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pola-rs
GitHub Repository: pola-rs/polars
Path: blob/main/crates/polars-core/src/series/implementations/datetime.rs
6940 views
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use polars_compute::rolling::QuantileMethod;
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use super::*;
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#[cfg(feature = "algorithm_group_by")]
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use crate::frame::group_by::*;
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use crate::prelude::*;
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unsafe impl IntoSeries for DatetimeChunked {
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fn into_series(self) -> Series {
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Series(Arc::new(SeriesWrap(self)))
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}
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}
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impl private::PrivateSeriesNumeric for SeriesWrap<DatetimeChunked> {
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fn bit_repr(&self) -> Option<BitRepr> {
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Some(self.0.physical().to_bit_repr())
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}
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}
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impl private::PrivateSeries for SeriesWrap<DatetimeChunked> {
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fn compute_len(&mut self) {
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self.0.physical_mut().compute_len()
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}
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fn _field(&self) -> Cow<'_, Field> {
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Cow::Owned(self.0.field())
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}
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fn _dtype(&self) -> &DataType {
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self.0.dtype()
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}
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fn _get_flags(&self) -> StatisticsFlags {
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self.0.physical().get_flags()
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}
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fn _set_flags(&mut self, flags: StatisticsFlags) {
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self.0.physical_mut().set_flags(flags)
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}
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#[cfg(feature = "zip_with")]
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fn zip_with_same_type(&self, mask: &BooleanChunked, other: &Series) -> PolarsResult<Series> {
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let other = other.to_physical_repr().into_owned();
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self.0
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.physical()
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.zip_with(mask, other.as_ref().as_ref())
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.map(|ca| {
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ca.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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})
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}
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fn into_total_eq_inner<'a>(&'a self) -> Box<dyn TotalEqInner + 'a> {
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self.0.physical().into_total_eq_inner()
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}
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fn into_total_ord_inner<'a>(&'a self) -> Box<dyn TotalOrdInner + 'a> {
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self.0.physical().into_total_ord_inner()
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}
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fn vec_hash(
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&self,
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random_state: PlSeedableRandomStateQuality,
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buf: &mut Vec<u64>,
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) -> PolarsResult<()> {
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self.0.physical().vec_hash(random_state, buf)?;
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Ok(())
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}
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fn vec_hash_combine(
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&self,
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build_hasher: PlSeedableRandomStateQuality,
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hashes: &mut [u64],
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) -> PolarsResult<()> {
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self.0.physical().vec_hash_combine(build_hasher, hashes)?;
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Ok(())
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}
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#[cfg(feature = "algorithm_group_by")]
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unsafe fn agg_min(&self, groups: &GroupsType) -> Series {
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self.0
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.physical()
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.agg_min(groups)
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.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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}
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#[cfg(feature = "algorithm_group_by")]
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unsafe fn agg_max(&self, groups: &GroupsType) -> Series {
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self.0
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.physical()
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.agg_max(groups)
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.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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}
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#[cfg(feature = "algorithm_group_by")]
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unsafe fn agg_list(&self, groups: &GroupsType) -> Series {
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// we cannot cast and dispatch as the inner type of the list would be incorrect
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self.0
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.physical()
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.agg_list(groups)
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.cast(&DataType::List(Box::new(self.dtype().clone())))
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.unwrap()
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}
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fn subtract(&self, rhs: &Series) -> PolarsResult<Series> {
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match (self.dtype(), rhs.dtype()) {
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(DataType::Datetime(tu, tz), DataType::Datetime(tur, tzr)) => {
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assert_eq!(tu, tur);
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assert_eq!(tz, tzr);
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let lhs = self.cast(&DataType::Int64, CastOptions::NonStrict).unwrap();
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let rhs = rhs.cast(&DataType::Int64).unwrap();
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Ok(lhs.subtract(&rhs)?.into_duration(*tu).into_series())
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},
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(DataType::Datetime(tu, tz), DataType::Duration(tur)) => {
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assert_eq!(tu, tur);
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let lhs = self.cast(&DataType::Int64, CastOptions::NonStrict).unwrap();
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let rhs = rhs.cast(&DataType::Int64).unwrap();
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Ok(lhs
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.subtract(&rhs)?
