Struct polars::datatypes::Logical

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pub struct Logical<Logical, Physical>(pub ChunkedArray<Physical>, _, pub Option<DataType>) 
where
    Logical: PolarsDataType,
    Physical: PolarsDataType;

Expand description

Maps a logical type to a a chunked array implementation of the physical type. This saves a lot of compiler bloat and allows us to reuse functionality.

Tuple Fields

0: ChunkedArray<Physical>2: Option<DataType>

Implementations

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impl<K, T> Logical<K, T> where
K: PolarsDataType,
T: PolarsDataType,

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pub fn new_logical<J>(ca: ChunkedArray<T>) -> Logical<J, T> where
J: PolarsDataType,

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impl<K, T> Logical<K, T> where
 K: PolarsDataType,
 T: PolarsDataType,
 Logical<K, T>: LogicalType,

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pub fn field(&self) -> Field

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impl Logical<DateType, Int32Type>

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pub fn as_date_iter(
&self
) -> impl Iterator<Item = Option<NaiveDate>> + TrustedLen

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pub fn from_naive_date(name: &str, v: I) -> Logical<DateType, Int32Type> where
I: IntoIterator<Item = NaiveDate>,

Construct a new DateChunked from an iterator over NaiveDate.

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pub fn strftime(&self, fmt: &str) -> ChunkedArray<Utf8Type>

Format Date with a fmt rule. See chrono strftime/strptime.

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pub fn from_naive_date_options(
 name: &str,
 v: I
) -> Logical<DateType, Int32Type> where
 I: IntoIterator<Item = Option<NaiveDate>>,

Construct a new DateChunked from an iterator over optional NaiveDate.

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impl Logical<DatetimeType, Int64Type>

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pub fn as_datetime_iter(
&self
) -> impl Iterator<Item = Option<NaiveDateTime>> + TrustedLen

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pub fn time_unit(&self) -> TimeUnit

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pub fn time_zone(&self) -> &Option<String>

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pub fn strftime(&self, fmt: &str) -> ChunkedArray<Utf8Type>

Format Datetime with a fmt rule. See chrono strftime/strptime.

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pub fn from_naive_datetime(
 name: &str,
 v: I,
 tu: TimeUnit
) -> Logical<DatetimeType, Int64Type> where
 I: IntoIterator<Item = NaiveDateTime>,

Construct a new DatetimeChunked from an iterator over NaiveDateTime.

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pub fn from_naive_datetime_options(
 name: &str,
 v: I,
 tu: TimeUnit
) -> Logical<DatetimeType, Int64Type> where
 I: IntoIterator<Item = Option<NaiveDateTime>>,

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pub fn cast_time_unit(&self, tu: TimeUnit) -> Logical<DatetimeType, Int64Type>

Change the underlying TimeUnit. And update the data accordingly.

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pub fn set_time_unit(&mut self, tu: TimeUnit)

Change the underlying TimeUnit. This does not modify the data.

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pub fn set_time_zone(&mut self, tz: Option<String>)

Change the underlying TimeZone. This does not modify the data.

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impl Logical<DurationType, Int64Type>

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pub fn time_unit(&self) -> TimeUnit

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pub fn cast_time_unit(&self, tu: TimeUnit) -> Logical<DurationType, Int64Type>

Change the underlying TimeUnit. And update the data accordingly.

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pub fn set_time_unit(&mut self, tu: TimeUnit)

Change the underlying TimeUnit. This does not modify the data.

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pub fn from_duration(
 name: &str,
 v: I,
 tu: TimeUnit
) -> Logical<DurationType, Int64Type> where
 I: IntoIterator<Item = Duration>,

Construct a new DurationChunked from an iterator over ChronoDuration.

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pub fn from_duration_options(
 name: &str,
 v: I,
 tu: TimeUnit
) -> Logical<DurationType, Int64Type> where
 I: IntoIterator<Item = Option<Duration>>,

Construct a new DurationChunked from an iterator over optional ChronoDuration.

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impl Logical<TimeType, Int64Type>

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pub fn as_time_iter(
&self
) -> impl Iterator<Item = Option<NaiveTime>> + TrustedLen

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pub fn from_naive_time(name: &str, v: I) -> Logical<TimeType, Int64Type> where
I: IntoIterator<Item = NaiveTime>,

Construct a new TimeChunked from an iterator over NaiveTime.

