The CASE function returns dimensions and metrics based on conditional expressions it is often used to create new groupings of data and sort them in categories. Enjoy! What is the Data Studio CASE function? *NEW – By popular demand, I have decided to expand the comprehensive guide on CASE and added IF statements, as the Google Data Studio team has had some incredible updates over the past year. In addition, I have added a section on how to compose the new Simplified CASE statements. I personally think that knowing how to write a CASE is not only helpful in Data Studio, but also it allows you to understand how computer logic works. The date/time constant must be in combined UTC format, as described in Formatting DateTime Property Values.In this post, we are going to explore one of the most useful functions in Google Data Studio, the CASE. To filter on a DateTime value, specify the datetime keyword, followed by the date/time constant in single quotation marks. ![]() To return all entities where IsActive is false, you can use the not operator: not IsActive In the following example, the Table service will also return all entities where IsActive is true: IsActive You can also write this filter expression without the logical operator. The following example returns all entities where the IsActive property is set to true: IsActive eq true To filter on a Boolean value, specify true or false without quotation marks. This example returns all entities with an AmountDue property whose value is less than or equal to 100.25: AmountDue le 100.25 This example returns all entities with an Age property whose value is greater than 30: Age gt 30 To filter on an integer or floating-point number, specify the number without quotation marks. The following example returns entities with a LastName property beginning with the letter 'A': LastName ge 'A' and LastName lt 'B' However, you can perform prefix matching by using comparison operators on the desired prefix. Note that the Table service does not support wildcard queries, and they are not supported in the Table Designer either. You can enclose each filter expression in parentheses, although it is not required: (PartitionKey eq 'Partition1') and (RowKey eq '00001') The following example filters on the PartitionKey and RowKey properties additional non-key properties could also be added to the filter string: PartitionKey eq 'Partition1' and RowKey eq '00001' When you filter on string properties, enclose the string constant in single quotation marks. For more information about supported property types, see Understanding the Table Service Data Model. The constant value must be of the same data type as the property in order for the filter to return valid results.All parts of the filter string are case-sensitive.Note that it is not possible to compare a property to a dynamic value one side of the expression must be a constant. Use the logical operators to compare a property to a value.When constructing a filter string, the following rules are important: The following logical operators are supported for all property types: Logical operator For details on the filter system query option ( $filter), see the OData URI Conventions specification. The WCF Data Services are based on the Open Data Protocol (OData). You do not need to include the $filter query option as you would if you were constructing a URL to query the table via the Storage Services REST API Reference. The Table Designer handles the proper encoding for you, so to filter on a desired property value, you need only enter the property name, comparison operator, criteria value, and optionally, Boolean operator in the filter field. The filter string syntax is defined by the WCF Data Services and is similar to a SQL WHERE clause, but is sent to the Table service via an HTTP request. To filter data in an Azure table that is displayed in the Visual Studio Table Designer, you construct a filter string and enter it into the filter field. Applies to: Visual Studio Visual Studio for Mac Visual Studio Code Overview
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