Series

Namespace: Polars.CSharp

Represents a single column of data (1-dimensional array).

A Series is backed by Apache Arrow arrays and supports eager execution. Operations on Series are generally performed immediately.

Sub-namespaces

Sub-namespace	Page	Description
.Array	Series.Array	Access Fixed-Size List (Array) operations.
.Bin	Series.Bin	Access binary operations.
.Cat	Series.Cat	Access categorical operations.
.Dt	Series.Dt	Date Ops
.Ext	Series.Ext	Access extension datatype operations.
.List	Series.List	Access list operations.
.Str	Series.Str	String Ops
.Struct	Series.Struct	Access struct operations.

Properties & Indexers

Property	Type	Description
DataType	DataType	Gets the DataType of the Series.
DataTypeName	string	Get the string representation of the Series data type (e.g. "i64", "str", "datetime(μs)").
IsContiguous	bool	Determines if the Series memory is physically contiguous (i.e., consists of a single chunk).
Length	long	Length of the Series.
NChunks	long	Gets the number of underlying Arrow memory chunks.
Name	string	Name of the Series.
NullCount	long	Get the number of null values in the Series.
Shape	long[]	Shape of this Series. In Polars, a Series is always 1D, so this returns an array of length 1.
SortedFlags	SortStateFlags	Gets the current metadata sortedness flags of this Series. (O(1) operation)
this[Range range]	Series	Range Indexer (getitem for slices) e.g. s[1..5] / s[..^1]
this[Series key]	object	e.g. s[s > 5] = 10;
this[int index]	object	Get an item at the specified index as object (boxed).
this[int[] indices]	object	e.g. s[0, 2, 5] = 99;

Constructors & Static Methods

Series

This will create an empty series, if dtype is also null, datatype will be null.

public Series(string name, ReadOnlySpan<sbyte> data)
public Series(string name, ReadOnlySpan<sbyte?> data)
public Series(string name, ReadOnlySpan<short> data)
public Series(string name, ReadOnlySpan<short?> data)
public Series(string name, ReadOnlySpan<int> data)
public Series(string name, ReadOnlySpan<int?> data)
public Series(string name, ReadOnlySpan<long> data)
public Series(string name, ReadOnlySpan<long?> data)
public Series(string name, ReadOnlySpan<Int128> data)
public Series(string name, ReadOnlySpan<Int128?> data)
public Series(string name, ReadOnlySpan<byte> data)
public Series(string name, ReadOnlySpan<byte?> data)
public Series(string name, ReadOnlySpan<ushort> data)
public Series(string name, ReadOnlySpan<ushort?> data)
public Series(string name, ReadOnlySpan<uint> data)
public Series(string name, ReadOnlySpan<uint?> data)
public Series(string name, ReadOnlySpan<ulong> data)
public Series(string name, ReadOnlySpan<ulong?> data)
public Series(string name, ReadOnlySpan<UInt128> data)
public Series(string name, ReadOnlySpan<UInt128?> data)
public Series(string name, ReadOnlySpan<Half> data)
public Series(string name, ReadOnlySpan<Half?> data)
public Series(string name, ReadOnlySpan<float> data)
public Series(string name, ReadOnlySpan<float?> data)
public Series(string name, ReadOnlySpan<double> data)
public Series(string name, ReadOnlySpan<double?> data)
public Series(string name, ReadOnlySpan<bool> data)
public Series(string name, ReadOnlySpan<bool?> data)
public Series(string name, ReadOnlySpan<string> data)
public Series(string name, ReadOnlySpan<decimal> data)
public Series(string name, ReadOnlySpan<decimal?> data)
public Series(string name, ReadOnlySpan<DateTime> data)
public Series(string name, ReadOnlySpan<DateTime?> data)
public Series(string name, ReadOnlySpan<DateTimeOffset> data)
public Series(string name, ReadOnlySpan<DateTimeOffset?> data)
public Series(string name, ReadOnlySpan<DateOnly> data)
public Series(string name, ReadOnlySpan<DateOnly?> data)
public Series(string name, ReadOnlySpan<TimeOnly> data)
public Series(string name, ReadOnlySpan<TimeOnly?> data)
public Series(string name, ReadOnlySpan<TimeSpan> data)
public Series(string name, ReadOnlySpan<TimeSpan?> data)
public Series(string name, sbyte[,] data)
public Series(string name, byte[,] data)
public Series(string name, short[,] data)
public Series(string name, ushort[,] data)
public Series(string name, int[,] data)
public Series(string name, uint[,] data)
public Series(string name, long[,] data)
public Series(string name, ulong[,] data)
public Series(string name, Half[,] data)
public Series(string name, float[,] data)
public Series(string name, double[,] data)
public Series(string name, decimal[,] data)
public Series(string name, Int128[,] data)
public Series(string name, UInt128[,] data)
public Series(string name = "", DataType? dtype = null)

Parameters

Name	Type	Description
name	string	-
data	ReadOnlySpan<sbyte> / ReadOnlySpan<sbyte?> / ReadOnlySpan<short> / ReadOnlySpan<short?> / ReadOnlySpan<int> / ReadOnlySpan<int?> / ReadOnlySpan<long> / ReadOnlySpan<long?> / ReadOnlySpan<Int128> / ReadOnlySpan<Int128?> / ReadOnlySpan<byte> / ReadOnlySpan<byte?> / ReadOnlySpan<ushort> / ReadOnlySpan<ushort?> / ReadOnlySpan<uint> / ReadOnlySpan<uint?> / ReadOnlySpan<ulong> / ReadOnlySpan<ulong?> / ReadOnlySpan<UInt128> / ReadOnlySpan<UInt128?> / ReadOnlySpan<Half> / ReadOnlySpan<Half?> / ReadOnlySpan<float> / ReadOnlySpan<float?> / ReadOnlySpan<double> / ReadOnlySpan<double?> / ReadOnlySpan<bool> / ReadOnlySpan<bool?> / ReadOnlySpan<string> / ReadOnlySpan<decimal> / ReadOnlySpan<decimal?> / ReadOnlySpan<DateTime> / ReadOnlySpan<DateTime?> / ReadOnlySpan<DateTimeOffset> / ReadOnlySpan<DateTimeOffset?> / ReadOnlySpan<DateOnly> / ReadOnlySpan<DateOnly?> / ReadOnlySpan<TimeOnly> / ReadOnlySpan<TimeOnly?> / ReadOnlySpan<TimeSpan> / ReadOnlySpan<TimeSpan?> / sbyte[,] / short[,] / ushort[,] / int[,] / uint[,] / long[,] / ulong[,] / Half[,] / float[,] / double[,] / decimal[,] / Int128[,] / UInt128[,]	-
dtype	DataType?	-

---

From

Create a Series from a list of objects, primitives, or nested lists. Uses SeriesFactory to automatically select the fastest path (SIMD for Arrays, Reflection for Lists).

Create Series from array

Create Series from 2D matrix

public static Series From<T>(string name, IEnumerable<T> data)
public static Series From<T>(string name, T[] data)
public static Series From<T>(string name, T[,] data)

Parameters

Name	Type	Description
name	string	-
data	IEnumerable<T> / T[] / T[,]	-

---

FromArrow

Low-level entry point: Create Series from existing Arrow Array.

public static Series FromArrow(string name, IArrowArray arrowArray)

Parameters

Name	Type	Description
name	string	-
arrowArray	IArrowArray	-

---

FromExpr

Create Series From single column expression.

public static Series FromExpr(Expr expr)

Parameters

Name	Type	Description
expr	Expr	-

---

FromSpan

Create Series from ReadOnlySpan

public static Series FromSpan<T>(string name, ReadOnlySpan<T> data)

Parameters

Name	Type	Description
name	string	-
data	ReadOnlySpan<T>	-

---

FromTensor

Converts an N-Dimensional .NET Tensor into a Polars Series. Automatically infers the rank and dynamically wraps the data into Polars native types: - 1D Tensors map to flat primitive columns (e.g., Float32, Int32). - N-D Tensors map to nested Array columns (e.g., Array[f32, (H, W)]).

public static Series FromTensor<T>(string name, ReadOnlyTensorSpan<T> tensor)

Parameters

Name	Type	Description
name	string	The column name for the newly created Series.
tensor	ReadOnlyTensorSpan<T>	The source TensorSpan. Supports sliced and transposed views safely.

Returns: A new Polars Series instance encapsulating the tensor data.

NOTE

For memory safety against non-contiguous tensor views (like transpositions), this method performs a memory materialization (Flatten) before mapping to Arrow's C Data Interface.

