polars_core/series/implementations/
null.rsuse std::any::Any;
use polars_error::constants::LENGTH_LIMIT_MSG;
use self::compare_inner::TotalOrdInner;
use crate::prelude::compare_inner::{IntoTotalEqInner, TotalEqInner};
use crate::prelude::*;
use crate::series::private::{PrivateSeries, PrivateSeriesNumeric};
use crate::series::*;
impl Series {
pub fn new_null(name: PlSmallStr, len: usize) -> Series {
NullChunked::new(name, len).into_series()
}
}
#[derive(Clone)]
pub struct NullChunked {
pub(crate) name: PlSmallStr,
length: IdxSize,
chunks: Vec<ArrayRef>,
}
impl NullChunked {
pub(crate) fn new(name: PlSmallStr, len: usize) -> Self {
Self {
name,
length: len as IdxSize,
chunks: vec![Box::new(arrow::array::NullArray::new(
ArrowDataType::Null,
len,
))],
}
}
}
impl PrivateSeriesNumeric for NullChunked {
fn bit_repr(&self) -> Option<BitRepr> {
Some(BitRepr::Small(UInt32Chunked::full_null(
self.name.clone(),
self.len(),
)))
}
}
impl PrivateSeries for NullChunked {
fn compute_len(&mut self) {
fn inner(chunks: &[ArrayRef]) -> usize {
match chunks.len() {
1 => chunks[0].len(),
_ => chunks.iter().fold(0, |acc, arr| acc + arr.len()),
}
}
self.length = IdxSize::try_from(inner(&self.chunks)).expect(LENGTH_LIMIT_MSG);
}
fn _field(&self) -> Cow<Field> {
Cow::Owned(Field::new(self.name().clone(), DataType::Null))
}
#[allow(unused)]
fn _set_flags(&mut self, flags: StatisticsFlags) {}
fn _dtype(&self) -> &DataType {
&DataType::Null
}
#[cfg(feature = "zip_with")]
fn zip_with_same_type(&self, mask: &BooleanChunked, other: &Series) -> PolarsResult<Series> {
let len = match (self.len(), mask.len(), other.len()) {
(a, b, c) if a == b && b == c => a,
(1, a, b) | (a, 1, b) | (a, b, 1) if a == b => a,
(a, 1, 1) | (1, a, 1) | (1, 1, a) => a,
(_, 0, _) => 0,
_ => {
polars_bail!(ShapeMismatch: "shapes of `self`, `mask` and `other` are not suitable for `zip_with` operation")
},
};
Ok(Self::new(self.name().clone(), len).into_series())
}
fn into_total_eq_inner<'a>(&'a self) -> Box<dyn TotalEqInner + 'a> {
IntoTotalEqInner::into_total_eq_inner(self)
}
fn into_total_ord_inner<'a>(&'a self) -> Box<dyn TotalOrdInner + 'a> {
invalid_operation_panic!(into_total_ord_inner, self)
}
fn subtract(&self, _rhs: &Series) -> PolarsResult<Series> {
null_arithmetic(self, _rhs, "subtract")
}
fn add_to(&self, _rhs: &Series) -> PolarsResult<Series> {
null_arithmetic(self, _rhs, "add_to")
}
fn multiply(&self, _rhs: &Series) -> PolarsResult<Series> {
null_arithmetic(self, _rhs, "multiply")
}
fn divide(&self, _rhs: &Series) -> PolarsResult<Series> {
null_arithmetic(self, _rhs, "divide")
}
fn remainder(&self, _rhs: &Series) -> PolarsResult<Series> {
null_arithmetic(self, _rhs, "remainder")
}
#[cfg(feature = "algorithm_group_by")]
fn group_tuples(&self, _multithreaded: bool, _sorted: bool) -> PolarsResult<GroupsProxy> {
Ok(if self.is_empty() {
GroupsProxy::default()
} else {
GroupsProxy::Slice {
groups: vec![[0, self.length]],
rolling: false,
}
})
}
#[cfg(feature = "algorithm_group_by")]
unsafe fn agg_list(&self, groups: &GroupsProxy) -> Series {
AggList::agg_list(self, groups)
}
fn _get_flags(&self) -> StatisticsFlags {
StatisticsFlags::empty()
}
fn vec_hash(&self, random_state: PlRandomState, buf: &mut Vec<u64>) -> PolarsResult<()> {
VecHash::vec_hash(self, random_state, buf)?;
Ok(())
}
fn vec_hash_combine(
&self,
build_hasher: PlRandomState,
hashes: &mut [u64],
) -> PolarsResult<()> {
VecHash::vec_hash_combine(self, build_hasher, hashes)?;
Ok(())
}
}
fn null_arithmetic(lhs: &NullChunked, rhs: &Series, op: &str) -> PolarsResult<Series> {
let output_len = match (lhs.len(), rhs.len()) {
(1, len_r) => len_r,
(len_l, 1) => len_l,
(len_l, len_r) if len_l == len_r => len_l,
_ => polars_bail!(ComputeError: "Cannot {:?} two series of different lengths.", op),
};
Ok(NullChunked::new(lhs.name().clone(), output_len).into_series())
}
impl SeriesTrait for NullChunked {
fn name(&self) -> &PlSmallStr {
&self.name
}
fn rename(&mut self, name: PlSmallStr) {
self.name = name
}
fn chunks(&self) -> &Vec<ArrayRef> {
&self.chunks
}
unsafe fn chunks_mut(&mut self) -> &mut Vec<ArrayRef> {
