Filters 101 - Part 3

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In part 2, some simple filters were shown to help you understand the components of a database filter. A database filter can be very simple, or fairly complex - it depends on the type of report that you are attempting to create.


In it's most simple form database filters can be used for three different situations:


You are extracting information based on text


You are extracting information using numbers


You are extracting information based on a logical condition


Here are some situation descriptions and a simple database filter for each:


Customers who drive a BMW

 CUS:CarType = 'bmw'


Products made by MierWater

 ITM:Company = 'mierwater'


Items with an onhand quantity greater than 20

 ITM:QtyOnhand > 20


Children who are too young to be in Kindergarten

 Nam:Age < 7


Customers who have pets

 NAM:Pets = 1


Items with no detailed information available

 ITM:Detailed = 0


The six example filters above are very simple in structure, but some interesting details quickly become apparent:


The first two filters for Text-type filters require a quote symbol (') before and after the text string that you are comparing against the database field


The next two filters for Integer-type filters don't use a quote symbol; that would make them a text string!


The last two filters for Logical-type filters use either a 0 (False) or 1 (True) to indicate true or false. This is because the information for this database field is stored as a one position integer in the database. For those of you with dBase experience this is quite different than what you are used to. dBase stores a value of true as "Y" or "T", and a negative value as "N" or "F".