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pub fn from_naive_time_options(
 name: &str,
 v: I
) -> Logical<TimeType, Int64Type> where
 I: IntoIterator<Item = Option<NaiveTime>>,

Construct a new TimeChunked from an iterator over optional NaiveTime.

Methods from Deref<Target = ChunkedArray<T>>

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pub fn abs(&self) -> ChunkedArray<T>

Convert all values to their absolute/positive value.

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pub fn append(&mut self, other: &ChunkedArray<T>)

Append in place. This is done by adding the chunks of other to this ChunkedArray.

See also extend for appends to the underlying memory

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pub fn cast_and_apply_in_place<F, S>(&self, f: F) -> ChunkedArray<S> where
F: Fn(<S as PolarsNumericType>::Native) -> <S as PolarsNumericType>::Native + Copy,
S: PolarsNumericType,

Cast a numeric array to another numeric data type and apply a function in place. This saves an allocation.

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pub fn extend(&mut self, other: &ChunkedArray<T>)

Extend the memory backed by this array with the values from other.

Different from ChunkedArray::append which adds chunks to this ChunkedArray extent appends the data from other to the underlying PrimitiveArray and thus may cause a reallocation.

However if this does not cause a reallocation, the resulting data structure will not have any extra chunks and thus will yield faster queries.

Prefer extend over append when you want to do a query after a single append. For instance during online operations where you add n rows and rerun a query.

Prefer append over extend when you want to append many times before doing a query. For instance when you read in multiple files and when to store them in a single DataFrame. In the latter case finish the sequence of append operations with a rechunk.

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pub fn rolling_sum(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling sum (moving sum) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their sum.

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pub fn rolling_median(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling median (moving median) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be weighted according to the weights vector.

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pub fn rolling_quantile(
 &self,
 quantile: f64,
 interpolation: QuantileInterpolOptions,
 options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling quantile (moving quantile) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be weighted according to the weights vector.

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pub fn rolling_min(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling min (moving min) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their min.

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pub fn rolling_max(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling max (moving max) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their max.

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pub fn rolling_apply_float<F>(
 &self,
 window_size: usize,
 f: F
) -> Result<ChunkedArray<T>, PolarsError> where
 F: Fn(&ChunkedArray<T>) -> Option<<T as PolarsNumericType>::Native>,

Apply a rolling custom function. This is pretty slow because of dynamic dispatch.

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pub fn rolling_var(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling var (moving var) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their var.

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pub fn rolling_std(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling std (moving std) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their std.

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pub fn arg_true(&self) -> ChunkedArray<UInt32Type>

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pub fn all(&self) -> bool

Check if all values are true

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pub fn any(&self) -> bool

Check if any value is true

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pub fn none_to_nan(&self) -> ChunkedArray<T>

Convert missing values to NaN values.

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pub fn par_iter(&self) -> impl ParallelIterator<Item = Option<Series>>

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pub fn par_iter_indexed(&self) -> impl IndexedParallelIterator

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pub fn par_iter(&self) -> impl ParallelIterator<Item = Option<&str>>

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pub fn to_ndarray(
&self
) -> Result<ArrayBase<ViewRepr<&<T as PolarsNumericType>::Native>, Dim<[usize ; 1]>>, PolarsError>

If data is aligned in a single chunk and has no Null values a zero copy view is returned as an ndarray

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pub fn to_ndarray<N>(
&self
) -> Result<ArrayBase<OwnedRepr<<N as PolarsNumericType>::Native>, Dim<[usize ; 2]>>, PolarsError> where
N: PolarsNumericType,

If all nested Series have the same length, a 2 dimensional ndarray::Array is returned.

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pub fn amortized_iter(
&self
) -> AmortizedListIter<'_, impl Iterator<Item = Option<Box<dyn Array + 'static, Global>>>>

This is an iterator over a ListChunked that save allocations. A Series is: 1. Arc ChunkedArray is: 2. Vec< 3. ArrayRef>

The ArrayRef we indicated with 3. will be updated during iteration. The Series will be pinned in memory, saving an allocation for

Arc<..>
Vec<…>

Warning

Though memory safe in the sense that it will not read unowned memory, UB, or memory leaks this function still needs precautions. The returned should never be cloned or taken longer than a single iteration, as every call on next of the iterator will change the contents of that Series.

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pub fn apply_amortized<'a, F>(&'a self, f: F) -> ChunkedArray<ListType> where
F: FnMut(UnstableSeries<'a>) -> Series,

Apply a closure F elementwise.

