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Cards in this section are used to visualize, aggregate, or transform data in a table format.
Visualize a Foundry dataset in your analysis. Datasets opened in Quiver can only be used in the time series preview card if they have a specific time series schema.
Foundry dataset cards are a Beta feature and may not be available on your Foundry instance.
Display a list of all objects in an object set. The List card is useful if you want to open an individual object in Object Explorer.
A pivot table is used to display aggregated data over an object set in a table. Object properties are chosen as row and column properties; the resulting data is grouped by these object properties and aggregated based on the configuration you set in the Editor panel. Pivot tables are mainly configured in three ways: row properties, column properties, and aggregations.
Row properties are the properties with values that will be the row headers of the table. Rows will only appear in the table for sets of values with data.
Column properties are the properties with values that will be the column headers of the table. Columns will only appear in the table for sets of values with data.
Aggregation configurations allow you to set the way you want the data to be aggregated for each cell, grouped by row and column properties. Five configuration options are available for aggregations:
Alternatively, you can select Switch to formula metric to write your own metric composed of the aggregations listed above. You can also select +Add Series to configure as many aggregations as you want. The aggregations will appear next to each other with their own column headers below the headers representing column property values.
For example, supppose you have a dataset of daily precipitation by city in the United States. If you select city as a row property, year as a column property, and sum of precipitation as an aggregation, then the column headers will be New York, Chicago, and Los Angeles, the row headers will be 2015, 2016, and 2017, and the values will be the total precipitation in that city during that year. If no row or column properties are specified, the aggregation will be computed over all objects.
The only difference between row and column properties is on which edge of the table they appear. For example, if you have configured row properties A and B with no column properties, the data will be the same as if you had row property A and column property B, or column properties A and B with no row properties. Only the layout of the data will be different.
You can use the pivot table to filter data. Select individual cells or entire rows and columns by clicking on the headers. Clicking Drill down to selection will filter the data to those with the property values for the rows and columns you selected. Hold down the shift or command key to select multiple regions of the table.
You can also activate the toggle to Show grand totals for rows or columns to show aggregates on the right side (for rows) or bottom (for columns). Be aware that these aggregates apply over all of the data for that set of row or column properties; it is not an aggregate of aggregates. Select the info icon next to this option for a deeper explanation of how grand totals are computed.
Show chosen properties of your chosen objects as rows of a table and use this to manually select certain objects for drill-down if desired. Tables can also include the properties of linked objects and time series (measures or time dependent properties) of the object displayed as sparklines.
Transform tables are data structures that allow users to join and aggregate objects, derive properties and perform options on derived properties, edit tabular data in-line, and perform batch time series operations. For a complete list of transforms available in transform tables, consult the index of transform table transformations.