Table.filter

filtercolumnfilter on_problems

Group: Selections
Aliases: filter rows, where

Documentation

Filter is used to select data from a table using a condition. The rows that meet the condition will remain after the filter. Filters can compare columns, compare against static values, or compare against an argument from another component.

• action: This can be set to Keep, which keeps all rows which meet the condition. It can also be set to Remove, which will instead only keep the rows that do not meet the condition. For example, [people] Is Null would keep all the rows where the column people had a Null value. Changing this to Remove would remove all of the rows where people had a Null value, leaving only the records that are not null. - on_problems: specified how to report any issues encountered during the operation.

Arguments

• column: The column our condition is tested against. This can be a column name, the column's index or an expression.
• filter: The filter to apply to the column. It can either be an instance of Filter_Condition or a predicate taking a cell value and returning a boolean value indicating whether the corresponding row should be kept or not.

Returns

• Returns a Table of all of the rows that met the specified condition.

Examples

Filter where an Age is Greater than 30.

      table1 = Table.new [['Name', ['John', 'Paul', 'Ringo']], ['Age', [25, 35, 40]]]
      filter1 = table1.filter 'Age' (..Greater 30)

Returns a Table

Name	Age
Paul	35
Ringo	40

Filter where an Age is Between 30 and 39.

      table1 = Table.new [['Name', ['John', 'Paul', 'Ringo']], ['Age', [25, 35, 40]]]
      filter1 = table1.filter 'Age' (..Between 30 39)

Returns a Table

Name	Age
Paul	35

Select rows where more than 50% of the stock is sold.

      table2 = Table.new [['Name', ['John', 'Paul']], ['sold_stock', [20, 30]], ['total_stock', [50, 50]]]
      filter3= table2.filter 'sold_stock' (..Greater (expr '[total_stock]/2'))

Returns a Table

Name	sold_stock	total_stock
Paul	30	50

Select people celebrating a jubilee.

      table3 = Table.new [['Name', ['John', 'Paul', 'Ringo']], ['Age', [25, 35, 40]]]
      filter4 = table3.filter (expr '[Age] % 10 = 0') ..Is_True

Returns a Table

Name	Age
Ringo	40

Errors

• If a column name cannot be found, a No_Such_Column dataflow error is raised.
• If a column index is invalid, an Index_Out_Of_Bounds dataflow error is raised.
• If the column is an invalid type for the filter, an Invalid_Value_Type dataflow error is raised.
• Additionally, the following problems may be reported according to the on_problems setting:
  • If filtering by equality on a floating-point column, a Floating_Point_Equality will warn the user that comparing floats is imprecise, so results may be inconsistent.

Remarks

Nothing Equality

When comparing Nothing values, filter follows the ANSI SQL conventions that Nothing == Nothing results in a Nothing. This includes both Equal and Is_In conditions. If you want to filter out Nothing use Is_Not_Nothing condition (or Is_Nothing to filter out non-Nothing).