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pub fn try_apply_amortized<'a, F>(
 &'a self,
 f: F
) -> Result<ChunkedArray<ListType>, PolarsError> where
 F: FnMut(UnstableSeries<'a>) -> Result<Series, PolarsError>,

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pub fn lst_join(
&self,
separator: &str
) -> Result<ChunkedArray<Utf8Type>, PolarsError>

In case the inner dtype DataType::Utf8, the individual items will be joined into a single string separated by separator.

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pub fn lst_max(&self) -> Series

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pub fn lst_min(&self) -> Series

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pub fn lst_sum(&self) -> Series

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pub fn lst_mean(&self) -> ChunkedArray<Float64Type>

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pub fn lst_sort(&self, reverse: bool) -> ChunkedArray<ListType>

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pub fn lst_reverse(&self) -> ChunkedArray<ListType>

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pub fn lst_unique(&self) -> Result<ChunkedArray<ListType>, PolarsError>

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pub fn lst_arg_min(&self) -> ChunkedArray<UInt32Type>

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pub fn lst_arg_max(&self) -> ChunkedArray<UInt32Type>

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pub fn lst_diff(
 &self,
 n: usize,
 null_behavior: NullBehavior
) -> ChunkedArray<ListType>

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pub fn lst_shift(&self, periods: i64) -> ChunkedArray<ListType>

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pub fn lst_slice(&self, offset: i64, length: usize) -> ChunkedArray<ListType>

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pub fn lst_lengths(&self) -> ChunkedArray<UInt32Type>

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pub fn lst_get(&self, idx: i64) -> Result<Series, PolarsError>

Get the value by index in the sublists. So index 0 would return the first item of every sublist and index -1 would return the last item of every sublist if an index is out of bounds, it will return a None.

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pub fn lst_concat(
&self,
other: &[Series ]
) -> Result<ChunkedArray<ListType>, PolarsError>

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pub fn set_fast_explode(&mut self)

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pub fn to_logical(&mut self, inner_dtype: DataType)

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pub unsafe fn get_object_unchecked(
&self,
index: usize
) -> Option<&(dyn PolarsObjectSafe + 'static)>

Get a hold to an object that can be formatted or downcasted via the Any trait.

Safety

No bounds checks

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pub fn get_object(
&self,
index: usize
) -> Option<&(dyn PolarsObjectSafe + 'static)>

Get a hold to an object that can be formatted or downcasted via the Any trait.

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pub fn sample_n(
 &self,
 n: usize,
 with_replacement: bool,
 seed: Option<u64>
) -> Result<ChunkedArray<T>, PolarsError>

Sample n datapoints from this ChunkedArray.

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pub fn sample_frac(
 &self,
 frac: f64,
 with_replacement: bool,
 seed: Option<u64>
) -> Result<ChunkedArray<T>, PolarsError>

Sample a fraction between 0.0-1.0 of this ChunkedArray.

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pub fn json_path_match(
&self,
json_path: &str
) -> Result<ChunkedArray<Utf8Type>, PolarsError>

Extract json path, first match Refer to https://goessner.net/articles/JsonPath/

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pub fn hex_decode(
&self,
strict: Option<bool>
) -> Result<ChunkedArray<Utf8Type>, PolarsError>

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pub fn hex_encode(&self) -> ChunkedArray<Utf8Type>

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pub fn base64_decode(
&self,
strict: Option<bool>
) -> Result<ChunkedArray<Utf8Type>, PolarsError>

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pub fn base64_encode(&self) -> ChunkedArray<Utf8Type>

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pub fn str_lengths(&self) -> ChunkedArray<UInt32Type>

Get the length of the string values.

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pub fn contains(
&self,
pat: &str
) -> Result<ChunkedArray<BooleanType>, PolarsError>

Check if strings contain a regex pattern

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pub fn replace(
 &self,
 pat: &str,
 val: &str
) -> Result<ChunkedArray<Utf8Type>, PolarsError>

Replace the leftmost (sub)string by a regex pattern

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pub fn replace_all(
 &self,
 pat: &str,
 val: &str
) -> Result<ChunkedArray<Utf8Type>, PolarsError>

Replace all (sub)strings by a regex pattern

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pub fn extract(
 &self,
 pat: &str,
 group_index: usize
) -> Result<ChunkedArray<Utf8Type>, PolarsError>

Extract the nth capture group from pattern

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pub fn to_lowercase(&self) -> ChunkedArray<Utf8Type>

Modify the strings to their lowercase equivalent

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pub fn to_uppercase(&self) -> ChunkedArray<Utf8Type>

Modify the strings to their uppercase equivalent

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pub fn concat(&self, other: &ChunkedArray<Utf8Type>) -> ChunkedArray<Utf8Type>

Concat with the values from a second Utf8Chunked

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pub fn str_slice(
 &self,
 start: i64,
 length: Option<u64>
) -> Result<ChunkedArray<Utf8Type>, PolarsError>

Slice the string values Determines a substring starting from start and with optional length length of each of the elements in array. start can be negative, in which case the start counts from the end of the string.

