Aggregation Class

Contains factory methods for dataframe aggregation descriptors.

Definition

Namespace: Numerics.NET.DataAnalysis
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 10.8.0
C#
public static class Aggregation
Inheritance
Object  →  Aggregation

Remarks

The factory methods create immutable descriptors. They do not bind to a data frame or execute an aggregation until passed to a descriptor-based Aggregate overload.

Default unary output keys are strings in the form column_statistic. Default binary output keys are strings in the form left_right_statistic. Selector-based methods require the source column-key type to be supplied explicitly because a selector is independent of the key type.

Use Aggregation<C, COut>.As(...) to choose a custom output key type. All descriptors supplied to one descriptor-based Aggregate call must share one output key type, and duplicate output keys are invalid.

The descriptor helper set covers unary and binary aggregator groups that map to one output per selected input or input pair. Dictionary and multi-output aggregators are deferred.

Methods

AbsoluteMax<C>(C) Creates a descriptor that computes the value with greatest absolute magnitude in the specified column.
AbsoluteMax<C>(ColumnSelector) Creates a descriptor that computes values with greatest absolute magnitude in selected columns.
AbsoluteMaxIndex<C>(C) Creates a descriptor that computes the zero-based index of the value with greatest absolute magnitude.
AbsoluteMaxIndex<C>(ColumnSelector) Creates a descriptor that computes zero-based indexes of values with greatest absolute magnitude.
AbsoluteMin<C>(C) Creates a descriptor that computes the value with smallest absolute magnitude in the specified column.
AbsoluteMin<C>(ColumnSelector) Creates a descriptor that computes values with smallest absolute magnitude in selected columns.
AbsoluteMinIndex<C>(C) Creates a descriptor that computes the zero-based index of the value with smallest absolute magnitude.
AbsoluteMinIndex<C>(ColumnSelector) Creates a descriptor that computes zero-based indexes of values with smallest absolute magnitude.
Correlation<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes correlations for selected column pairs.
Correlation<C>(C, C) Creates a descriptor that computes correlation between two columns.
CorrelationAsDouble<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes double-valued correlations for selected column pairs.
CorrelationAsDouble<C>(C, C) Creates a descriptor that computes correlation between two columns and returns a Double result.
CorrelationDistance<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes correlation distances for selected column pairs.
CorrelationDistance<C>(C, C) Creates a descriptor that computes correlation distance between two columns.
CosineDistance<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes cosine distances for selected column pairs.
CosineDistance<C>(C, C) Creates a descriptor that computes cosine distance between two columns.
CosineSimilarity<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes cosine similarities for selected column pairs.
CosineSimilarity<C>(C, C) Creates a descriptor that computes cosine similarity between two columns.
CosineSimilarityAsDouble<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes double-valued cosine similarities for selected column pairs.
CosineSimilarityAsDouble<C>(C, C) Creates a descriptor that computes cosine similarity and returns a Double result.
Count<C>(ColumnSelector) Creates a descriptor that counts non-missing values in selected columns.
Count<C>(C) Creates a descriptor that counts non-missing values in the specified column.
CountUnique<C>(ColumnSelector) Creates a descriptor that counts distinct non-missing values in selected columns.
CountUnique<C>(C) Creates a descriptor that counts distinct non-missing values in the specified column.
Covariance<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes covariance for selected column pairs.
Covariance<C>(C, C) Creates a descriptor that computes covariance between two columns.
CovarianceAsDouble<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes double-valued covariances for selected column pairs.
CovarianceAsDouble<C>(C, C) Creates a descriptor that computes covariance between two columns and returns a Double result.
DotProduct<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes dot products for selected column pairs.
DotProduct<C>(C, C) Creates a descriptor that computes dot product between two columns.
