You can add columns to your current data table to create a join between data from different sources, and merge it to a single (in-memory) data table in Spotfire. Data can be added from a local file, a data file previously saved in the library, from data connections, from information links, or, from the clipboard.
Even though data from different data tables often can be viewed in the same visualization, it may be preferred to actually incorporate similar data into a single data table. When multiple data tables are used in one visualization, the join of the two tables is done after aggregation has been performed. Therefore, if you want to perform joining of tables before any aggregations, or, if you want to create certain calculated columns based on data from two sources, you might want to insert data from one table to the other.
You add data from the Files and data flyout .
When you add data into your analysis, you can select to add the data as new columns in another data table, from the final step in the add data workflow:
To add columns into a specific place in a data table:
On the authoring bar, click Data canvas .
From the drop-down list in the upper-left part of the Data canvas, select the data table in which to add columns.
In the source view, click the
plus sign between the nodes where you want to insert columns.
Click Add columns.
In the Files and data flyout, locate the data to add by searching for a suitable keyword or by browsing the different categories.
In the summary view, click on the new data to enable editing and click the settings icon to configure how to match columns between the two data sets.
In the Add columns – match columns dialog, verify that the column match suggested by the recommendation engine is the way you want it, or configure the matching as desired. You can add or remove matches, or edit an existing match. To edit a match, click on the row with the match and select one column From original data and one From new data. Click on the x on a row to remove a match. Repeat if necessary.
Comment: When adding columns, matching is done to enable joining between two data sets. Typically, only one or a few columns containing row identifiers should be used in the match.
Tip: If you cannot match your desired columns directly, a transformation added on the node of the original data set might be used to create a calculated column to use in the match.
To the right in the dialog, you see a preview of the data, using the current settings. You can change the Number of input rows to include more rows (from both input tables) in the sample calculation. This may increase the accuracy of the shown result. However, using too many rows can decrease the performance of the preview.
Optionally, if you do not wish to add all available columns from the added data, as is the default, you can select to skip columns under Columns from new data by clearing the check box for the undesired columns.
Under Columns from new data, select the columns that you wish to add from the new data, or clear columns that you want to skip.
Comment: Note that if the data source from which columns were added can be reloaded, and new columns become available after a reload, then the new columns will automatically become included. If this was not desired, you may want to exclude new columns after reloading data by editing the settings for added columns.
Review the Join settings. Look at the interactive Join example, at the bottom of the Join settings field, for information about how rows will be matched using the different join types. You can specify whether or not to match on empty values using the Treat empty values as equal check box.
Comment: Note that selecting an inner join may result in that no data remains in TIBCO Spotfire, if no matching rows are found. You can edit the join settings at a later stage from the data canvas.
Optionally, click Transform data to apply transformations on the new source data.
Comment: See Transforming Data to learn more.
Response: The selected columns are added to your data table.