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pub fn first_non_null(&self) -> Option<usize>

Get the index of the first non null value in this ChunkedArray.

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pub fn iter_validities(&self) -> impl Iterator<Item = Option<&Bitmap>>

Get the buffer of bits representing null values

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pub fn has_validity(&self) -> bool

Return if any the chunks in this [ChunkedArray] have a validity bitmap. no bitmap means no null values.

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pub fn shrink_to_fit(&mut self)

Shrink the capacity of this array to fit it’s length.

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pub fn unpack_series_matching_type(
&self,
series: &Series
) -> Result<&ChunkedArray<T>, PolarsError>

Series to ChunkedArray

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pub fn chunk_id(
&self
) -> Map<Iter<'_, Arc<dyn Array + 'static>>, fn(&Arc<dyn Array + 'static>) -> usize>

Unique id representing the number of chunks

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pub fn chunks(&self) -> &Vec<Arc<dyn Array + 'static>, Global>ⓘNotable traits for Vec<u8, A>`impl<A> Write for Vec<u8, A> where A: Allocator,`

A reference to the chunks

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pub fn is_optimal_aligned(&self) -> bool

Returns true if contains a single chunk and has no null values

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pub fn null_count(&self) -> usize

Count the null values.

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pub fn append_array(
&mut self,
other: Arc<dyn Array + 'static>
) -> Result<(), PolarsError>

Append arrow array in place.

let mut array = Int32Chunked::new("array", &[1, 2]);
let array_2 = Int32Chunked::new("2nd", &[3]);

array.append(&array_2);
assert_eq!(Vec::from(&array), [Some(1), Some(2), Some(3)])

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pub fn is_null(&self) -> ChunkedArray<BooleanType>

Get a mask of the null values.

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pub fn is_not_null(&self) -> ChunkedArray<BooleanType>

Get a mask of the valid values.

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pub fn dtype(&self) -> &DataType

Get data type of ChunkedArray.

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pub fn name(&self) -> &str

Name of the ChunkedArray.

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pub fn ref_field(&self) -> &Field

Get a reference to the field.

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pub fn rename(&mut self, name: &str)

Rename this ChunkedArray.

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pub fn cont_slice(
&self
) -> Result<&[<T as PolarsNumericType>::Native ], PolarsError>

Contiguous slice

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pub fn data_views(
&self
) -> impl Iterator<Item = &[<T as PolarsNumericType>::Native ]> + DoubleEndedIterator

Get slices of the underlying arrow data. NOTE: null values should be taken into account by the user of these slices as they are handled separately

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pub fn into_no_null_iter(
&self
) -> impl Iterator<Item = <T as PolarsNumericType>::Native> + Send + Sync + ExactSizeIterator + DoubleEndedIterator + TrustedLen

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pub fn inner_dtype(&self) -> DataType

Get the inner data type of the list.

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pub fn lhs_sub<N>(&self, lhs: N) -> ChunkedArray<T> where
N: Num + NumCast,

Apply lhs - self

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pub fn lhs_div<N>(&self, lhs: N) -> ChunkedArray<T> where
N: Num + NumCast,

Apply lhs / self

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pub fn lhs_rem<N>(&self, lhs: N) -> ChunkedArray<T> where
N: Num + NumCast,

Apply lhs % self

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pub fn rolling_mean(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling mean (moving mean) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their mean.

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pub fn rolling_sum(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling sum (moving sum) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their sum.

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pub fn rolling_min(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling min (moving min) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their min.

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pub fn rolling_max(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling max (moving max) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their max.

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pub fn rolling_median(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling median (moving median) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be weighted according to the weights vector.

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pub fn rolling_quantile(
 &self,
 quantile: f64,
 interpolation: QuantileInterpolOptions,
 options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling quantile (moving quantile) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be weighted according to the weights vector.