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.into_datetime(*tu, tz.clone())
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.into_series())
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},
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(dtl, dtr) => polars_bail!(opq = sub, dtl, dtr),
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}
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}
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fn add_to(&self, rhs: &Series) -> PolarsResult<Series> {
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match (self.dtype(), rhs.dtype()) {
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(DataType::Datetime(tu, tz), DataType::Duration(tur)) => {
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assert_eq!(tu, tur);
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let lhs = self.cast(&DataType::Int64, CastOptions::NonStrict).unwrap();
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let rhs = rhs.cast(&DataType::Int64).unwrap();
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Ok(lhs
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.add_to(&rhs)?
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.into_datetime(*tu, tz.clone())
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.into_series())
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},
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(dtl, dtr) => polars_bail!(opq = add, dtl, dtr),
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}
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}
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fn multiply(&self, rhs: &Series) -> PolarsResult<Series> {
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polars_bail!(opq = mul, self.dtype(), rhs.dtype());
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}
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fn divide(&self, rhs: &Series) -> PolarsResult<Series> {
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polars_bail!(opq = div, self.dtype(), rhs.dtype());
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}
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fn remainder(&self, rhs: &Series) -> PolarsResult<Series> {
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polars_bail!(opq = rem, self.dtype(), rhs.dtype());
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}
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#[cfg(feature = "algorithm_group_by")]
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fn group_tuples(&self, multithreaded: bool, sorted: bool) -> PolarsResult<GroupsType> {
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self.0.physical().group_tuples(multithreaded, sorted)
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}
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fn arg_sort_multiple(
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&self,
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by: &[Column],
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options: &SortMultipleOptions,
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) -> PolarsResult<IdxCa> {
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self.0.physical().arg_sort_multiple(by, options)
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}
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}
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impl SeriesTrait for SeriesWrap<DatetimeChunked> {
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fn rename(&mut self, name: PlSmallStr) {
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self.0.rename(name);
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}
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fn chunk_lengths(&self) -> ChunkLenIter<'_> {
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self.0.physical().chunk_lengths()
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}
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fn name(&self) -> &PlSmallStr {
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self.0.name()
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}
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fn chunks(&self) -> &Vec<ArrayRef> {
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self.0.physical().chunks()
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}
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unsafe fn chunks_mut(&mut self) -> &mut Vec<ArrayRef> {
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self.0.physical_mut().chunks_mut()
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}
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fn shrink_to_fit(&mut self) {
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self.0.physical_mut().shrink_to_fit()
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}
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fn slice(&self, offset: i64, length: usize) -> Series {
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self.0.slice(offset, length).into_series()
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}
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fn split_at(&self, offset: i64) -> (Series, Series) {
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let (a, b) = self.0.split_at(offset);
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(a.into_series(), b.into_series())
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}
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fn _sum_as_f64(&self) -> f64 {
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self.0.physical()._sum_as_f64()
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}
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fn mean(&self) -> Option<f64> {
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self.0.physical().mean()
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}
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fn median(&self) -> Option<f64> {
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self.0.physical().median()
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}
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fn append(&mut self, other: &Series) -> PolarsResult<()> {
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polars_ensure!(self.0.dtype() == other.dtype(), append);
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let mut other = other.to_physical_repr().into_owned();
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self.0
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.physical_mut()
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.append_owned(std::mem::take(other._get_inner_mut().as_mut()))
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}
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fn append_owned(&mut self, mut other: Series) -> PolarsResult<()> {
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polars_ensure!(self.0.dtype() == other.dtype(), append);
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self.0.physical_mut().append_owned(std::mem::take(
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&mut other
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._get_inner_mut()
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.as_any_mut()
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.downcast_mut::<DatetimeChunked>()
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.unwrap()
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.phys,
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))
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}
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fn extend(&mut self, other: &Series) -> PolarsResult<()> {
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polars_ensure!(self.0.dtype() == other.dtype(), extend);
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let other = other.to_physical_repr();
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self.0
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.physical_mut()
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.extend(other.as_ref().as_ref().as_ref())?;
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Ok(())
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}
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fn filter(&self, filter: &BooleanChunked) -> PolarsResult<Series> {
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self.0.physical().filter(filter).map(|ca| {
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ca.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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})
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}
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fn take(&self, indices: &IdxCa) -> PolarsResult<Series> {
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let ca = self.0.physical().take(indices)?;
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Ok(ca
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.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series())
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}
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unsafe fn take_unchecked(&self, indices: &IdxCa) -> Series {
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let ca = self.0.physical().take_unchecked(indices);
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ca.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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}
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fn take_slice(&self, indices: &[IdxSize]) -> PolarsResult<Series> {
