series())
175 }
176 fn add_to(&self, rhs: &Series) -> PolarsResult<Series> {
177 let rhs = rhs.decimal()?;
178 ((&self.0) + rhs).map(|ca| ca.into_series())
179 }
180 fn multiply(&self, rhs: &Series) -> PolarsResult<Series> {
181 let rhs = rhs.decimal()?;
182 ((&self.0) * rhs).map(|ca| ca.into_series())
183 }
184 fn divide(&self, rhs: &Series) -> PolarsResult<Series> {
185 let rhs = rhs.decimal()?;
186 ((&self.0) / rhs).map(|ca| ca.into_series())
187 }
188 #[cfg(feature = "algorithm_group_by")]
189 fn group_tuples(&self, multithreaded: bool, sorted: bool) -> PolarsResult<GroupsType> {
190 self.0.group_tuples(multithreaded, sorted)
191 }
192 fn arg_sort_multiple(
193 &self,
194 by: &[Column],
195 options: &SortMultipleOptions,
196 ) -> PolarsResult<IdxCa> {
197 self.0.arg_sort_multiple(by, options)
198 }
199}
200
201impl SeriesTrait for SeriesWrap<DecimalChunked> {
202 fn rename(&mut self, name: PlSmallStr) {
203 self.0.rename(name)
204 }
205
206 fn chunk_lengths(&self) -> ChunkLenIter {
207 self.0.chunk_lengths()
208 }
209
210 fn name(&self) -> &PlSmallStr {
211 self.0.name()
212 }
213
214 fn chunks(&self) -> &Vec<ArrayRef> {
215 self.0.chunks()
216 }
217 unsafe fn chunks_mut(&mut self) -> &mut Vec<ArrayRef> {
218 self.0.chunks_mut()
219 }
220
221 fn slice(&self, offset: i64, length: usize) -> Series {
222 self.apply_physical_to_s(|ca| ca.slice(offset, length))
223 }
224
225 fn split_at(&self, offset: i64) -> (Series, Series) {
226 let (a, b) = self.0.split_at(offset);
227 let a = a
228 .into_decimal_unchecked(self.0.precision(), self.0.scale())
229 .into_series();
230 let b = b
231 .into_decimal_unchecked(self.0.precision(), self.0.scale())
232 .into_series();
233 (a, b)
234 }
235
236 fn append(&mut self, other: &Series) -> PolarsResult<()> {
237 polars_ensure!(self.0.dtype() == other.dtype(), append);
238 let mut other = other.to_physical_repr().into_owned();
239 self.0
240 .append_owned(std::mem::take(other._get_inner_mut().as_mut()))
241 }
242 fn append_owned(&mut self, mut other: Series) -> PolarsResult<()> {
243 polars_ensure!(self.0.dtype() == other.dtype(), append);
244 self.0.append_owned(std::mem::take(
245 &mut other
246 ._get_inner_mut()
247 .as_any_mut()
248 .downcast_mut::<DecimalChunked>()
249 .unwrap()
250 .0,
251 ))
252 }
253
254 fn extend(&mut self, other: &Series) -> PolarsResult<()> {
255 polars_ensure!(self.0.dtype() == other.dtype(), extend);
256 let other = other.to_physical_repr();
261 self.0.extend(other.as_ref().as_ref().as_ref())?;
262 Ok(())
263 }
264
265 fn filter(&self, filter: &BooleanChunked) -> PolarsResult<Series> {
266 Ok(self
267 .0
268 .filter(filter)?
269 .into_decimal_unchecked(self.0.precision(), self.0.scale())
270 .into_series())
271 }
272
273 fn take(&self, indices: &IdxCa) -> PolarsResult<Series> {
274 Ok(self
275 .0
276 .take(indices)?
277 .into_decimal_unchecked(self.0.precision(), self.0.scale())
278 .into_series())
279 }
280
281 unsafe fn take_unchecked(&self, indices: &IdxCa) -> Series {
282 self.0
283 .take_unchecked(indices)
284 .into_decimal_unchecked(self.0.precision(), self.0.scale())
285 .into_series()
286 }
287
288 fn take_slice(&self, indices: &[IdxSize]) -> PolarsResult<Series> {
289 Ok(self
290 .0
291 .take(indices)?