---

Operators

operator + (Addition)

Add Series

public static Series operator +(Series left, Series right)
public static Series operator +(Series left, IntoExpr right)
public static Series operator +(IntoExpr left, Series right)

Parameters

Name	Type	Description
left	Series / IntoExpr	-
right	Series / IntoExpr	-

---

operator / (Division)

Divide Series

public static Series operator /(Series left, Series right)
public static Series operator /(Series left, IntoExpr right)
public static Series operator /(IntoExpr left, Series right)

Parameters

Name	Type	Description
left	Series / IntoExpr	-
right	Series / IntoExpr	-

---

operator == (Equality)

public static Series operator ==(Series left, Series right)
public static Series operator ==(Series left, IntoExpr right)
public static Series operator ==(IntoExpr left, Series right)

Parameters

Name	Type	Description
left	Series / IntoExpr	-
right	Series / IntoExpr	-

---

operator ^ (Exclusive OR)

Exponentiation Series

public static Series operator ^(Series left, Series right)

Parameters

Name	Type	Description
left	Series	-
right	Series	-

---

operator > (Greater Than)

Compare whether left series is greater than right series

public static Series operator >(Series left, Series right)
public static Series operator >(Series left, IntoExpr right)
public static Series operator >(IntoExpr left, Series right)

Parameters

Name	Type	Description
left	Series / IntoExpr	-
right	Series / IntoExpr	-

---

operator >= (Greater Or Equal)

Compare whether left series is greater than or equal to right series

public static Series operator >=(Series left, Series right)
public static Series operator >=(Series left, IntoExpr right)
public static Series operator >=(IntoExpr left, Series right)

Parameters

Name	Type	Description
left	Series / IntoExpr	-
right	Series / IntoExpr	-

---

operator != (Inequality)

public static Series operator !=(Series left, Series right)
public static Series operator !=(Series left, IntoExpr right)
public static Series operator !=(IntoExpr left, Series right)

Parameters

Name	Type	Description
left	Series / IntoExpr	-
right	Series / IntoExpr	-

---

operator << (Left Shift)

Bitwise left shift operation.

public static Series operator <<(Series left, int right)

Parameters

Name	Type	Description
left	Series	-
right	int	-

---

operator < (Less Than)

Compare whether left series is less than right series

public static Series operator <(Series left, Series right)
public static Series operator <(Series left, IntoExpr right)
public static Series operator <(IntoExpr left, Series right)

Parameters

Name	Type	Description
left	Series / IntoExpr	-
right	Series / IntoExpr	-

---

operator <= (Less Or Equal)

Compare whether left series is less than or equal to right series

public static Series operator <=(Series left, Series right)
public static Series operator <=(Series left, IntoExpr right)
public static Series operator <=(IntoExpr left, Series right)

Parameters

Name	Type	Description
left	Series / IntoExpr	-
right	Series / IntoExpr	-

---

operator ! (Logical NOT)

public static Series operator !(Series booleanSeries)

Parameters

Name	Type	Description
booleanSeries	Series	-

---

operator % (Modulus)

Mod Series

public static Series operator %(Series left, Series right)

Parameters

Name	Type	Description
left	Series	-
right	Series	-

---

operator * (Multiply)

Multiple Series

public static Series operator *(Series left, Series right)
public static Series operator *(Series left, IntoExpr right)
public static Series operator *(IntoExpr left, Series right)

Parameters

Name	Type	Description
left	Series / IntoExpr	-
right	Series / IntoExpr	-

---

operator ~ (Bitwise NOT)

public static Series operator ~(Series booleanSeries)

Parameters

Name	Type	Description
booleanSeries	Series	-

---

operator >> (Right Shift)

Bitwise right shift operation.

For signed integers, this is arithmetic shift. For unsigned integers, this is logical shift.

public static Series operator >>(Series left, int right)

Parameters

Name	Type	Description
left	Series	-
right	int	-

---

operator - (Subtraction)

Minus Series

public static Series operator -(Series left, Series right)
public static Series operator -(Series left, IntoExpr right)
public static Series operator -(IntoExpr left, Series right)

Parameters

Name	Type	Description
left	Series / IntoExpr	-
right	Series / IntoExpr	-

---

Instance Methods

Abs

Calculate absolute value.

public Series Abs()

---

Alias

Rename Series. Same as Rename.

public Series Alias(string newName)

Parameters

Name	Type	Description
newName	string	-

---

All

Check if all values in the boolean expression are true.

This is a boolean aggregation.

public bool? All(bool ignoreNulls = false)

Parameters

Name	Type	Description
ignoreNulls	bool	If true, null values are ignored. If false (default), the result propagates nulls (i.e., if there is a null and no false, the result might be null).

---

Any

Check if any value in the boolean expression is true.

This is a boolean aggregation.

public bool? Any(bool ignoreNulls = false)

Parameters

Name	Type	Description
ignoreNulls	bool	If true, null values are ignored. If false (default), the result propagates nulls.

---

Append

Append a Series to this one. The resulting series will consist of multiple chunks.

public Series Append(Series other)

Parameters

Name	Type	Description
other	Series	Series to append.

---

ApproxNUnique

Get an approximation of the number of unique values in this Series. Uses HyperLogLog algorithm for fast, memory-efficient counting.

public long ApproxNUnique()

Returns: Approximate count of unique values.

---

ArcCos

Compute the element-wise inverse cosine.

public Series ArcCos()

---

ArcCosh

Compute the element-wise inverse hyperbolic cosine.

public Series ArcCosh()

---

ArcSin

Compute the element-wise inverse sine.

public Series ArcSin()

---

ArcSinh

Compute the element-wise inverse hyperbolic sine.

public Series ArcSinh()

---

ArcTan

Compute the element-wise inverse tangent.

public Series ArcTan()

---

ArcTanh

Compute the element-wise inverse hyperbolic tangent.

public Series ArcTanh()

---

ArgMax

Get the index of the maximum value. Returns null if the Series is empty or contains only null values.

public long? ArgMax()

---

ArgMin

Get the index of the minimum value. Returns null if the Series is empty or contains only null values.

public long? ArgMin()

---

ArgSort

Get the index values that would sort this expression.

public Series ArgSort(bool descending = false, bool nullsLast = false)

Parameters

Name	Type	Description
descending	bool	If true, sort in descending order. Default is false.
nullsLast	bool	If true, place null values last. Default is false.

---

ArgTrue

Get index values where Boolean Series evaluate True.

public Series ArgTrue()

Returns: Series of data type UInt32.

---

ArgUnique

Get the index of the unique values.

public Series ArgUnique()

---

As

Returns a zero-allocation stack enumerator for strongly-typed iteration. Usage: foreach (int val in series.As{int}())

public SeriesEnumerator<T> As<T>()

---

AsDangerousUnmanagedTensor

Extracts the raw unmanaged pointer and shape metadata of the underlying physical Arrow memory. Designed for zero-copy integrations with native C++ Machine Learning backends like ONNX Runtime or TorchSharp.

Extracts the raw unmanaged pointer and reshapes the metadata for native ML backends.

public (IntPtr, long[]) AsDangerousUnmanagedTensor<T>()
public (IntPtr, long[]) AsDangerousUnmanagedTensor<T>(ReadOnlySpan<IntPtr> shape)

Parameters

Name	Type	Description
shape	ReadOnlySpan<IntPtr>	The target tensor shape. Total elements must strictly match the memory length.

Returns: A tuple containing the raw System.IntPtr to the first element, and a long[] representing the tensor shape.

NOTE

DANGER (LIFECYCLE WARNING): This is a zero-copy operation. The returned System.IntPtr points directly to native memory managed by the Rust Polars engine. It is ONLY valid as long as this Series instance remains alive. You MUST ensure the Series is not garbage collected or explicitly disposed. Considering use GC.KeepAlive(series) while the native pointer is still in use by an external FFI library, otherwise it will result in a fatal segmentation fault.

---

AsReadOnlySpan

Generate zero-copy ReadOnlySpan from a numeric Series.

public ReadOnlySpan<T> AsReadOnlySpan<T>()

Returns: A continuous span over the underlying memory.

---

AsTensor

Deep copies the underlying Arrow memory into a managed .NET System.Numerics.Tensors.Tensor on the garbage-collected heap. Automatically infers the rank and dimensions: 1D data is promoted to a [N, 1] column vector, while 2D nested data becomes an [N, M] matrix.

Deep copies the underlying Arrow memory into a managed .NET System.Numerics.Tensors.Tensor with an explicit N-dimensional shape.

public Tensor<T> AsTensor<T>()
public Tensor<T> AsTensor<T>(ReadOnlySpan<IntPtr> shape)

Parameters

Name	Type	Description
shape	ReadOnlySpan<IntPtr>	The target dimensions. The total number of elements must match the underlying Arrow memory length.

Returns: A new managed System.Numerics.Tensors.Tensor containing the copied data. / A new managed System.Numerics.Tensors.Tensor reshaped to the specified dimensions.

NOTE

Unlike Series.AsTensorSpan, this method allocates memory and performs a safe physical copy. The returned Tensor is completely independent of the Polars engine, making it safe to pass across threads or await inside asynchronous (async/Task) workflows. This method performs a safe physical copy to the managed heap. It is highly useful when reshaping flat or nested Arrow arrays into higher-dimensional structures (e.g., 3D/4D image batches like [Batch, Channel, Height, Width]) required by Machine Learning models.

---

AsTensorSpan

Generates a zero-copy Tensor representation from the Series. Automatically infers the shape: - 1D [Rows] for flat numeric columns. - 2D [Rows, ListSize] for List/Array columns (Perfect for Embeddings or Feature Matrices).

Generates a zero-copy N-Dimensional Tensor representation from the Series. Allows explicit reshaping of the underlying memory (e.g., for 3D/4D image matrices).

public ReadOnlyTensorSpan<T> AsTensorSpan<T>()
public ReadOnlyTensorSpan<T> AsTensorSpan<T>(ReadOnlySpan<IntPtr> shape)

Parameters

Name	Type	Description
shape	ReadOnlySpan<IntPtr>	The desired dimensions. Total elements must match the underlying memory.

Returns: A ReadOnlyTensorSpan representing the underlying Arrow memory. / A reshaped ReadOnlyTensorSpan representing the underlying Arrow memory.

---

AsTransposedTensorSpan

Generates a zero-copy, transposed 2D Tensor representation from a List or Array Series. By manipulating memory strides, it returns an (N x M) view of an (M x N) matrix without moving bytes.

public ReadOnlyTensorSpan<T> AsTransposedTensorSpan<T>()

Returns: A transposed System.Numerics.Tensors.ReadOnlyTensorSpan pointing to the original Arrow memory.

NOTE

This is useful when bridging with external Machine Learning libraries (like ONNX or native C++ math backends) that expect Column-Major order or specifically require a transposed matrix.