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pub fn rolling_mean(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling mean (moving mean) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their mean.

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pub fn rolling_sum(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling sum (moving sum) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their sum.

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pub fn rolling_min(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling min (moving min) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their min.

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pub fn rolling_max(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling max (moving max) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be multiplied with the weights given by the weights vector. The resulting values will be aggregated to their max.

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pub fn rolling_median(
&self,
options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling median (moving median) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be weighted according to the weights vector.

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pub fn rolling_quantile(
 &self,
 quantile: f64,
 interpolation: QuantileInterpolOptions,
 options: RollingOptions
) -> Result<Series, PolarsError>

Apply a rolling quantile (moving quantile) over the values in this array. A window of length window_size will traverse the array. The values that fill this window will (optionally) be weighted according to the weights vector.

Trait Implementations

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impl<K, T> Clone for Logical<K, T> where
K: PolarsDataType,
T: PolarsDataType,

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fn clone(&self) -> Logical<K, T>

Returns a copy of the value. Read more

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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more

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impl DateMethods for Logical<DateType, Int32Type>

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fn year(&self) -> ChunkedArray<Int32Type>

Extract month from underlying NaiveDate representation. Returns the year number in the calendar date.

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fn month(&self) -> ChunkedArray<UInt32Type>

Extract month from underlying NaiveDateTime representation. Returns the month number starting from 1.

The return value ranges from 1 to 12.

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fn weekday(&self) -> ChunkedArray<UInt32Type>

Extract weekday from underlying NaiveDate representation. Returns the weekday number where monday = 0 and sunday = 6

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fn week(&self) -> ChunkedArray<UInt32Type>

Returns the ISO week number starting from 1. The return value ranges from 1 to 53. (The last week of year differs by years.)

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fn day(&self) -> ChunkedArray<UInt32Type>

Extract day from underlying NaiveDate representation. Returns the day of month starting from 1.

The return value ranges from 1 to 31. (The last day of month differs by months.)

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fn ordinal(&self) -> ChunkedArray<UInt32Type>

Returns the day of year starting from 1.

The return value ranges from 1 to 366. (The last day of year differs by years.)

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fn parse_from_str_slice(
 name: &str,
 v: &[&str ],
 fmt: &str
) -> Logical<DateType, Int32Type>

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impl DatetimeMethods for Logical<DatetimeType, Int64Type>

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fn year(&self) -> ChunkedArray<Int32Type>

Extract month from underlying NaiveDateTime representation. Returns the year number in the calendar date.

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fn month(&self) -> ChunkedArray<UInt32Type>

Extract month from underlying NaiveDateTime representation. Returns the month number starting from 1.

The return value ranges from 1 to 12.

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fn weekday(&self) -> ChunkedArray<UInt32Type>

Extract weekday from underlying NaiveDateTime representation. Returns the weekday number where monday = 0 and sunday = 6

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fn week(&self) -> ChunkedArray<UInt32Type>

Returns the ISO week number starting from 1. The return value ranges from 1 to 53. (The last week of year differs by years.)

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fn day(&self) -> ChunkedArray<UInt32Type>

Extract day from underlying NaiveDateTime representation. Returns the day of month starting from 1.

The return value ranges from 1 to 31. (The last day of month differs by months.)

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fn hour(&self) -> ChunkedArray<UInt32Type>

Extract hour from underlying NaiveDateTime representation. Returns the hour number from 0 to 23.

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fn minute(&self) -> ChunkedArray<UInt32Type>

Extract minute from underlying NaiveDateTime representation. Returns the minute number from 0 to 59.

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fn second(&self) -> ChunkedArray<UInt32Type>

Extract second from underlying NaiveDateTime representation. Returns the second number from 0 to 59.

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fn nanosecond(&self) -> ChunkedArray<UInt32Type>

Extract second from underlying NaiveDateTime representation. Returns the number of nanoseconds since the whole non-leap second. The range from 1,000,000,000 to 1,999,999,999 represents the leap second.

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fn ordinal(&self) -> ChunkedArray<UInt32Type>

Returns the day of year starting from 1.

The return value ranges from 1 to 366. (The last day of year differs by years.)

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fn parse_from_str_slice(
 name: &str,
 v: &[&str ],
 fmt: &str,
 tu: TimeUnit
) -> Logical<DatetimeType, Int64Type>

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impl<K, T> Deref for Logical<K, T> where
K: PolarsDataType,
T: PolarsDataType,

type Target = ChunkedArray<T>

The resulting type after dereferencing.