EuclideanDistance<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes Euclidean distances for selected column pairs.
EuclideanDistance<C>(C, C) Creates a descriptor that computes Euclidean distance between two columns.
EuclideanDistanceAsDouble<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes double-valued Euclidean distances for selected column pairs.
EuclideanDistanceAsDouble<C>(C, C) Creates a descriptor that computes Euclidean distance and returns a Double result.
First<C>(ColumnSelector) Creates a descriptor that returns first values in selected columns.
First<C>(C) Creates a descriptor that returns the first value in the specified column.
FirstQuartile<C>(ColumnSelector) Creates a descriptor that computes first quartiles of selected columns.
FirstQuartile<C>(C) Creates a descriptor that computes the first quartile of the specified column.
Kurtosis<C>(ColumnSelector) Creates a descriptor that computes kurtosis of selected columns.
Kurtosis<C>(C) Creates a descriptor that computes kurtosis of the specified column.
Last<C>(ColumnSelector) Creates a descriptor that returns last values in selected columns.
Last<C>(C) Creates a descriptor that returns the last value in the specified column.
LogSumExp<C>(ColumnSelector) Creates a descriptor that computes logarithms of sums of exponentials of selected columns.
LogSumExp<C>(C) Creates a descriptor that computes the logarithm of the sum of exponentials of the specified column.
Max<C>(ColumnSelector) Creates a descriptor that computes maximum values of selected columns.
Max<C>(C) Creates a descriptor that computes the maximum value of the specified column.
MaxIndex<C>(ColumnSelector) Creates a descriptor that computes zero-based indexes of maximum values in selected columns.
MaxIndex<C>(C) Creates a descriptor that computes the zero-based index of the maximum value in the specified column.
Mean<C>(ColumnSelector) Creates a descriptor that computes the mean of selected columns.
Mean<C>(C) Creates a descriptor that computes the mean of the specified column.
MeanAsDouble<C>(ColumnSelector) Creates a descriptor that computes means of selected columns and returns Double results.
MeanAsDouble<C>(C) Creates a descriptor that computes the mean of the specified column and returns a Double result.
Median<C>(ColumnSelector) Creates a descriptor that computes medians of selected columns.
Median<C>(C) Creates a descriptor that computes the median of the specified column.
Min<C>(ColumnSelector) Creates a descriptor that computes minimum values of selected columns.
Min<C>(C) Creates a descriptor that computes the minimum value of the specified column.
MinIndex<C>(ColumnSelector) Creates a descriptor that computes zero-based indexes of minimum values in selected columns.
MinIndex<C>(C) Creates a descriptor that computes the zero-based index of the minimum value in the specified column.
Mode<C>(ColumnSelector) Creates a descriptor that computes the mode of selected columns.
Mode<C>(C) Creates a descriptor that computes the mode of the specified column.
OneNorm<C>(ColumnSelector) Creates a descriptor that computes one-norms of selected columns.
OneNorm<C>(C) Creates a descriptor that computes the one-norm of the specified column.
OneNormAsDouble<C>(ColumnSelector) Creates a descriptor that computes one-norms of selected columns and returns Double results.
OneNormAsDouble<C>(C) Creates a descriptor that computes the one-norm of the specified column and returns a Double result.
Product<C>(ColumnSelector) Creates a descriptor that multiplies values in selected columns.
Product<C>(C) Creates a descriptor that multiplies values in the specified column.
ProductAsDouble<C>(ColumnSelector) Creates a descriptor that multiplies values in selected columns and returns Double results.
ProductAsDouble<C>(C) Creates a descriptor that multiplies values in the specified column and returns a Double result.
Quantile<C>(ColumnSelector, Double) Creates a descriptor that computes quantiles of selected columns.
Quantile<C>(C, Double) Creates a descriptor that computes a quantile of the specified column.
Quantile<C>(ColumnSelector, Double, QuantileType) Creates a descriptor that computes quantiles of selected columns using the specified quantile method.
Quantile<C>(ColumnSelector, Double, Int32) Creates a descriptor that computes quantiles of selected columns using an R quantile type number.
Quantile<C>(C, Double, Int32) Creates a descriptor that computes a quantile of the specified column using an R quantile type number.