---

BackwardFill

Fill null values with a specific strategy (Backward).

public Series BackwardFill(uint limit = 0)

Parameters

Name	Type	Description
limit	uint	Max number of consecutive nulls to fill. (Default null = infinite)

---

BitwiseAnd

Perform an aggregation of bitwise ANDs.

Perform an aggregation of bitwise ANDs across all elements.

public Series BitwiseAnd()
public T? BitwiseAnd<T>()

---

BitwiseCountOnes

Evaluate the number of set bits.

public Series BitwiseCountOnes()

---

BitwiseCountZeros

Evaluate the number of unset bits.

public Series BitwiseCountZeros()

---

BitwiseLeadingOnes

Evaluate the number most-significant set bits before seeing an unset bit.

public Series BitwiseLeadingOnes()

---

BitwiseLeadingZeros

Evaluate the number most-significant unset bits before seeing a set bit.

public Series BitwiseLeadingZeros()

---

BitwiseOr

Perform an aggregation of bitwise Ors.

Perform an aggregation of bitwise ORs across all elements.

public Series BitwiseOr()
public T? BitwiseOr<T>()

---

BitwiseTrailingOnes

Evaluate the number least-significant set bits before seeing an unset bit.

public Series BitwiseTrailingOnes()

---

BitwiseTrailingZeros

Evaluate the number least-significant unset bits before seeing a set bit.

public Series BitwiseTrailingZeros()

---

BitwiseXor

Perform an aggregation of bitwise Xors.

Perform an aggregation of bitwise XORs across all elements.

public Series BitwiseXor()
public T? BitwiseXor<T>()

---

BottomK

Get the bottom k values.

public Series BottomK(int k)

Parameters

Name	Type	Description
k	int	-

---

BottomKBy

Get the bottom k rows according to the sorting criteria defined by by.

Get the bottom k values sorted by another Series.

public Series BottomKBy(int k, Expr[] by, bool[] reverse)
public Series BottomKBy(int k, Expr by, bool reverse = false)
public Series BottomKBy(int k, Series by, bool reverse = false)

Parameters

Name	Type	Description
k	int	Number of rows to return.
by	Expr[] / Series	The expressions (columns) to sort by.
reverse	bool[]	Controls the sorting direction for each expression in by. For BottomK: - false (default): Sorts ascending (picks smallest values). - true: Sorts descending (picks largest values, acting like TopK for this column). Length must match by.

Returns: A new Series containing the bottom k elements.

---

Cast

Cast Series to another DataType.

Cast the series to a specific .NET type.

public Series Cast(DataType dtype, bool strict = true, bool wrapNumerical = false)
public Series Cast<T>(bool strict = true, bool wrapNumerical = false)

Parameters

Name	Type	Description
dtype	DataType	The target type (can be Polars DataType or .NET Type)
strict	bool	Throws an error if conversion had overflows.
wrapNumerical	bool	Allows wrapping numerical overflow.

Returns: A new Series of the target type.

---

Cbrt

Calculate the cube root of the expression.

public Series Cbrt()

---

Ceil

Rounds up to the nearest integer.

public Series Ceil()

---

ChunkLengths

Get the length of each individual chunk.

public long[] ChunkLengths()

---

Clear

Create an empty copy of the current Series, with zero to ‘n’ elements. The copy has an identical name/dtype, but no data.

public Series Clear(uint n = 0)

Parameters

Name	Type	Description
n	uint	-

---

Clip

Set values outside the given boundaries to the boundary value.

public Series Clip(IntoExprColumn? lowerBound = null, IntoExprColumn? upperBound = null)

Parameters

Name	Type	Description
lowerBound	IntoExprColumn?	Lower bound. Accepts expression input. Non-expression inputs are parsed as literals. Strings are parsed as column names.
upperBound	IntoExprColumn?	Upper bound. Accepts expression input. Non-expression inputs are parsed as literals. Strings are parsed as column names.

---

Clone

Clone the Series

public Series Clone()

---

Cos

Compute the element-wise cosine.

public Series Cos()

---

Cosh

Compute the element-wise hyperbolic cosine.

public Series Cosh()

---

Cot

Compute the element-wise value for the cotangent.

public Series Cot()

---

Count

Return the number of non-null elements in the column.

public long Count()

Returns: A new Series containing the count of non-null values.

---

CumCount

Get an array with the cumulative count computed at every element.

public Series CumCount(bool reverse = false)

Parameters

Name	Type	Description
reverse	bool	Reverse the operation.

Returns: A new Series with the cumulative count.

---

CumMax

Get an array with the cumulative max computed at every element.

public Series CumMax(bool reverse = false)

Parameters

Name	Type	Description
reverse	bool	Reverse the operation.

Returns: A new Series with the cumulative maximum.

---

CumMin

Get an array with the cumulative min computed at every element.

public Series CumMin(bool reverse = false)

Parameters

Name	Type	Description
reverse	bool	Reverse the operation.

Returns: A new Series with the cumulative minimum.

---

CumProd

Get an array with the cumulative prod computed at every element.

public Series CumProd(bool reverse = false)

Parameters

Name	Type	Description
reverse	bool	Reverse the operation.

Returns: A new Series with the cumulative product.

---

CumSum

Get an array with the cumulative sum computed at every element.

public Series CumSum(bool reverse = false)

Parameters

Name	Type	Description
reverse	bool	Reverse the operation.

Returns: A new Series with the cumulative sum.

---

CumulativeEval

Run an expression over a sliding window that increases 1 slot every iteration. This can be really slow as it can have O(n^2) complexity. Don’t use this for operations that visit all elements.

public Series CumulativeEval(Expr expr, int minSamples = 1)

Parameters

Name	Type	Description
expr	Expr	Expression to evaluate
minSamples	int	Number of valid values there should be in the window before the expression is evaluated. valid values = length - null_count

---

Cut

Bin continuous values into discrete categories.

public Series Cut(
    ReadOnlySpan<double> breaks,
    string[]? labels = null,
    bool leftClosed = false,
    bool includeBreaks = false
)

Parameters

Name	Type	Description
breaks	ReadOnlySpan<double>	List of unique cut points.
labels	string[]?	Names of the categories. The number of labels must be equal to the number of cut points plus one.
leftClosed	bool	Set the intervals to be left-closed instead of right-closed.
includeBreaks	bool	Include a column with the right endpoint of the bin each observation falls in. This will change the data type of the output from an Enum to a Struct.

Returns: Expression/Series of data type Enum if include_breaks is set to False (default), otherwise an expression of data type Struct.

---

Describe

Generate a summary statistics DataFrame (count, mean, std, min, 25%, 50%, 75%, max). Similar to pandas/polars describe().

public DataFrame Describe()

---

Diff

Calculate the difference with the previous value (n-th lag).

public Series Diff(long n = 1)

Parameters

Name	Type	Description
n	long	-

---

Dot

Compute the dot/inner product between two Series.

The behavior is equivalent to (this * other).Sum().

Compute the dot/inner product and return the scalar value directly.

public Series Dot(Series other)
public T Dot<T>(Series other)

Parameters

Name	Type	Description
other	Series	The other Series to compute the dot product with.

Returns: A Series of length 1 containing the result. / The dot product value.

---

DropNans

Drop Nan Values

public Series DropNans()

---

DropNulls

Drop Null Values

public Series DropNulls()

---

Entropy

Computes the entropy. Uses the formula -sum(pk * log(pk)) where pk are discrete probabilities.

public double? Entropy(double baseVal = 2.718281828459045, bool normalize = true)

Parameters

Name	Type	Description
baseVal	double	Given base, defaults to e
normalize	bool	Normalize pk if it doesn’t sum to 1.

---

Eq

Compare whether two Series is equal

public Series Eq(Series other)

Parameters

Name	Type	Description
other	Series	-

---

EqMissing

Compare whether two Series is equal,This differs from the standard eq where null values are propagated.

public Series EqMissing(Series other)

Parameters

Name	Type	Description
other	Series	-

---

EstimatedSize

Return an estimation of the total (heap) allocated size of the Series/DataFrame. Estimated size is given in the specified unit (bytes by default).

public double EstimatedSize(SizeUnit unit = SizeUnit.Bytes)

Parameters

Name	Type	Description
unit	SizeUnit	Scale the returned size to the given unit (uses 1024 base).

Returns: The estimated size as a double.

---

EwmMean

Compute exponentially-weighted moving average.

public Series EwmMean(
    double alpha,
    bool adjust = true,
    bool bias = true,
    int minPeriods = 1,
    bool ignoreNulls = false
)

Parameters

Name	Type	Description
alpha	double	Specify smoothing factor alpha directly. Constraint: 0 < alpha <= 1
adjust	bool	If true, divide by decaying adjustment factor in beginning periods to account for imbalance in relative weightings (viewing data as finite history). If false, assume infinite history.
bias	bool	If true, use a biased estimator (Standard deviation uses N in denominator). If false, use an unbiased estimator (Standard deviation uses N-1). Note: This is primarily relevant for Variance/StdDev. For Mean, it typically defaults to true.
minPeriods	int	Minimum number of observations in window required to have a value (otherwise result is null).
ignoreNulls	bool	Ignore missing values when calculating weights.

Returns: A new Series with the EWM mean.

---

EwmMeanBy

Compute exponentially-weighted moving average based on a temporal or index column.

public Series EwmMeanBy(Expr by, string halfLife)

Parameters

Name	Type	Description
by	Expr	The column used to determine the distance between observations. Supported data types: Date, DateTime, UInt64, UInt32, Int64, or Int32.
halfLife	string	The unit over which an observation decays to half its value. Supported string formats: - Time unitsns (nanosecond), us (microsecond), ms (millisecond), s (second), m (minute), h (hour), d (day), w (week). - Index unitsi (index count). Example: "2i" means decay by half every 2 index steps. - CompoundExample: "3d12h4m25s". Warning:halfLife is treated as a constant duration. Calendar durations such as months (mo) or years (y) are NOT supported because they vary in length. Please express such durations in hours (e.g. use '730h' instead of '1mo').