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fn deref(&self) -> &<Logical<K, T> as Deref>::Target

Dereferences the value.

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impl<K, T> DerefMut for Logical<K, T> where
K: PolarsDataType,
T: PolarsDataType,

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fn deref_mut(&mut self) -> &mut <Logical<K, T> as Deref>::Target

Mutably dereferences the value.

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impl DurationMethods for Logical<DurationType, Int64Type>

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fn hours(&self) -> ChunkedArray<Int64Type>

Extract the hours from a Duration

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fn days(&self) -> ChunkedArray<Int64Type>

Extract the days from a Duration

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fn minutes(&self) -> ChunkedArray<Int64Type>

Extract the seconds from a Duration

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fn seconds(&self) -> ChunkedArray<Int64Type>

Extract the seconds from a Duration

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fn milliseconds(&self) -> ChunkedArray<Int64Type>

Extract the milliseconds from a Duration

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fn nanoseconds(&self) -> ChunkedArray<Int64Type>

Extract the nanoseconds from a Duration

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impl From<ChunkedArray<Int32Type>> for Logical<DateType, Int32Type>

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fn from(ca: ChunkedArray<Int32Type>) -> Logical<DateType, Int32Type>

Converts to this type from the input type.

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impl From<ChunkedArray<Int64Type>> for Logical<TimeType, Int64Type>

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fn from(ca: ChunkedArray<Int64Type>) -> Logical<TimeType, Int64Type>

Converts to this type from the input type.

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impl From<Logical<DateType, Int32Type>> for Series

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fn from(a: Logical<DateType, Int32Type>) -> Series

Converts to this type from the input type.

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impl From<Logical<DatetimeType, Int64Type>> for Series

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fn from(a: Logical<DatetimeType, Int64Type>) -> Series

Converts to this type from the input type.

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impl From<Logical<DurationType, Int64Type>> for Series

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fn from(a: Logical<DurationType, Int64Type>) -> Series

Converts to this type from the input type.

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impl From<Logical<TimeType, Int64Type>> for Series

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fn from(a: Logical<TimeType, Int64Type>) -> Series

Converts to this type from the input type.

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impl IntoSeries for Logical<TimeType, Int64Type>

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fn into_series(self) -> Series

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fn is_series() -> bool

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impl IntoSeries for Logical<DatetimeType, Int64Type>

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fn into_series(self) -> Series

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fn is_series() -> bool

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impl IntoSeries for Logical<DateType, Int32Type>

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fn into_series(self) -> Series

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fn is_series() -> bool

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impl IntoSeries for Logical<DurationType, Int64Type>

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fn into_series(self) -> Series

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fn is_series() -> bool

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impl IntoSeriesOps for Logical<DatetimeType, Int64Type>

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fn to_ops(&self) -> Arc<dyn SeriesOps + 'static>

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impl IntoSeriesOps for Logical<TimeType, Int64Type>

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fn to_ops(&self) -> Arc<dyn SeriesOps + 'static>

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impl LogicalType for Logical<DateType, Int32Type>

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fn dtype(&self) -> &DataType

Get data type of ChunkedArray.

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fn get_any_value(&self, i: usize) -> AnyValue<'_>

Gets AnyValue from LogicalType

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fn cast(&self, dtype: &DataType) -> Result<Series, PolarsError>

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impl LogicalType for Logical<DurationType, Int64Type>

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fn dtype(&self) -> &DataType

Get data type of ChunkedArray.

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fn get_any_value(&self, i: usize) -> AnyValue<'_>

Gets AnyValue from LogicalType

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fn cast(&self, dtype: &DataType) -> Result<Series, PolarsError>

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impl LogicalType for Logical<TimeType, Int64Type>

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fn dtype(&self) -> &'static DataType

Get data type of ChunkedArray.

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fn get_any_value(&self, i: usize) -> AnyValue<'_>

Gets AnyValue from LogicalType

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fn cast(&self, dtype: &DataType) -> Result<Series, PolarsError>

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impl LogicalType for Logical<DatetimeType, Int64Type>

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fn dtype(&self) -> &DataType

Get data type of ChunkedArray.

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fn get_any_value(&self, i: usize) -> AnyValue<'_>

Gets AnyValue from LogicalType

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fn cast(&self, dtype: &DataType) -> Result<Series, PolarsError>

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