Quantile<C>(C, Double, QuantileType) Creates a descriptor that computes a quantile of the specified column using the specified quantile method.
Range<C>(ColumnSelector) Creates a descriptor that computes ranges of selected columns.
Range<C>(C) Creates a descriptor that computes the range of the specified column.
Skewness<C>(ColumnSelector) Creates a descriptor that computes skewness of selected columns.
Skewness<C>(C) Creates a descriptor that computes skewness of the specified column.
Skip<C>(ColumnSelector, Int32) Creates a descriptor that returns first non-missing values after skipping a number of values.
Skip<C>(C, Int32) Creates a descriptor that returns the first non-missing value after skipping a number of values.
StandardDeviation<C>(ColumnSelector) Creates a descriptor that computes sample standard deviations of selected columns.
StandardDeviation<C>(C) Creates a descriptor that computes sample standard deviation of the specified column.
StandardDeviationAsDouble<C>(ColumnSelector) Creates a descriptor that computes sample standard deviations of selected columns and returns Double results.
StandardDeviationAsDouble<C>(C) Creates a descriptor that computes sample standard deviation of the specified column and returns a Double result.
Sum<C>(ColumnSelector) Creates a descriptor that sums selected columns.
Sum<C>(C) Creates a descriptor that sums the specified column.
SumAsDouble<C>(ColumnSelector) Creates a descriptor that sums selected columns and returns Double results.
SumAsDouble<C>(C) Creates a descriptor that sums the specified column and returns a Double result.
SumOfAbsoluteDifferences<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes sums of absolute differences for selected column pairs.
SumOfAbsoluteDifferences<C>(C, C) Creates a descriptor that computes the sum of absolute differences between two columns.
SumOfSquares<C>(ColumnSelector) Creates a descriptor that computes sums of squares of selected columns.
SumOfSquares<C>(C) Creates a descriptor that computes the sum of squares of the specified column.
ThirdQuartile<C>(ColumnSelector) Creates a descriptor that computes third quartiles of selected columns.
ThirdQuartile<C>(C) Creates a descriptor that computes the third quartile of the specified column.
TwoNorm<C>(ColumnSelector) Creates a descriptor that computes Euclidean norms of selected columns.
TwoNorm<C>(C) Creates a descriptor that computes the Euclidean norm of the specified column.
Variance<C>(ColumnSelector) Creates a descriptor that computes sample variances of selected columns.
Variance<C>(C) Creates a descriptor that computes sample variance of the specified column.
VarianceAsDouble<C>(ColumnSelector) Creates a descriptor that computes sample variances of selected columns and returns Double results.
VarianceAsDouble<C>(C) Creates a descriptor that computes sample variance of the specified column and returns a Double result.
WeightedMean<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes weighted means for selected value/weight column pairs.
WeightedMean<C>(C, C) Creates a descriptor that computes the weighted mean of one column using another as weights.
WeightedMeanAsDouble<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes double-valued weighted means for selected value/weight column pairs.
WeightedMeanAsDouble<C>(C, C) Creates a descriptor that computes the weighted mean of one column and returns a Double result.
WeightedStandardDeviation<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes weighted standard deviations for selected value/weight column pairs.
WeightedStandardDeviation<C>(C, C) Creates a descriptor that computes weighted standard deviation of one column using another as weights.
WeightedStandardDeviationOfDouble<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes double-valued weighted standard deviations for selected value/weight column pairs.
WeightedStandardDeviationOfDouble<C>(C, C) Creates a descriptor that computes weighted standard deviation and returns a Double result.
WeightedVariance<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes weighted variances for selected value/weight column pairs.
WeightedVariance<C>(C, C) Creates a descriptor that computes weighted variance of one column using another as weights.
WeightedVarianceOfDouble<C>(ColumnSelector, ColumnSelector) Creates a descriptor that computes double-valued weighted variances for selected value/weight column pairs.
WeightedVarianceOfDouble<C>(C, C) Creates a descriptor that computes weighted variance and returns a Double result.

See Also