Returns: A new Series with the time/index-based EWM mean.

---

EwmStd

Compute exponentially-weighted moving standard deviation.

public Series EwmStd(
    double alpha,
    bool adjust = true,
    bool bias = true,
    int minPeriods = 1,
    bool ignoreNulls = false
)

Parameters

Name	Type	Description
alpha	double	Specify smoothing factor alpha directly. Constraint: 0 < alpha <= 1
adjust	bool	If true, divide by decaying adjustment factor in beginning periods to account for imbalance in relative weightings (viewing data as finite history). If false, assume infinite history.
bias	bool	If true, use a biased estimator (Standard deviation uses N in denominator). If false, use an unbiased estimator (Standard deviation uses N-1). Note: This is primarily relevant for Variance/StdDev. For Mean, it typically defaults to true.
minPeriods	int	Minimum number of observations in window required to have a value (otherwise result is null).
ignoreNulls	bool	Ignore missing values when calculating weights.

Returns: A new Series with the EWM standard deviation.

---

EwmSum

Compute exponentially-weighted moving sum.

public Series EwmSum(
    double alpha,
    bool adjust = true,
    bool bias = true,
    int minPeriods = 1,
    bool ignoreNulls = false
)

Parameters

Name	Type	Description
alpha	double	Specify smoothing factor alpha directly. Constraint: 0 < alpha <= 1
adjust	bool	If true, divide by decaying adjustment factor in beginning periods to account for imbalance in relative weightings (viewing data as finite history). If false, assume infinite history.
bias	bool	If true, use a biased estimator (Standard deviation uses N in denominator). If false, use an unbiased estimator (Standard deviation uses N-1). Note: This is primarily relevant for Variance/StdDev. For Mean, it typically defaults to true.
minPeriods	int	Minimum number of observations in window required to have a value (otherwise result is null).
ignoreNulls	bool	Ignore missing values when calculating weights.

Returns: A new Series with the EWM sum.

---

EwmSumBy

Compute time-based exponentially-weighted moving sum.

public Series EwmSumBy(Expr by, string halfLife)

Parameters

Name	Type	Description
by	Expr	Column to use as reference for the time decay.
halfLife	string	Half-life of the exponential decay.

Returns: A new Series with the time/index-based EWM sum.

---

EwmVar

Compute exponentially-weighted moving variance.

public Series EwmVar(
    double alpha,
    bool adjust = true,
    bool bias = true,
    int minPeriods = 1,
    bool ignoreNulls = false
)

Parameters

Name	Type	Description
alpha	double	Specify smoothing factor alpha directly. Constraint: 0 < alpha <= 1
adjust	bool	If true, divide by decaying adjustment factor in beginning periods to account for imbalance in relative weightings (viewing data as finite history). If false, assume infinite history.
bias	bool	If true, use a biased estimator (Standard deviation uses N in denominator). If false, use an unbiased estimator (Standard deviation uses N-1). Note: This is primarily relevant for Variance/StdDev. For Mean, it typically defaults to true.
minPeriods	int	Minimum number of observations in window required to have a value (otherwise result is null).
ignoreNulls	bool	Ignore missing values when calculating weights.

Returns: A new Series with the EWM variance.

---

Exp

Calculate the power of the Euler's number.

public Series Exp()

---

Explode

Explode a list column into multiple rows. The resulting Series will be longer than the original.

public Series Explode(bool emptyAsNull = true, bool keepNulls = true)

Parameters

Name	Type	Description
emptyAsNull	bool	-
keepNulls	bool	-

---

Extend

Extend the memory backed by this Series with the values from another. Different from append, which adds the chunks from other to the chunks of this series, extend appends the data from other to the underlying memory locations and thus may cause a reallocation (which is expensive). If this does not cause a reallocation, the resulting data structure will not have any extra chunks and thus will yield faster queries.

public Series Extend(Series other)

Parameters

Name	Type	Description
other	Series	Series to extend the series with.

---

ExtendConstant

Extremely fast method for extending the Series with ‘n’ copies of a value.

public Series ExtendConstant(IntoExpr value, Expr n)

Parameters

Name	Type	Description
value	IntoExpr	A constant literal value or a unit expression with which to extend the expression result Series; can pass None to extend with nulls.
n	Expr	The number of additional values that will be added.

---

FillNan

Fill floating point NaN values with a specified value. This is different from FillNull. It only handles IEEE 754 NaN.

public Series FillNan(IntoExpr value)

Parameters

Name	Type	Description
value	IntoExpr	-

---

FillNull

Fill null values using the specified value

Fill null values using the specified strategy

public Series FillNull(IntoExpr value)
public Series FillNull(FillNullStrategy strategy, uint? limit = null)

Parameters

Name	Type	Description
value	IntoExpr	Value used to fill null values.
strategy	FillNullStrategy	Strategy used to fill null values.
limit	uint?	Number of consecutive null values to fill when using the ‘forward’ or ‘backward’ strategy.

---

Filter

Filter a series using a boolean series.

public Series Filter(Series predicate)
public Series Filter(IEnumerable<bool> predicate)

Parameters

Name	Type	Description
predicate	Series / IEnumerable<bool>	-

---

First

Get the first value of the group/series.

First series into scalar

public Series First()
public T? First<T>()

Returns: A new Series containing the first value (length 1).

---

Floor

Rounds down to the nearest integer.

public Series Floor()

---

ForwardFill

Fill null values with a specific strategy (Forward).

public Series ForwardFill(uint limit = 0)

Parameters

Name	Type	Description
limit	uint	Max number of consecutive nulls to fill. (Default null = infinite)

---

FromEpoch

Parses an integer Series into a Datetime or Date Series.

public Series FromEpoch(EpochTimeUnit timeUnit = EpochTimeUnit.Second)

Parameters

Name	Type	Description
timeUnit	EpochTimeUnit	-

---

Gather

Gather values by an index expression.

Take elements by physical integer indices. Negative indices are not supported. All values must be >= 0.

public Series Gather(IntoExprColumn indices)
public Series Gather(ReadOnlySpan<int> indices)

Parameters

Name	Type	Description
indices	IntoExprColumn / ReadOnlySpan<int>	-

---

GatherEvery

Take every nth value starting from an offset.

public Series GatherEvery(ulong n, ulong offset = 0)

Parameters

Name	Type	Description
n	ulong	-
offset	ulong	-

---

Get

Get a single value by index. Returns a scalar.

public Series Get(Expr index, bool nullOnOutOfBounds = false)
public Series Get(ulong index, bool nullOnOutOfBounds = false)

Parameters

Name	Type	Description
index	Expr / ulong	The index expression.
nullOnOutOfBounds	bool	If true, returns Null when the index is out of bounds instead of raising an error.

---

GetValue

Get an item at the specified index.

public T GetValue<T>(long index, bool uncheck = false)

Parameters

Name	Type	Description
index	long	-
uncheck	bool	-

---

Gt

Compare whether left series is greater than right series

public Series Gt(Series other)

Parameters

Name	Type	Description
other	Series	-

---

GtEq

Compare whether left series is greater than or equal to right series

public Series GtEq(Series other)

Parameters

Name	Type	Description
other	Series	-

---

HasNulls

Check whether the Series contains one or more null values.

public bool HasNulls()

---

Hash

Hash the elements in the selection.The hash value is of type UInt64.

public Series Hash(
    ulong seed = 0,
    ulong? seed1 = null,
    ulong? seed2 = null,
    ulong? seed3 = null
)

Parameters

Name	Type	Description
seed	ulong	Random seed parameter. Defaults to 0.
seed1	ulong?	Random seed parameter. Defaults to seed if not set.
seed2	ulong?	Random seed parameter. Defaults to seed if not set.
seed3	ulong?	Random seed parameter. Defaults to seed if not set.

---

Hist

Bin values into buckets and count their occurrences.

public DataFrame Hist(
    IntoExpr? bins = null,
    int? binCount = null,
    bool includeCategory = true,
    bool includeBreakPoint = true
)

Parameters

Name	Type	Description
bins	IntoExpr?	Bin edges. If None given, we determine the edges based on the data.
binCount	int?	If bins is not provided, binCount uniform bins are created that fully encompass the data.
includeCategory	bool	Include a column that indicates the upper breakpoint.
includeBreakPoint	bool	Include a column that shows the intervals as categories.

---

Implode

Aggregate values into a list. Result is a Series with 1 row containing a List of all values.

public Series Implode()

---

IndexOf

Find the index of the first occurrence of a specific value.

public int? IndexOf(IntoExpr element)

Parameters

Name	Type	Description
element	IntoExpr	The element expression to search for.

---

Interpolate

Interpolate intermediate values.

public Series Interpolate(InterpolationMethod method = InterpolationMethod.Linear)

Parameters

Name	Type	Description
method	InterpolationMethod	Interpolation method (Linear or Nearest).

---

InterpolateBy

Interpolate intermediate values based on the values of another Series.

Useful for linear interpolation across unevenly spaced data.

public Series InterpolateBy(IntoExprColumn by)

Parameters

Name	Type	Description
by	IntoExprColumn	The Series to use for interpolation (e.g. timestamps).

Returns: A new Series with interpolated values.

