• Column properties
Column properties are shown in the right pane of the data studio by clicking on any column that is included in the report.
Displayed title that is shown in column headers, legends and tooltips.
The default value is sourced from the column metadata of the dataset.
Provides a means to override the column type defined in the dataset metadata. This can be useful to display the raw value of a field by transforming it into a string, or to convert from numbers to currency.
The column can be hidden from view by setting the display setting to not show, see below.
Hide the column from view in the result. You can still use the column data for filtering and for constructing derived columns.
Display data as a string. Strings are not formatted.
Display data as a number. Numbers are formatted using the browser built-in formatting functions using the locale of the workspace.
Display data as a date. Dates are formatted using the built-in formatting functions using the locale of the workspace.
Display data as a currency. The currency value will be formatted using the browser built-in formatting functions using the locale of the workspace.
Display data as a boolean true/false value. This type of data may be rendered differently based on the selected visualization type.
Longitudes are numerical values that have been flagged for use in a map visualization.
Latitudes are numerical values that have been flagged for use in a map visualization.
By default, the date granularity is automatic and will be determined based on the date range constraints of the report.
If the column has been constrained by a filter on the column itself, the system will look at the date range and make a determination of an appropriate date granularity to produce what would be a reasonable number of rows in the resultset every day in the range had a row and the column was the only dimensional row in the resultset.
The following logic is used:
|Number of days in span||Granularity|
|a week or less||hourly|
|a year or less||daily|
|four years or less||monthly|
The date granularity will be automatically determined based on the active date range, if applicable. Defaults to daily granularity if no date range can be calculated.
Display the date in a full format including hour of the day.
Display the date with daily granularity.
Display the date with monthly granularity
Display the date with only the year.
Set a custom date format. The date is formatted per the format string.
Specify if the all values with the same value should be grouped into a single line or not. Grouping by a column makes it similar to a dimension.
Group by this column¶
Enable aggregation of identical values into a single row. This has the effect of adding the column into the
GROUP BY statement of the SQL query.
Do not group by this column. Values appear as they are returned from the underlying data.
Count the number of values. This is the equivalent of SQL
Return the average of the values in the group. This is the equivalent of SQL
Return the summation of the values in the group. This is the equivalent of SQL
Return the smallest of the values in the group. This is the equivalent of SQL
Return the largest of the values in the group. This is the equivalent of SQL
Specify a default value when the value in the resultset is missing (or in database terminology a null value.)
Set a custom format. The value can be formatted using the Excel formatting language (ECMA-376). Custom formats can be constructed online.
Examples of date formatting:
Transform the measure by applying a transformation. Calculated columns can be used to easily apply resultset wide adjustments to a specfic series of values.
No calculation is performed and the values are presented as they appear based on aggregation
Percent of Total¶
The sum of all of the values of the measure is calculated and the value of each row is set to the percentage of the total represented by the value in the row.
Calculate a running total of the values in the columnn from top to bottom.
Calculate a moving average of the values in the column. The moving average is based on the average of the four prior values.
Column filters are the equivalent of SQL such as
COUNT(CASE WHEN column = 'VALUE' THEN 1 END)