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10.4 Null Values

When no special steps are taken, if a null value (blank cell) is encountered in evaluating an expression (usually because one of the columns it relies on has a null value in the row in question) then the result of the expression is also null.

It is possible to exercise more control than this, but it requires a little bit of care, because the expressions work in terms of primitive values (numeric or boolean ones) which don't in general have a defined null value. The name "null" in expressions gives you the java null reference, but this cannot be matched against a primitive value or used as the return value of a primitive expression.

For most purposes, the following two tips should enable you to work with null values:

Testing for null
To test whether a column contains a null value, prepend the string "NULL_" (use upper case) to the column name or $ID. This will yield a boolean value which is true if the column contains a blank or a floating point NaN (not-a-number) value, and false otherwise. Note that if combined with other boolean expressions, this null test should come first, i.e. write "NULL_i || i==999" rather than "i==999 || NULL_i", though this is only essential for integer or boolean variables.
Returning null
To return a null value from a numeric expression, use the name "NULL" (upper case). To return a null value from a non-numeric expression (e.g. a String column) use the name "null" (lower case).

Null values are often used in conjunction with the conditional operator, "? :"; the expression

   test ? tval : fval
returns the value tval if the boolean expression test evaluates true, or fval if test evaluates false. So for instance the following expression:
   Vmag == -99 ? NULL : Vmag
can be used to define a new column which has the same value as the Vmag column for most values, but if Vmag has the "magic" value -99 the new column will contain a blank. The opposite trick (substituting a blank value with a magic one) can be done like this:
   NULL_Vmag ? -99 : Vmag
Some more examples are given in Section 10.8.

Note that for floating point data, STILTS treats null and NaN (Not-a-Number) values somewhat interchangeably. Blank values arising either from an input file format that can represent missing values, or from processing that fails to provide a definite value, are in most cases represented internally as null for integer-type values and NaN for floating point values. However in general users should not rely on distinguishing between null and NaN.

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