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Pivoting

KNIME Base Nodes version 4.0.1.v201908131444 by KNIME AG, Zurich, Switzerland

Performs a pivoting on the given input table using a selected number of columns for grouping and pivoting. The group columns will result into unique rows, whereby the pivot values turned into columns for each set of column combinations together with each aggregation method. In addition, the node returns the total aggregation (a) based on only the group columns and (b) based on only the pivoted columns resulting in a single row; optionally, with the total aggregation without pivoting.

To change the aggregation method of more than one column select all columns to change, open the context menu with a right mouse click and select the aggregation method to use.

A detailed description of the available aggregation methods can be found on the 'Description' tab in the node dialog.

Options

Group settings

Group columns
Select one or more columns according to which the group rows are created.

Pivot settings

Pivot columns
Select one or more columns according to which the pivot columns are created.
Ignore missing values
Ignore rows containing missing values in pivot column.
Append overall totals
Appends the overall pivot totals with each aggregation performed together on all selected pivot columns.
Ignore domain
Ignore domain and use only the possible values available in the input data.

Manual Aggregation

Aggregation methods
Select one or more columns for aggregation from the available columns list. Change the aggregation method in the Aggregation column of the table. You can add the same column multiple times. In order to change the aggregation method of more than one column select all columns to change, open the context menu with a right mouse click and select the aggregation method to use. Tick the missing box to include missing values. This option might be disabled if the aggregation method does not support missing values. The parameter column shows an "Edit" button for all aggregation operators that require additional information. Clicking on the "Edit" button opens the parameter dialog which allows changing the operator specific settings.

Advanced settings

Column name
The name of the resulting pivot column(s) depends on the selected naming schema.
  • Pivot name+Aggregation name: Uses the pivot name first and the aggregation name second joint by a + character. Keeps the original column names. Note that you can use all aggregation columns only once with this column naming option to prevent duplicate column names.
  • Aggregation name+Pivot name: Uses the aggregation name first and the pivot name second joint by a + character.
  • Pivot name: Uses solely the pivot name. Note that this option solely supports the selection of a single aggregation method to ensure uniqueness of the column names.
Aggregation name
The name of the resulting aggregation column(s) depends on the selected naming schema.
  • Keep original name(s): Keeps the original column names. Note that you can use all aggregation columns only once with this naming option to prevent duplicated column names.
  • Aggregation method (column name): Uses the aggregation method first and appends the column name in brackets
  • Column name (aggregation method): Uses the column name first and appends the aggregation method in brackets
All aggregation methods get an * appended if the missing value option is not ticked in the aggregation settings in order to distinguish between columns that considered missing values in the aggregation process and columns that do not.
Sort lexicographically
Lexicographically sorts all columns belonging to the same logical group, i.e., pivots (aggregations), groups, and overall totals.
Maximum unique values per group
Defines the maximum number of unique values per group to avoid problems with memory overloading. All groups with more unique values are skipped during the calculation and a missing value is set in the corresponding column, and a warning is displayed.
Value delimiter
The value delimiter used by aggregation methods such as concatenate.
Process in memory
Process the table in the memory. Requires more memory but is faster since the table needs not to be sorted prior aggregation. The memory consumption depends on the number of unique groups and the chosen aggregation method. The row order of the input table is automatically retained.
Retain row order
Retains the original row order of the input table. Could result in longer execution time. The row order is automatically retained if the process in memory option is selected.
Enable hiliting
If enabled, the hiliting of a group row will hilite all rows of this group in other views. Depending on the number of rows, enabling this feature might consume a lot of memory.
Missing
Missing values are considered during aggregation if the missing option is ticked for the corresponding row in the column aggregation table. Some aggregation methods do not support the changing of the missing option such as means.

Input Ports

The input table to pivot.

Output Ports

Pivot table.
A table containing the totals for each defined group. That is, the aggregation for each group ignoring the pivoting groups. This table can be joined with the Pivot table; the RowIDs of both tables represent the same groups). The table will contain as many rows as there are different groups in the data and as many columns as there are selected aggregations. The table is identical to the output of a GroupBy node, in which the group and aggregation columns are chosen accordingly.
A single row table containing the aggregated values of the Pivot table. The table structure is identical to the Pivot table (possibly enriched by overall totals if the "Append overall totals" is selected. This table is usually concatenated with table that results from joining the Pivot table with the Group table.

Best Friends (Incoming)

Best Friends (Outgoing)

Workflows

Installation

To use this node in KNIME, install KNIME Core from the following update site:

KNIME 4.0
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