Column Quantiles#

group column_quantiles

Functions

std::unique_ptr<column> quantile(column_view const &input, std::vector<double> const &q, interpolation interp = interpolation::LINEAR, column_view const &ordered_indices = {}, bool exact = true, rmm::cuda_stream_view stream = cudf::get_default_stream(), rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref())#

Computes quantiles with interpolation.

Computes the specified quantiles by interpolating values between which they lie, using the interpolation strategy specified in interp.

Parameters:

  • input – [in] Column from which to compute quantile values

  • q – [in] Specified quantiles in range [0, 1]

  • interp – [in] Strategy used to select between values adjacent to a specified quantile.

  • ordered_indices – [in] Column containing the sorted order of input. If the column is empty, all input values are used in existing order. Indices must be in range [0, input.size()), but are not required to be unique. Values not indexed by this column will be ignored.

  • exact – [in] If true, returns doubles. If false, returns same type as input.

  • stream – [in] CUDA stream used for device memory operations and kernel launches

  • mr – [in] Device memory resource used to allocate the returned column’s device memory

Returns:

Column of specified quantiles, with nulls for indeterminable values

std::unique_ptr<table> quantiles(table_view const &input, std::vector<double> const &q, interpolation interp = interpolation::NEAREST, cudf::sorted is_input_sorted = sorted::NO, std::vector<order> const &column_order = {}, std::vector<null_order> const &null_precedence = {}, rmm::cuda_stream_view stream = cudf::get_default_stream(), rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref())#

Returns the rows of the input corresponding to the requested quantiles.

Quantiles are cut points that divide the range of a dataset into continuous intervals. e.g: quartiles are the three cut points that divide a dataset into four equal-sized groups. See https://en.wikipedia.org/wiki/Quantile

The indices used to gather rows are computed by interpolating between the index on either side of the desired quantile. Since some columns may be non-arithmetic, interpolation between rows is limited to non-arithmetic strategies.

Non-arithmetic interpolation strategies include HIGHER, LOWER, and NEAREST.

quantiles <= 0 correspond to row 0. (first) quantiles >= 1 correspond to row input.size() - 1. (last)

Parameters:

  • input – Table used to compute quantile rows

  • q – Desired quantiles in range [0, 1]

  • interp – Strategy used to select between the two rows on either side of the desired quantile.

  • is_input_sorted – Indicates if the input has been pre-sorted

  • column_order – The desired sort order for each column

  • null_precedence – The desired order of null compared to other elements

  • stream – CUDA stream used for device memory operations and kernel launches

  • mr – Device memory resource used to allocate the returned table’s device memory

Throws:
Returns:

Table of specified quantiles, with nulls for indeterminable values

std::unique_ptr<column> percentile_approx(tdigest::tdigest_column_view const &input, column_view const &percentiles, rmm::cuda_stream_view stream = cudf::get_default_stream(), rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref())#

Calculate approximate percentiles on an input tdigest column.

tdigest (https://arxiv.org/pdf/1902.04023.pdf) columns are produced specifically by the TDIGEST and MERGE_TDIGEST aggregations. These columns represent compressed representations of a very large input data set that can be queried for quantile information.

Produces a LIST column where each row i represents output from querying the corresponding tdigest from input row i. The length of each output list is the number of percentages specified in percentages.

Parameters:

  • input – tdigest input data. One tdigest per row

  • percentiles – Desired percentiles in range [0, 1]

  • stream – CUDA stream used for device memory operations and kernel launches

  • mr – Device memory resource used to allocate the returned column’s device memory

Throws:
Returns:

LIST Column containing requested percentile values as FLOAT64

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