292 .into_decimal_unchecked(self.0.precision(), self.0.scale())
293 .into_series())
294 }
295
296 unsafe fn take_slice_unchecked(&self, indices: &[IdxSize]) -> Series {
297 self.0
298 .take_unchecked(indices)
299 .into_decimal_unchecked(self.0.precision(), self.0.scale())
300 .into_series()
301 }
302
303 fn len(&self) -> usize {
304 self.0.len()
305 }
306
307 fn rechunk(&self) -> Series {
308 let ca = self.0.rechunk().into_owned();
309 ca.into_decimal_unchecked(self.0.precision(), self.0.scale())
310 .into_series()
311 }
312
313 fn new_from_index(&self, index: usize, length: usize) -> Series {
314 self.0
315 .new_from_index(index, length)
316 .into_decimal_unchecked(self.0.precision(), self.0.scale())
317 .into_series()
318 }
319
320 fn cast(&self, dtype: &DataType, cast_options: CastOptions) -> PolarsResult<Series> {
321 self.0.cast_with_options(dtype, cast_options)
322 }
323
324 #[inline]
325 unsafe fn get_unchecked(&self, index: usize) -> AnyValue {
326 self.0.get_any_value_unchecked(index)
327 }
328
329 fn sort_with(&self, options: SortOptions) -> PolarsResult<Series> {
330 Ok(self
331 .0
332 .sort_with(options)
333 .into_decimal_unchecked(self.0.precision(), self.0.scale())
334 .into_series())
335 }
336
337 fn arg_sort(&self, options: SortOptions) -> IdxCa {
338 self.0.arg_sort(options)
339 }
340
341 fn null_count(&self) -> usize {
342 self.0.null_count()
343 }
344
345 fn has_nulls(&self) -> bool {
346 self.0.has_nulls()
347 }
348
349 #[cfg(feature = "algorithm_group_by")]
350 fn unique(&self) -> PolarsResult<Series> {
351 Ok(self.apply_physical_to_s(|ca| ca.unique().unwrap()))
352 }
353
354 #[cfg(feature = "algorithm_group_by")]
355 fn n_unique(&self) -> PolarsResult<usize> {
356 self.0.n_unique()
357 }
358
359 #[cfg(feature = "algorithm_group_by")]
360 fn arg_unique(&self) -> PolarsResult<IdxCa> {
361 self.0.arg_unique()
362 }
363
364 fn is_null(&self) -> BooleanChunked {
365 self.0.is_null()
366 }
367
368 fn is_not_null(&self) -> BooleanChunked {
369 self.0.is_not_null()
370 }
371
372 fn reverse(&self) -> Series {
373 self.apply_physical_to_s(|ca| ca.reverse())
374 }
375
376 fn shift(&self, periods: i64) -> Series {
377 self.apply_physical_to_s(|ca| ca.shift(periods))
378 }
379
380 fn clone_inner(&self) -> Arc<dyn SeriesTrait> {
381 Arc::new(SeriesWrap(Clone::clone(&self.0)))
382 }
383
384 fn sum_reduce(&self) -> PolarsResult<Scalar> {
385 Ok(self.apply_physical(|ca| {
386 let sum = ca.sum();
387 let DataType::Decimal(_, Some(scale)) = self.dtype() else {
388 unreachable!()
389 };
390 let av = AnyValue::Decimal(sum.unwrap(), *scale);
391 Scalar::new(self.dtype().clone(), av)
392 }))
393 }
394 fn min_reduce(&self) -> PolarsResult<Scalar> {
395 Ok(self.apply_physical(|ca| {
396 let min = ca.min();
397 let DataType::Decimal(_, Some(scale)) = self.dtype() else {
398 unreachable!()
399 };
400 let av = if let Some(min) = min {
401 AnyValue::Decimal(min, *scale)
402 } else {
403 AnyValue::Null
404 };
405 Scalar::new(self.dtype().clone(), av)
406 }))
407 }
408 fn max_reduce(&self) -> PolarsResult<Scalar> {
409 Ok(self.apply_physical(|ca| {
410 let max = ca.max();
411 let DataType::Decimal(_, Some(scale)) = self.dtype() else {
412 unreachable!()
413 };
414 let av = if let Some(m) = max {
415 AnyValue::Decimal(m, *scale)
416 } else {
417 AnyValue::Null
418 };
419 Scalar::new(self.dtype().clone(), av)
420 }))
421 }
422
423 fn _sum_as_f64(&self) -> f64 {
424 self.0._sum_as_f64() / self.scale_factor() as f64
425 }
426
427 fn mean(&self) -> Option<f64> {
428 self.0.mean().map(|v| v / self.scale_factor() as f64)
429 }
430
431 fn median(&self) -> Option<f64> {
432 self.0.median().map(|v| v / self.scale_factor() as f64)
433 }
434 fn median_reduce(&self) -> PolarsResult<Scalar> {
435 Ok(self.apply_scale(self.0.median_reduce()))
436 }
437
438 fn std(&self, ddof: u8) -> Option<f64> {
439 self.0.std(ddof).map(|v| v / self.scale_factor() as f64)
440 }
441 fn std_reduce(&self, ddof: u8) -> PolarsResult<Scalar> {
442 Ok(self.apply_scale(self.0.std_reduce(ddof)))
443 }
444
445 fn quantile_reduce(&self, quantile: f64, method: QuantileMethod) -> PolarsResult<Scalar> {
446 self.0
447 .quantile_reduce(quantile, method)
448 .map(|v| self.apply_scale(v))
449 }
450
451 fn as_any(&self) -> &dyn Any {
452 &self.0
453 }
454
455 fn as_any_mut(&mut self) -> &mut dyn Any {
456 &mut self.0
457 }
458
459 fn as_phys_any(&self) -> &dyn Any {
460 self.0.physical()
461 }
462
463 fn as_arc_any(self: Arc<Self>) -> Arc<dyn Any + Send + Sync> {
464 self as _
465 }
466}