---

IsBetween

Check if values are between lower and upper bounds.

public Series IsBetween(object lower, object upper, ClosedInterval closedInterval = ClosedInterval.Both)
public Series IsBetween(Expr lower, Expr upper, ClosedInterval closedInterval = ClosedInterval.Both)

Parameters

Name	Type	Description
lower	object / Expr	-
upper	object / Expr	-
closedInterval	ClosedInterval	-

---

IsClose

Check if this expression is close, i.e. almost equal, to the other expression.

public Series IsClose(
    IntoExprColumn other,
    double absTol = 0,
    double relTol = 1E-09,
    bool nansEqual = false
)

Parameters

Name	Type	Description
other	IntoExprColumn	A literal or expression value to compare with.
absTol	double	Absolute tolerance. This is the maximum allowed absolute difference betweentwo values. Must be non-negative.
relTol	double	Relative tolerance. This is the maximum allowed difference between two values, relative to the larger absolute value. Must be non-negative.
nansEqual	bool	Whether NaN values should be considered equal.

Returns: Expression/Series of data type Boolean.

---

IsDuplicated

Get a boolean mask indicating which values are duplicated.

Implemented via DataFrame expression composition.

public Series IsDuplicated()

---

IsEmpty

True if the Series is empty.

public bool IsEmpty(bool ignoreNulls = false)

Parameters

Name	Type	Description
ignoreNulls	bool	-

---

IsFinite

Check whether this series is finite

public Series IsFinite()

---

IsFirstDistinct

Return a boolean mask indicating the first occurrence of each distinct value.

public Series IsFirstDistinct()

---

IsIn

Check if elements of this Series are in the other Series.

Check if elements of this Series are in the collections.

public Series IsIn(Series other, bool nullsEqual = false)
public Series IsIn<T>(IEnumerable<T> collection, bool nullsEqual = false)

Parameters

Name	Type	Description
other	Series	-
nullsEqual	bool	-
collection	IEnumerable<T>	-

---

IsInfinite

Check whether this series is infinite

public Series IsInfinite()

---

IsLastDistinct

Return a boolean mask indicating the last occurrence of each distinct value.

public Series IsLastDistinct()

---

IsNan

Check whether this series is NaN

public Series IsNan()

---

IsNotNan

Check whether this series is not NaN

public Series IsNotNan()

---

IsNotNull

Return a Boolean series, where null value will be masked as false.

public Series IsNotNull()

---

IsNull

Return a Boolean series, where null value will be masked as true.

public Series IsNull()

---

IsNullAt

Check whether indexed value is null。

public bool IsNullAt(long index, bool uncheck = false)

Parameters

Name	Type	Description
index	long	-
uncheck	bool	-

---

IsSorted

Checks if the Series is sorted according to the given rules. If the metadata flag matches, returns O(1). Otherwise, scans the data O(N).

public bool IsSorted(bool descending = false, bool nullsLast = false)

Parameters

Name	Type	Description
descending	bool	-
nullsLast	bool	-

---

IsUnique

Get a boolean mask indicating which values are unique.

Implemented via DataFrame expression composition.

public Series IsUnique()

---

Kurtosis

Compute the kurtosis (Fisher or Pearson) of a dataset.

public double? Kurtosis(bool fisher = true, bool bias = true)

Parameters

Name	Type	Description
fisher	bool	If True, Fisher’s definition is used (normal ==> 0.0). If False, Pearson’s definition is used (normal ==> 3.0).
bias	bool	If False, the calculations are corrected for statistical bias.

Returns: A series which length is 1

---

Last

Get the last value of the group/series.

Last series into scalar

public Series Last()
public T? Last<T>()

Returns: A new Series containing the last value (length 1).

---

Len

Return the length of the Series.

public long Len()

---

Ln

public Series Ln()

---

Log

Compute the logarithm to a given base,defaults to e.

public Series Log(Expr baseVal)
public Series Log()

Parameters

Name	Type	Description
baseVal	Expr	Given base, defaults to e

---

Log10

Compute the base 10 logarithm of the input array, element-wise.

public Series Log10()

---

Log1p

Compute the natural logarithm of each element plus one.This computes log(1 + x) but is more numerically stable for x close to zero.

public Series Log1p()

---

LowerBound

Return the lower bound of this Series’ dtype as a unit Series.

public Series LowerBound()

---

Lt

Compare whether left series is less than right series

public Series Lt(Series other)

Parameters

Name	Type	Description
other	Series	-

---

LtEq

Compare whether left series is less than or equal to right series

public Series LtEq(Series other)

Parameters

Name	Type	Description
other	Series	-

---

Map

Apply a custom C# function to the series (element-wise).

Warning: This is slower than native expressions because it runs in the .NET runtime.

Apply a raw Arrow-to-Arrow UDF.

public Series Map<TInput, TOutput>(Func<TInput, TOutput> function)
public Series Map(Func<IArrowArray, IArrowArray> function, DataType outputType)

Parameters

Name	Type	Description
function	Func<TInput, TOutput> / Func<IArrowArray, IArrowArray>	-
outputType	DataType	-

---

Max

Max series into 1 length series(Scalar)

Max series into scalar

public Series Max()
public T? Max<T>()

---

MaxBy

Get the maximum value in this Series, ordered by an expression.

public Series MaxBy(IntoExprColumn by)
public T? MaxBy<T>(IntoExprColumn by)

Parameters

Name	Type	Description
by	IntoExprColumn	Column used to determine the largest element. Accepts expression input.

---

Mean

Mean series into 1 length series(Scalar)

Mean series into scalar

public Series Mean()
public T? Mean<T>()

---

Median

Get the median value.

public T? Median<T>()

---

Min

Min series into 1 length series(Scalar)

Min series into scalar

public Series Min()
public T? Min<T>()

---

MinBy

Get the minimum value in this Series, ordered by an expression.

public Series MinBy(IntoExprColumn by)
public T? MinBy<T>(IntoExprColumn by)

Parameters

Name	Type	Description
by	IntoExprColumn	Column used to determine the largest element. Accepts expression input.

---

Mode

Compute the most occurring value(s).Can return multiple Values.

public Series Mode(bool maintainOrder = false)

Parameters

Name	Type	Description
maintainOrder	bool	Maintain order of data. This requires more work.

---

NUnique

Count the number of unique values in this Series.

public long NUnique()

---

NanMax

Get maximum value, but propagate/poison encountered NaN values.

public T? NanMax<T>()

---

NanMaxString

Get maximum value, but propagate/poison encountered NaN values.

public string NanMaxString()

---

NanMin

Get minimum value, but propagate/poison encountered NaN values.

public T? NanMin<T>()

---

NanMinString

Get minimum value, but propagate/poison encountered NaN values.

public string NanMinString()

---

Neq

Compare whether two Series is not equal

public Series Neq(Series other)

Parameters

Name	Type	Description
other	Series	-

---

NeqMissing

Compare whether two Series is not equal,This differs from the standard neq where null values are propagated.

public Series NeqMissing(Series other)

Parameters

Name	Type	Description
other	Series	-

---

NewFromIndex

Create a new Series filled with values from the given index.

public Series NewFromIndex(long index, long length)

Parameters

Name	Type	Description
index	long	-
length	long	-

---

Not

Bitwise NOT operator

public Series Not()

---

PctChange

Computes percentage change between values. Percentage change (as fraction) between current element and most-recent non-null element at least n period(s) before the current element. Computes the change from the previous row by default.

public Series PctChange(int n = 1)

Parameters

Name	Type	Description
n	int	periods to shift for forming percent change.

Returns: A new Series with the percentage change.

---

PeakMax

Get a boolean mask of the local maximum peaks.

public Series PeakMax()

---

PeakMin

Get a boolean mask of the local minimum peaks.

public Series PeakMin()

---

Pow

Calculate exponent value.

Calculate the power of the expression with a given numeric exponent.

Calculate the power of the expression with a given exponent expression.

public Series Pow(double exponent)
public Series Pow(int exponent)
public Series Pow(long exponent)
public Series Pow(float exponent)
public Series Pow(Series exponent)

Parameters

Name	Type	Description
exponent	double / int / long / float / Series	-

---

Product

Product series into 1 length series(Scalar)

Product series into scalar

public Series Product()
public T? Product<T>()

---

QCut

Bin continuous values into discrete categories based on their quantiles.

public Series QCut(
    ReadOnlySpan<double> quantiles,
    string[]? labels = null,
    bool leftClosed = false,
    bool allowDuplicates = false,
    bool includeBreaks = false
)

public Series QCut(
    int quantiles,
    string[]? labels = null,
    bool leftClosed = false,
    bool allowDuplicates = false,
    bool includeBreaks = false
)

Parameters

Name	Type	Description
quantiles	ReadOnlySpan<double> / int	Either a list of quantile probabilities between 0 and 1 or a positive integer determining the number of bins with uniform probability.
labels	string[]?	Names of the categories. The number of labels must be equal to the number of categories.
leftClosed	bool	Set the intervals to be left-closed instead of right-closed.
allowDuplicates	bool	If set to True, duplicates in the resulting quantiles are dropped, rather than raising a DuplicateError. This can happen even with unique probabilities, depending on the data.
includeBreaks	bool	Include a column with the right endpoint of the bin each observation falls in. This will change the data type of the output from a Categorical to a Struct.

Returns: Expression/Series of data type Categorical if include_breaks is set to False (default), otherwise an expression of data type Struct.

---

Quantile

Get the quantile value.

public Series Quantile(double quantile, QuantileMethod method = QuantileMethod.Linear)

Parameters

Name	Type	Description
quantile	double	Quantile between 0.0 and 1.0.
method	QuantileMethod	['nearest’, ‘higher’, ‘lower’, ‘midpoint’, ‘linear’] Interpolation method.

Returns: A new Series containing the quantile value (length 1).