&mut self.chunks
}
fn chunk_lengths(&self) -> ChunkLenIter {
self.chunks.iter().map(|chunk| chunk.len())
}
fn take(&self, indices: &IdxCa) -> PolarsResult<Series> {
Ok(NullChunked::new(self.name.clone(), indices.len()).into_series())
}
unsafe fn take_unchecked(&self, indices: &IdxCa) -> Series {
NullChunked::new(self.name.clone(), indices.len()).into_series()
}
fn take_slice(&self, indices: &[IdxSize]) -> PolarsResult<Series> {
Ok(NullChunked::new(self.name.clone(), indices.len()).into_series())
}
unsafe fn take_slice_unchecked(&self, indices: &[IdxSize]) -> Series {
NullChunked::new(self.name.clone(), indices.len()).into_series()
}
fn len(&self) -> usize {
self.length as usize
}
fn has_nulls(&self) -> bool {
self.len() > 0
}
fn rechunk(&self) -> Series {
NullChunked::new(self.name.clone(), self.len()).into_series()
}
fn drop_nulls(&self) -> Series {
NullChunked::new(self.name.clone(), 0).into_series()
}
fn cast(&self, dtype: &DataType, _cast_options: CastOptions) -> PolarsResult<Series> {
Ok(Series::full_null(self.name.clone(), self.len(), dtype))
}
fn null_count(&self) -> usize {
self.len()
}
#[cfg(feature = "algorithm_group_by")]
fn unique(&self) -> PolarsResult<Series> {
let ca = NullChunked::new(self.name.clone(), self.n_unique().unwrap());
Ok(ca.into_series())
}
#[cfg(feature = "algorithm_group_by")]
fn n_unique(&self) -> PolarsResult<usize> {
let n = if self.is_empty() { 0 } else { 1 };
Ok(n)
}
fn new_from_index(&self, _index: usize, length: usize) -> Series {
NullChunked::new(self.name.clone(), length).into_series()
}
unsafe fn get_unchecked(&self, _index: usize) -> AnyValue {
AnyValue::Null
}
fn slice(&self, offset: i64, length: usize) -> Series {
let (chunks, len) = chunkops::slice(&self.chunks, offset, length, self.len());
NullChunked {
name: self.name.clone(),
length: len as IdxSize,
chunks,
}
.into_series()
}
fn split_at(&self, offset: i64) -> (Series, Series) {
let (l, r) = chunkops::split_at(self.chunks(), offset, self.len());
(
NullChunked {
name: self.name.clone(),
length: l.iter().map(|arr| arr.len() as IdxSize).sum(),
chunks: l,
}
.into_series(),
NullChunked {
name: self.name.clone(),
length: r.iter().map(|arr| arr.len() as IdxSize).sum(),
chunks: r,
}
.into_series(),
)
}
fn sort_with(&self, _options: SortOptions) -> PolarsResult<Series> {
Ok(self.clone().into_series())
}
fn arg_sort(&self, _options: SortOptions) -> IdxCa {
IdxCa::from_vec(self.name().clone(), (0..self.len() as IdxSize).collect())
}
fn is_null(&self) -> BooleanChunked {
BooleanChunked::full(self.name().clone(), true, self.len())
}
fn is_not_null(&self) -> BooleanChunked {
BooleanChunked::full(self.name().clone(), false, self.len())
}
fn reverse(&self) -> Series {
self.clone().into_series()
}
fn filter(&self, filter: &BooleanChunked) -> PolarsResult<Series> {
let len = if self.is_empty() {
polars_ensure!(filter.len() <= 1, ShapeMismatch: "filter's length: {} differs from that of the series: 0", filter.len());
0
} else if filter.len() == 1 {
return match filter.get(0) {
Some(true) => Ok(self.clone().into_series()),
None | Some(false) => Ok(NullChunked::new(self.name.clone(), 0).into_series()),
};
} else {
polars_ensure!(filter.len() == self.len(), ShapeMismatch: "filter's length: {} differs from that of the series: {}", filter.len(), self.len());
filter.sum().unwrap_or(0) as usize
};
Ok(NullChunked::new(self.name.clone(), len).into_series())
}
fn shift(&self, _periods: i64) -> Series {
self.clone().into_series()
}
fn append(&mut self, other: &Series) -> PolarsResult<()> {
polars_ensure!(other.dtype() == &DataType::Null, ComputeError: "expected null dtype");
self.chunks.extend(other.chunks().iter().cloned());
self.length += other.len() as IdxSize;
Ok(())
}
fn extend(&mut self, other: &Series) -> PolarsResult<()> {
*self = NullChunked::new(self.name.clone(), self.len() + other.len());
Ok(())
}
fn clone_inner(&self) -> Arc<dyn SeriesTrait> {
Arc::new(self.clone())
}
fn as_any(&self) -> &dyn Any {
self
}
}
unsafe impl IntoSeries for NullChunked {
fn into_series(self) -> Series
where
Self: Sized,
{
Series(Arc::new(self))
}
}