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let ca = self.0.physical().take(indices)?;
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Ok(ca
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.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series())
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}
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unsafe fn take_slice_unchecked(&self, indices: &[IdxSize]) -> Series {
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let ca = self.0.physical().take_unchecked(indices);
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ca.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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}
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fn len(&self) -> usize {
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self.0.len()
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}
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fn rechunk(&self) -> Series {
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self.0
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.physical()
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.rechunk()
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.into_owned()
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.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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}
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fn new_from_index(&self, index: usize, length: usize) -> Series {
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self.0
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.physical()
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.new_from_index(index, length)
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.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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}
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fn cast(&self, dtype: &DataType, cast_options: CastOptions) -> PolarsResult<Series> {
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match dtype {
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DataType::String => Ok(self.0.to_string("iso")?.into_series()),
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_ => self.0.cast_with_options(dtype, cast_options),
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}
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}
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#[inline]
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unsafe fn get_unchecked(&self, index: usize) -> AnyValue<'_> {
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self.0.get_any_value_unchecked(index)
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}
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fn sort_with(&self, options: SortOptions) -> PolarsResult<Series> {
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Ok(self
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.0
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.physical()
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.sort_with(options)
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.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series())
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}
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fn arg_sort(&self, options: SortOptions) -> IdxCa {
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self.0.physical().arg_sort(options)
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}
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fn null_count(&self) -> usize {
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self.0.null_count()
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}
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fn has_nulls(&self) -> bool {
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self.0.has_nulls()
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}
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#[cfg(feature = "algorithm_group_by")]
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fn unique(&self) -> PolarsResult<Series> {
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self.0.physical().unique().map(|ca| {
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ca.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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})
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}
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#[cfg(feature = "algorithm_group_by")]
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fn n_unique(&self) -> PolarsResult<usize> {
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self.0.physical().n_unique()
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}
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#[cfg(feature = "algorithm_group_by")]
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fn arg_unique(&self) -> PolarsResult<IdxCa> {
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self.0.physical().arg_unique()
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}
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fn is_null(&self) -> BooleanChunked {
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self.0.is_null()
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}
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fn is_not_null(&self) -> BooleanChunked {
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self.0.is_not_null()
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}
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fn reverse(&self) -> Series {
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self.0
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.physical()
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.reverse()
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.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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}
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fn as_single_ptr(&mut self) -> PolarsResult<usize> {
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self.0.physical_mut().as_single_ptr()
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}
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fn shift(&self, periods: i64) -> Series {
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self.0
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.physical()
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.shift(periods)
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.into_datetime(self.0.time_unit(), self.0.time_zone().clone())
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.into_series()
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}
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fn max_reduce(&self) -> PolarsResult<Scalar> {
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let sc = self.0.physical().max_reduce();
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Ok(Scalar::new(self.dtype().clone(), sc.value().clone()))
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}
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fn min_reduce(&self) -> PolarsResult<Scalar> {
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let sc = self.0.physical().min_reduce();
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Ok(Scalar::new(self.dtype().clone(), sc.value().clone()))
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}
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fn median_reduce(&self) -> PolarsResult<Scalar> {
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let av: AnyValue = self.median().map(|v| v as i64).into();
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Ok(Scalar::new(self.dtype().clone(), av))
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}
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fn quantile_reduce(&self, _quantile: f64, _method: QuantileMethod) -> PolarsResult<Scalar> {
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Ok(Scalar::new(self.dtype().clone(), AnyValue::Null))
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}
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fn clone_inner(&self) -> Arc<dyn SeriesTrait> {
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Arc::new(SeriesWrap(Clone::clone(&self.0)))
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}
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fn find_validity_mismatch(&self, other: &Series, idxs: &mut Vec<IdxSize>) {
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self.0.physical().find_validity_mismatch(other, idxs)
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}
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fn as_any(&self) -> &dyn Any {
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&self.0
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}
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fn as_any_mut(&mut self) -> &mut dyn Any {
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&mut self.0
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}
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fn as_phys_any(&self) -> &dyn Any {
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self.0.physical()
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}
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fn as_arc_any(self: Arc<Self>) -> Arc<dyn Any + Send + Sync> {
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self as _
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}
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}
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