---

Rank

Assign ranks to data, dealing with ties appropriately.

public Series Rank(RankMethod method = RankMethod.Average, bool descending = false, ulong? seed = null)

Parameters

Name	Type	Description
method	RankMethod	The method used to assign ranks to tied elements. See RankMethod for details. Default is RankMethod.Average.
descending	bool	Rank in descending order.
seed	ulong?	If method="random", use this as seed.

Returns: A new Series with the ranks.

---

Rechunk

Reallocates the Series to ensure that all its underlying memory is physically contiguous.

public Series Rechunk()

Returns: A new Series instance backed by contiguous memory.

NOTE

Polars Operations like Appending or Filtering can create fragmented memory chunks. Calling Rechunk() merges these chunks into a single contiguous Arrow array. This is CRITICAL before zero-copy extracting native pointers for Tensors or FFI.

---

Reinterpret

Reinterpret the underlying bits as a signed/unsigned integer. This operation is only allowed for numeric types of the same size. For lower bits numbers, you can safely use the cast operation.

Reinterpret the underlying bits as a signed/unsigned integer or float.

public Series Reinterpret(bool signed = true)
public Series Reinterpret(DataType dtype)
public Series Reinterpret<T>()

Parameters

Name	Type	Description
signed	bool	If True, reinterpret as signed integer. Otherwise, reinterpret as unsigned integer.
dtype	DataType	DataType to reinterpret to.

---

Rename

Rename Series

public Series Rename(string newName)

Parameters

Name	Type	Description
newName	string	-

---

RepeatBy

Repeat the elements in this Series as specified in the given expression. The repeated elements are expanded into a List.

public Series RepeatBy(IntoExpr by)

Parameters

Name	Type	Description
by	IntoExpr	Numeric column that determines how often the values will be repeated. The column will be coerced to UInt32. Give this dtype to make the coercion a no-op.

Returns: Expression/Series of data type List, where the inner data type is equal to the original data type.

---

Replace

Replace the given values by different values of the same data type.

Replace values using a mapping (Dictionary/IEnumerable of KeyValuePair).

Replace values strictly using two sequences (IEnumerable).

public Series Replace(IntoExpr old, IntoExpr newExpr)
public Series Replace<TKey, TValue>(IEnumerable<KeyValuePair<TKey, TValue>> mapping)
public Series Replace<TOld, TNew>(IEnumerable<TOld> oldValues, IEnumerable<TNew> newValues)

Parameters

Name	Type	Description
old	IntoExpr	Value or sequence of values to replace. Accepts expression input. Sequences are parsed as Series, other non-expression inputs are parsed as literals.
newExpr	IntoExpr	Value or sequence of values to replace by. Accepts expression input. Sequences are parsed as Series, other non-expression inputs are parsed as literals.
mapping	IEnumerable<KeyValuePair<TKey, TValue>>	-
oldValues	IEnumerable<TOld>	-
newValues	IEnumerable<TNew>	-

---

ReplaceStrict

Replace all values by different values.

Replace values strictly using a mapping.

Replace values strictly using two sequences (IEnumerable).

public Series ReplaceStrict(
    IntoExpr old,
    IntoExpr newExpr,
    IntoExpr? defaultExpr = null,
    IntoDataTypeExpr? returnDataType = null
)

public Series ReplaceStrict<TKey, TValue>(IEnumerable<KeyValuePair<TKey, TValue>> mapping, IntoExpr? defaultExpr = null, IntoDataTypeExpr? returnDataType = null)
public Series ReplaceStrict<TOld, TNew>(
    IEnumerable<TOld> oldValues,
    IEnumerable<TNew> newValues,
    IntoExpr? defaultExpr = null,
    IntoDataTypeExpr? returnDataType = null
)

Parameters

Name	Type	Description
old	IntoExpr	Value or sequence of values to replace. Accepts expression input. Sequences are parsed as Series, other non-expression inputs are parsed as literals.
newExpr	IntoExpr	Value or sequence of values to replace by. Accepts expression input. Sequences are parsed as Series, other non-expression inputs are parsed as literals. Length must match the length of old or have length 1.
defaultExpr	IntoExpr?	Set values that were not replaced to this value. If no default is specified, (default), an error is raised if any values were not replaced. Accepts expression input. Non-expression inputs are parsed as literals.
returnDataType	IntoDataTypeExpr?	The data type of the resulting expression. If set to null (default), the data type is determined automatically based on the other inputs.
mapping	IEnumerable<KeyValuePair<TKey, TValue>>	-
oldValues	IEnumerable<TOld>	-
newValues	IEnumerable<TNew>	-

---

Reshape

Reshape this Series to a flat Series or an Array Series.

public Series Reshape(ReadOnlySpan<long> dimensions)

Parameters

Name	Type	Description
dimensions	ReadOnlySpan<long>	Tuple of the dimension sizes. If a -1 is used in any of the dimensions, that dimension is inferred.

Returns: Tuple of the dimension sizes. If a -1 is used in any of the dimensions, that dimension is inferred.

---

Reverse

Reverse the selection.

This is useful in a GroupBy context to reverse the order of the group.

public Series Reverse()

Returns: A new Series with the order reversed.

---

Rle

Compress the column data using run-length encoding. Run-length encoding (RLE) encodes data by storing each run of identical values as a single value and its length.

public Series Rle()

Returns: Expression/Series of data type Struct with fields len of data type UInt32 and value of the original data type.

---

RleId

Get a distinct integer ID for each run of identical values. The ID starts at 0 and increases by one each time the value of the column changes.

public Series RleId()

Returns: Expression/Series of data type UInt32.

---

RollingKurtosis

Apply a rolling kurtosis (moving kurtosis) over a window.

public Series RollingKurtosis(
    IntoDuration windowSize,
    int minPeriods = 1,
    double[]? weights = null,
    bool center = false,
    bool fisher = true,
    bool bias = true
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the window formatted as a string duration. Or use .NET TimeSpan directly. Examples: "3i" (3 index rows), "1d" (1 day), "1h" (1 hour).
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
weights	double[]?	Optional weights to apply to the window. The length of the array should match the window size (if using fixed row windows). Default is null (unweighted).
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).
fisher	bool	-
bias	bool	-

Returns: A new Series with the rolling kurtosis.

---

RollingMax

Apply a rolling max (moving max) over a window.

public Series RollingMax(
    IntoDuration windowSize,
    int minPeriods = 1,
    double[]? weights = null,
    bool center = false
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the window formatted as a string duration. Or use .NET TimeSpan directly. Examples: "3i" (3 index rows), "1d" (1 day), "1h" (1 hour).
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
weights	double[]?	Optional weights to apply to the window. The length of the array should match the window size (if using fixed row windows). Default is null (unweighted).
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).

Returns: A new Series with the rolling maximum.

---

RollingMaxBy

Apply the rolling maximum over a dynamic window defined by the values in the by column.

public Series RollingMaxBy(
    IntoDuration windowSize,
    Expr by,
    int minPeriods = 1,
    ClosedInterval closed = ClosedInterval.Left
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the dynamic window. Supported duration strings: "1d", "2h", "10s", "500ms", etc.
by	Expr	The column used to define the window (the "time" axis). Typically a Date or DateTime column, but can also be monotonic integers.
minPeriods	int	The minimum number of observations in the window required to have a non-null result.
closed	ClosedInterval	Defines how the window interval is closed. Default is ClosedInterval.Left``[t - window, t).

Returns: A new Series with the dynamic rolling maximum.

---

RollingMean

Apply a rolling mean (moving average) over a window.

public Series RollingMean(
    IntoDuration windowSize,
    int minPeriods = 1,
    double[]? weights = null,
    bool center = false
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the window formatted as a string duration. Or use .NET TimeSpan directly. Examples: "3i" (3 index rows), "1d" (1 day), "1h" (1 hour).
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
weights	double[]?	Optional weights to apply to the window. The length of the array should match the window size (if using fixed row windows). Default is null (unweighted).
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).

Returns: A new Series with the rolling mean.

---

RollingMeanBy

Apply a rolling mean (moving average) over a dynamic window defined by the values in the by column.

Unlike standard fixed-size rolling windows (which operate on row counts), this operates on values (typically time).

public Series RollingMeanBy(
    IntoDuration windowSize,
    Expr by,
    int minPeriods = 1,
    ClosedInterval closed = ClosedInterval.Left
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the dynamic window. Supported duration strings: "1d", "2h", "10s", "500ms", etc.
by	Expr	The column used to define the window (the "time" axis). Typically a Date or DateTime column, but can also be monotonic integers.
minPeriods	int	The minimum number of observations in the window required to have a non-null result.
closed	ClosedInterval	Defines how the window interval is closed. Default is ClosedInterval.Left``[t - window, t).

Returns: A new Series with the dynamic rolling mean.

---

RollingMedian

Apply a rolling median (moving median) over a window.

public Series RollingMedian(
    IntoDuration windowSize,
    int minPeriods = 1,
    double[]? weights = null,
    bool center = false
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the window formatted as a string duration. Or use .NET TimeSpan directly. Examples: "3i" (3 index rows), "1d" (1 day), "1h" (1 hour).
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
weights	double[]?	Optional weights to apply to the window. The length of the array should match the window size (if using fixed row windows). Default is null (unweighted).
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).

Returns: A new Series with the rolling median.

---

RollingMedianBy

Apply the rolling median over a dynamic window defined by the values in the by column.

public Series RollingMedianBy(
    IntoDuration windowSize,
    Expr by,
    int minPeriods = 1,
    ClosedInterval closed = ClosedInterval.Left
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the dynamic window. Supported duration strings: "1d", "2h", "10s", "500ms", etc.
by	Expr	The column used to define the window (the "time" axis). Typically a Date or DateTime column, but can also be monotonic integers.
minPeriods	int	The minimum number of observations in the window required to have a non-null result.
closed	ClosedInterval	Defines how the window interval is closed. Default is ClosedInterval.Left``[t - window, t).

