[Qgis-user] Preserving geometry when batching joins

[Samuel Williams]

Hello,

I've hit a issue in Qgis that I'm struggling to resolve, and I'm hoping that someone might be able to point me in the right direction.
I have 12 point geometry data sets and 12 csv files. Each csv file contain the attributes for one of the point data sets - there are exactly the same number of records in each point / csv pair:
Points1.shp:
-- point 1 UID
-- point 2 UID
..
-- point 980 UID

Attributes1.csv:
-- record 1 (Point 1 UID, blah, blah, whatever)
-- record 2 (Point 2 UID, blah, blah, whatever)
...
-- record 980 (Point 980 UID, blah, blah, whatever)

I've loaded them all into Qgis and was hoping that I could join them as a batch process, so that I end up with 12 point geometry shapefiles, with each point associated with the equivalent record from the matching csv file.... I've had some success, in that the batch interface to join allows me to list the input layers, fields for the joins and the output file names very easily, but I can't work out how to preserve the geometry of the points. The only file type listed that I can save are DBF / XLSX / CSV / ODS files, which will only preserve the joined tables not the geometry.
Am I approaching this whole problem in the wrong way, or is there something very obvious that I've missed?
I'm using:

QGIS version

2.18.17

QGIS code branch

Release 2.18 (https://link.getmailspring.com/link/1527454204.local-f62ddf4d-2b7e-v1.2.1-7e7447b6@getmailspring.com/0?redirect=https%3A%2F%2Fgithub.com%2Fqgis%2FQGIS%2Ftree%2Frelease-2_18&recipient=cWdpcy11c2VyQGxpc3RzLm9zZ2VvLm9yZw%3D%3D)

Compiled against Qt

4.8.7

Running against Qt

4.8.7

Compiled against GDAL/OGR

2.2.3

Running against GDAL/OGR

2.2.3

Compiled against GEOS

3.6.2-CAPI-1.10.2

Running against GEOS

3.6.2-CAPI-1.10.2 4d2925d6

PostgreSQL Client Version

10.2 (Ubuntu 10.2-1)

SpatiaLite Version

4.3.0a

QWT Version

6.1.3

PROJ.4 Version

493

QScintilla2 Version

2.10.2

This particular workstation is running Ubuntu 18.04 on amd64 hardware.

Any suggestions welcomed - I know that for just 12 data sets I could probably have done the joins manually in the time it has taken to type this out, but I'm really curious as to whether there is a better way.
Cheers,
Sam
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