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Filtering

This tool provides several methods for filtering the dataset. The window that opens has four options for you to choose from:

Filter dialog window

Levels of a categorical variable​

Filter by categorical levels

After selecting a categorical variable from the drop down box, you can select which levels you want to keep in the data set.

Numeric condition​

Filter by numeric condition

This allows you to define a condition with which to filter your data. For example, you could include only the observations of height over 180 cm by

  1. selecting height from the drop down menu,
  2. clicking on the > symbol, and
  3. entering the value 180 in the third box.

Row number​

Filter by row number

Exclude a range of row numbers as follows:

  • Entering 101:1000 (and then Submit) will exclude all rows from 101 to 1000
  • Similarly, 1, 5, 99, 101:1000 will exclude rows 1, 5, 99, and everything from 101 to 1000

Randomly​

Filter randomly

Essentially, this allows you to perform bootstrap randomisation manually. The current behaviour is this:

  • "Sample Size", n, is the number of observations to draw for each sample,
  • "Number of Samples", m, is the number of samples to create in the new data set.
  • The output will be a data set with n x m rows, which must be smaller than the total number of rows in the data set.
  • The observations are drawn randomly without replacement from the data set.