Returns: A new Series with the dynamic rolling median.

---

RollingMin

Apply a rolling min (moving min) over a window.

public Series RollingMin(
    IntoDuration windowSize,
    int minPeriods = 1,
    double[]? weights = null,
    bool center = false
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the window formatted as a string duration. Or use .NET TimeSpan directly. Examples: "3i" (3 index rows), "1d" (1 day), "1h" (1 hour).
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
weights	double[]?	Optional weights to apply to the window. The length of the array should match the window size (if using fixed row windows). Default is null (unweighted).
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).

Returns: A new Series with the rolling minimum.

---

RollingMinBy

Apply the rolling minimum over a dynamic window defined by the values in the by column.

public Series RollingMinBy(
    IntoDuration windowSize,
    Expr by,
    int minPeriods = 1,
    ClosedInterval closed = ClosedInterval.Left
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the dynamic window. Supported duration strings: "1d", "2h", "10s", "500ms", etc.
by	Expr	The column used to define the window (the "time" axis). Typically a Date or DateTime column, but can also be monotonic integers.
minPeriods	int	The minimum number of observations in the window required to have a non-null result.
closed	ClosedInterval	Defines how the window interval is closed. Default is ClosedInterval.Left``[t - window, t).

Returns: A new Series with the dynamic rolling minimum.

---

RollingQuantile

Apply a rolling quantile over a fixed window.

public Series RollingQuantile(
    double quantile,
    QuantileMethod method,
    IntoDuration windowSize,
    int minPeriods = 1,
    double[]? weights = null,
    bool center = false
)

Parameters

Name	Type	Description
quantile	double	Quantile between 0.0 and 1.0 (e.g., 0.5 for median).
method	QuantileMethod	Interpolation method when the quantile lies between two data points.
windowSize	IntoDuration	The size of the window. Format: "3i" (3 rows) or just a number string "3". For time-based windows (e.g. "2h"), use Expr.RollingQuantileBy instead.
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
weights	double[]?	Optional weights for the window. The length must match the parsed window size. If null, equal weights are used.
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).

Returns: A new Series with the rolling quantile.

---

RollingQuantileBy

Compute the rolling quantile over a dynamic window defined by the values in the by column.

public Series RollingQuantileBy(
    double quantile,
    QuantileMethod method,
    IntoDuration windowSize,
    Expr by,
    int minPeriods = 1,
    ClosedInterval closed = ClosedInterval.Left
)

Parameters

Name	Type	Description
quantile	double	Quantile between 0.0 and 1.0 (e.g., 0.5 for median).
method	QuantileMethod	Interpolation method when the quantile lies between two data points.
windowSize	IntoDuration	The size of the time window as a System.TimeSpan. This will be automatically converted to a Polars duration string (e.g., 01:30:00 -> "1h30m").
by	Expr	The column used to define the window (the "time" axis). Typically a Date or DateTime column, but can also be monotonic integers.
minPeriods	int	The minimum number of observations in the window required to have a non-null result.
closed	ClosedInterval	Defines how the window interval is closed. Default is ClosedInterval.Left``[t - window, t).

Returns: A new Series with the dynamic rolling quantile.

---

RollingRank

Apply a rolling rank (moving rank) over a window.

public Series RollingRank(
    IntoDuration windowSize,
    int minPeriods = 1,
    RankMethod method = RankMethod.Average,
    ulong? seed = null,
    double[]? weights = null,
    bool center = false
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the window formatted as a string duration. Or use .NET TimeSpan directly. Examples: "3i" (3 index rows), "1d" (1 day), "1h" (1 hour).
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
method	RankMethod	The method used to assign ranks to tied elements. See RankMethod for details. Default is RankMethod.Average.
seed	ulong?	If method="random", use this as seed.
weights	double[]?	Optional weights to apply to the window. The length of the array should match the window size (if using fixed row windows). Default is null (unweighted).
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).

Returns: A new Series with the rolling rank.

---

RollingRankBy

Compute the rolling rank over a dynamic window defined by the values in the by column.

public Series RollingRankBy(
    IntoDuration windowSize,
    Expr by,
    RollingRankMethod method = RollingRankMethod.Average,
    ulong? seed = null,
    int minPeriods = 1,
    ClosedInterval closed = ClosedInterval.Left
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the dynamic window. Supported duration strings: "1d", "2h", "10s", "500ms", etc.
by	Expr	The column used to define the window (the "time" axis). Typically a Date or DateTime column, but can also be monotonic integers.
method	RollingRankMethod	The method used to assign ranks to tied elements.
seed	ulong?	Seed for the random method (only relevant when method is Random).
minPeriods	int	The minimum number of observations in the window required to have a non-null result.
closed	ClosedInterval	Defines how the window interval is closed. Default is ClosedInterval.Left``[t - window, t).

Returns: A new Series with the dynamic rolling rank.

---

RollingSkew

Apply a rolling skew (moving skew) over a window.

public Series RollingSkew(
    IntoDuration windowSize,
    int minPeriods = 1,
    double[]? weights = null,
    bool center = false,
    bool bias = true
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the window formatted as a string duration. Or use .NET TimeSpan directly. Examples: "3i" (3 index rows), "1d" (1 day), "1h" (1 hour).
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
weights	double[]?	Optional weights to apply to the window. The length of the array should match the window size (if using fixed row windows). Default is null (unweighted).
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).
bias	bool	-

Returns: A new Series with the rolling skew.

---

RollingStd

Apply a rolling standard deviation (moving std) over a window.

public Series RollingStd(
    IntoDuration windowSize,
    int minPeriods = 1,
    double[]? weights = null,
    bool center = false
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the window formatted as a string duration. Or use .NET TimeSpan directly. Examples: "3i" (3 index rows), "1d" (1 day), "1h" (1 hour).
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
weights	double[]?	Optional weights to apply to the window. The length of the array should match the window size (if using fixed row windows). Default is null (unweighted).
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).

Returns: A new Series with the rolling standard deviation.

---

RollingStdBy

Apply the rolling standard deviation over a dynamic window defined by the values in the by column.

public Series RollingStdBy(
    IntoDuration windowSize,
    Expr by,
    int minPeriods = 1,
    ClosedInterval closed = ClosedInterval.Left
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the dynamic window. Supported duration strings: "1d", "2h", "10s", "500ms", etc.
by	Expr	The column used to define the window (the "time" axis). Typically a Date or DateTime column, but can also be monotonic integers.
minPeriods	int	The minimum number of observations in the window required to have a non-null result.
closed	ClosedInterval	Defines how the window interval is closed. Default is ClosedInterval.Left``[t - window, t).

Returns: A new Series with the dynamic rolling standard deviation.

---

RollingSum

Apply a rolling sum (moving sum) over a window.

public Series RollingSum(
    IntoDuration windowSize,
    int minPeriods = 1,
    double[]? weights = null,
    bool center = false
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the window formatted as a string duration. Or use .NET TimeSpan directly. Examples: "3i" (3 index rows), "1d" (1 day), "1h" (1 hour).
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
weights	double[]?	Optional weights to apply to the window. The length of the array should match the window size (if using fixed row windows). Default is null (unweighted).
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).

Returns: A new Series with the rolling sum.

---

RollingSumBy

Apply a rolling sum over a dynamic window defined by the values in the by column.

public Series RollingSumBy(
    IntoDuration windowSize,
    Expr by,
    int minPeriods = 1,
    ClosedInterval closed = ClosedInterval.Left
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the dynamic window. Supported duration strings: "1d", "2h", "10s", "500ms", etc.
by	Expr	The column used to define the window (the "time" axis). Typically a Date or DateTime column, but can also be monotonic integers.
minPeriods	int	The minimum number of observations in the window required to have a non-null result.
closed	ClosedInterval	Defines how the window interval is closed. Default is ClosedInterval.Left``[t - window, t).

Returns: A new Series with the dynamic rolling sum.

---

RollingVar

Apply a rolling variance (moving var) over a window.

public Series RollingVar(
    IntoDuration windowSize,
    int minPeriods = 1,
    double[]? weights = null,
    bool center = false,
    byte ddof = 1
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the window formatted as a string duration. Or use .NET TimeSpan directly. Examples: "3i" (3 index rows), "1d" (1 day), "1h" (1 hour).
minPeriods	int	The minimum number of observations in the window required to have a value (otherwise null).
weights	double[]?	Optional weights to apply to the window. The length of the array should match the window size (if using fixed row windows). Default is null (unweighted).
center	bool	If true, the window is centered on the current observation. Default is false (right-aligned window, [i-window, i]).
ddof	byte	“Delta Degrees of Freedom”: the divisor used in the calculation is N - ddof, where N represents the number of elements. By default ddof is 1.

Returns: A new Series with the rolling variance.

---

RollingVarBy

Apply the rolling variance over a dynamic window defined by the values in the by column.

public Series RollingVarBy(
    IntoDuration windowSize,
    Expr by,
    int minPeriods = 1,
    ClosedInterval closed = ClosedInterval.Left,
    byte ddof = 1
)

Parameters

Name	Type	Description
windowSize	IntoDuration	The size of the dynamic window. Supported duration strings: "1d", "2h", "10s", "500ms", etc.
by	Expr	The column used to define the window (the "time" axis). Typically a Date or DateTime column, but can also be monotonic integers.
minPeriods	int	The minimum number of observations in the window required to have a non-null result.
closed	ClosedInterval	Defines how the window interval is closed. Default is ClosedInterval.Left``[t - window, t).
ddof	byte	“Delta Degrees of Freedom”: the divisor used in the calculation is N - ddof, where N represents the number of elements. By default ddof is 1.

