Row Sampling

This node extracts a sample (a bunch of rows) from the input data. The dialog enables you to specify the sample size. The following options are available in the dialog:

Options

Absolute

Specify the absolute number of rows in the sample. If there are less rows than specified here, all rows are used.

Relative

The percentage of the number of rows in the sample. Must be between 0 and 100, inclusively.

Take from top

This mode selects the top most rows of the table.

Linear sampling

This mode always includes the first and the last row and selects the remaining rows linearly over the whole table (e.g. every third row). This is useful to downsample a sorted column while maintaining minimum and maximum value.

Draw randomly

Random sampling of all rows, you may optionally specify a fixed seed (see below).

Stratified sampling

Check this button if you want stratified sampling, i.e. the distribution of values in the selected column is (approximately) retained in the output table. You may optionally specify a fixed seed (see below).

Use random seed

If either random or stratified sampling is selected, you may enter a fixed seed here in order to get reproducible results upon re-execution. If you do not specify a seed, a new random seed is taken for each execution.

Views

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Workflows

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Links

• Selecting the top 50 rows of a table by a control columnby armingrudd on 2019-11-05

  forum.knime.com/p/74011
• Partitioning absolute number of rows from top slowby izaychik63 on 2021-04-12

  forum.knime.com/p/120671
• Create a random list of valuesby s.roughley on 2019-05-03

  forum.knime.com/p/59889
• How to Filter Databy HansS on 2021-08-28

  forum.knime.com/p/133011
• Unbalanced Databy armingrudd on 2019-10-26

  forum.knime.com/p/73300
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Developers