Paste and merge is the term used when appending (importing) new data to an existing, i.e. already saved, OrgVue dataset: it is a common action within OrgVue operational activity that new records (nodes) or new elements (properties) are required to be added into what is already there.
- This applies for working with multiple documents, just ensure you save the updated OrgVue dataset after each cycle of adding a new .csv file to a saved dataset
If there are error messages shown after the paste-merge process, for best results check and resolve these before save, see here for further advice.
When you add i.e paste a new data file into an existing OrgVue dataset, OrgVue automatically reviews the present dataset structure versus the new imported data and if there is a match, OrgVue will manage the process of merging the two documents.
For clarity, there are two elements to paste and merge:
- "Paste" is selecting the Paste option within an existing (saved) dataset in OrgVue, i.e. the dataset is open in OrgVue when you select paste, so you can import additional data into the dataset
- "Merge" is the workflow that OrgVue itself manages: merge is triggered because OrgVue recognises that there are common properties or values between the imported (pasted) data and existing dataset.
- For a typical People-type dataset where there is a ID field on which to merge, that will be the predetermined merge field and the below dialogue will not be shown, as it is not required: where there is more than one merge option, that will show as a dropdown
(Note: this article focuses on "Merge on Field" with is synonymous with Tree by Level which is the standard approach for OrgVue hierarchies. "Merge on position" is synonymous with Tree by ID - see here- - but otherwise the content here is equally applicable)
- Once OrgVue has verified there is a common structure between existing and imported data, an additional dialogue is displayed where other options will appear
Pre-requisites for a successful paste-merge
These are as listed below (these are usually a given, but worth checking for troubleshooting purposes):
- Incoming data must be structured in a CSV-type format e.g. Excel worksheet
- Incoming data must include headers
- Incoming data must have at least one common property between incoming (pasted) data and existing dataset. In practice this means, one column header in the incoming data must be the same as a property key in the dataset
- Incoming data must have matching values/IDs if existing nodes are to have their associated property set updated
OrgVue will work out itself if you are adding new nodes (rows) or properties (columns) or both.
The 6 exhibits below indicate the impact of paste.
The following simple dataset is the saved dataset into which the examples below are pasted.
The following is some new data being pasted into a standard people dataset (note, no ID property):
Pasting generates error as no headers (properties) are associated with pasted data:
Pasting generates the following dialogue, as OrgVue recognises Country as being common between source and destination:
However paste fails as node values have no match with existing dataset
Pasting generates the standard merge dialogues, as OrgVue recognises Country as being common between source and destination, however only one node is merged given only one match with existing dataset
Two new properties are now available - not shown by default, available for selection
This merge executes as a simple overwrite, given [Country] property name and [UK] property value match the existing dataset.
Pasting generates the standard merge dialogues, as OrgVue recognises Country as being common between source and destination, and provides options for merging given there are both common and new nodes in the source/destination
Pasting generates the standard merge dialogue, as OrgVue recognises Country as being common between source and destination, and provides options for merging given there are both common and new nodes in the source/destination, however default options change versus Exhibit Five given missing ID 4