Returns: A new Series with the dynamic rolling variance.

---

Round

Round underlying floating point data by decimals digits.

public Series Round(uint decimals = 0, RoundMode mode = RoundMode.HalfToEven)

Parameters

Name	Type	Description
decimals	uint	Number of decimals to round by.
mode	RoundMode	The rounding strategy used. A “rounded value” is a value with at most decimals decimal places (e.g. integers when decimals=0, multiples of 0.1 when decimals=1, 0.01 when decimals=2, and so on). Strategies that start with half_ round all values to the nearest rounded value, only using the strategy to break ties when a value falls exactly between two rounded values (e.g. 0.5 when decimals=0, 0.05 when decimals=1). Other rounding strategies specify explicitly which rounded value is chosen and always apply (not just for tiebreaks).

---

RoundSigFigs

Round to a number of significant figures.

public Series RoundSigFigs(int digits)

Parameters

Name	Type	Description
digits	int	Number of significant figures to round to.

---

Sample

Sample from this expression.

public Series Sample(
    ulong n = 1,
    bool withReplacement = false,
    bool shuffle = false,
    ulong? seed = null
)

public Series Sample(
    double fraction,
    bool withReplacement = false,
    bool shuffle = false,
    ulong? seed = null
)

Parameters

Name	Type	Description
n	ulong	Number of items to return. Default to 1
withReplacement	bool	Allow values to be sampled more than once.
shuffle	bool	Shuffle the order of sampled data points.
seed	ulong?	Seed for the random number generator. If set to None (default), a random seed is generated for each sample operation.
fraction	double	Fraction of items to return.

---

SearchSorted

Find indices where elements should be inserted to maintain order (Binary Search).

public Series SearchSorted(IntoExpr? element, SearchSortedSide side = SearchSortedSide.Any, bool descending = false)
public Series SearchSorted<T>(IEnumerable<T> element, SearchSortedSide side = SearchSortedSide.Any, bool descending = false)

Parameters

Name	Type	Description
element	IntoExpr? / IEnumerable<T>	The element expression to insert/search.
side	SearchSortedSide	The insertion side (Any, Left, Right). Default is Any.
descending	bool	Whether the target column is sorted in descending order. Default is false.

---

SearchSortedIndex

Searches for a single scalar value and returns its insertion index.

public int SearchSortedIndex(object? scalar, SearchSortedSide side = SearchSortedSide.Any, bool descending = false)

Parameters

Name	Type	Description
scalar	object?	-
side	SearchSortedSide	-
descending	bool	-

---

SetSorted

Flags the Series as ‘sorted’. Enables downstream code to user fast paths for sorted arrays.

public Series SetSorted(bool descending = false)

Parameters

Name	Type	Description
descending	bool	If the Series order is descending.

---

Shift

Shift values by the given number of indices.

public Series Shift(long n = 1)

Parameters

Name	Type	Description
n	long	-

---

Show

Print the DataFrame to Console.

public void Show()

---

ShrinkToFit

Shrink Series memory usage.

public Series ShrinkToFit()

Returns: A new Series

---

ShrinkToFitInplace

Shrink Series memory usage.This won't return a new Series

public void ShrinkToFitInplace()

---

Sign

Compute the element-wise sign (-1, 0, 1).

public Series Sign()

---

Sin

Compute the element-wise sine.

public Series Sin()

---

Sinh

Compute the element-wise hyperbolic sine.

public Series Sinh()

---

Skew

Compute the sample skewness of a data set.

public double? Skew(bool bias = true)

Parameters

Name	Type	Description
bias	bool	If False, the calculations are corrected for statistical bias.

Returns: A series which length is 1

---

Slice

Get a slice of this Series.

public Series Slice(long offset, ulong? length = null)
public Series Slice(Range range)

Parameters

Name	Type	Description
offset	long	Start index. Negative values count from the end.
length	ulong?	Length of the slice.
range	Range	-

---

Sort

Sort this Series.

public Series Sort(
    bool descending = false,
    bool nullsLast = false,
    bool maintainOrder = false,
    bool multithreaded = true
)

Parameters

Name	Type	Description
descending	bool	Sort in descending order.
nullsLast	bool	Place null values last (default behavior depends on ascending/descending).
maintainOrder	bool	Use stable sort (maintain order of equal elements) (default: false).
multithreaded	bool	Use parallel sorting (default: true).

---

Sqrt

Calculate square value.

public Series Sqrt()

---

Std

Get the standard deviation of this Series.

public T? Std<T>(byte ddof = 1)

Parameters

Name	Type	Description
ddof	byte	Delta Degrees of Freedom. The divisor used in calculations is N - ddof.

---

Sum

Sum series into 1 length series(Scalar)

Sum series into scalar

public Series Sum()
public T? Sum<T>()

---

Take

LINQ-like alias for Gather.

Take elements by physical integer indices. Negative indices are not supported. All values must be >= 0.

public Series Take(IntoExprColumn indices)
public Series Take(ReadOnlySpan<int> indices)
public Series Take(Series indices)

Parameters

Name	Type	Description
indices	IntoExprColumn / ReadOnlySpan<int> / Series	-

---

Tan

Compute the element-wise tangent.

public Series Tan()

---

Tanh

Compute the element-wise hyperbolic tangent.

public Series Tanh()

---

ToArray

Convert Series to Array

public T[] ToArray<T>()

---

ToArrow

Zero-copy convert to Apache Arrow Array.

public IArrowArray ToArrow()

---

ToDataFrame

Convert this single Series into a DataFrame. Functional alias for Series.ToFrame.

public DataFrame ToDataFrame()

---

ToDummies

Get dummy/indicator variables.

public DataFrame ToDummies(string? separator = "_", bool dropFirst = false, bool dropNulls = false)

Parameters

Name	Type	Description
separator	string?	Separator/delimiter used when generating column names.
dropFirst	bool	Remove the first category from the variable being encoded.
dropNulls	bool	If there are None values in the series, a null column is not generated. Null values in the input are represented by zero vectors.

---

ToFrame

Convert this single Series into a DataFrame.

public DataFrame ToFrame()

---

ToHtml

Generates a rich HTML table representation of the Series by delegating to a single-column DataFrame preview.

public string ToHtml()

Returns: An HTML string representing the Series preview.

---

ToPhysical

Cast to physical representation of the logical dtype.

public Series ToPhysical()

---

TopK

Get the top k values.

public Series TopK(int k)

Parameters

Name	Type	Description
k	int	-

---

TopKBy

Get the top k rows according to the sorting criteria defined by by.

Get the top k values sorted by another Series.

public Series TopKBy(int k, Expr[] by, bool[] reverse)
public Series TopKBy(int k, Expr by, bool reverse = false)
public Series TopKBy(int k, Series by, bool reverse = false)

Parameters

Name	Type	Description
k	int	Number of rows to return.
by	Expr[] / Series	The expressions (columns) to sort by.
reverse	bool[]	Controls the sorting direction for each expression in by. For TopK: - false (default): Sorts descending (picks largest values). - true: Sorts ascending (picks smallest values, acting like BottomK for this column). Length must match by.

Returns: A new Series containing the top k elements.

---

Truncate

Truncate numeric data toward zero to decimals number of decimal places.

public Series Truncate(uint decimals = 0)

Parameters

Name	Type	Description
decimals	uint	Number of decimal places to truncate to.

---

Unique

Get unique values of this series.

public Series Unique(bool maintainOrder = false)

Parameters

Name	Type	Description
maintainOrder	bool	Maintain order of data. This requires more work.

---

UniqueCounts

Return a count of the unique values in the order of appearance.

public Series UniqueCounts()

---

Unnest

Unnest a Struct column into a DataFrame. Shortcut for SeriesStructOps.Unnest.

public DataFrame Unnest()

---

UpperBound

Return the upper bound of this Series’ dtype as a unit Series.

public Series UpperBound()

---

ValueCounts

Count the occurrences of unique values.

Similar to SQL GROUP BY val COUNT(*).

public DataFrame ValueCounts(
    bool sort = true,
    bool parallel = true,
    string? name = null,
    bool normalize = false
)

Parameters

Name	Type	Description
sort	bool	Sort the output by count in descending order. Default is true.
parallel	bool	Execute in parallel. Default is true.
name	string?	Give the resulting count column a specific name; if normalize is True this defaults to “proportion”, otherwise defaults to “count”..
normalize	bool	If true, the count column will contain probabilities (fractions) instead of absolute counts. Default is false.

Returns: A DataFrame with the series values and their counts.

Example

var s = Series.From("fruit", ["apple", "apple", "banana"]);

// Default: sorted, absolute counts
s.ValueCounts().Show();

// Normalized (percentage)
s.ValueCounts(normalize: true, name: "prob").Show();
// Result
┌────────┬───────┐
│ fruit  ┆ prob  │
│ ---    ┆ ---   │
│ str    ┆ u32   │
╞════════╪═══════╡
│ apple  ┆ 3     │
│ orange ┆ 2     │
│ banana ┆ 1     │
└────────┴───────┘

---

Var

Get the variance of this Series.

public T? Var<T>(byte ddof = 1)

Parameters

Name	Type	Description
ddof	byte	Delta Degrees of Freedom. The divisor used in calculations is N - ddof.

---

ZipWith

Take values from self or other based on the given mask. Where mask evaluates true, take values from self. Where mask evaluates false, take values from other.

public Series ZipWith(Series mask, Series other)

Parameters

Name	Type	Description
mask	Series	Boolean Series.
other	Series	Series of same type.

Returns: Series

---