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No, it's not possible to recycle the database, as both tools do very different tasks and therefore they create very specific datastructures to run nice and smooth. Please import another time your DB dump for mapnik, as explained here: www.switch2osm.org


If your organization uses AutoCAD, I would suggest to have a look at ESRI's "ArcGIS for AutoCAD" product. It should theoretically allow a much more streamlined working process between AutoCAD and ArcGIS, where both your ArcGIS and AutoCAD users, can use and edit the same datasets stored in an ESRI Geodatabase via editable webservices. See here for the ...


Wow. Way simpler than I expected. Should not have supposed that 'ogr' wouldn't be able. Anyone have a dunce cap I can borrow? someTableLayer = QgsVectorLayer(ministryOf.csv, 'sillyWalks', 'ogr') QgsMapLayerRegistry.instance().addMapLayer(someTableLayer)


The following snippet works for me: uri = "file:///C:/testdata/somecsv.csv?delimiter=%s" % (";") lyr = QgsVectorLayer(uri, 'New CSV','delimitedtext') QgsMapLayerRegistry.instance().addMapLayer(lyr) For reference, if you wanted to add it with geometry: uri = "file:///C:/testdata/somecsv.csv?delimiter=%s&crs=epsg:4326&xField=%s&yField=%s" % ...


I don't know if this is the cause, but here are some things to check by on; without more details about the dataset and environment, it's really just shots in the dark though. My first though would be to check if the dataset in question has subtypes. If there are subtypes, you can set default field values in the fields tab of the FC properties all day and ...


Arcpy has a built-in function to do this kind of conversion: Convert Time Field. It's mentioned in the first ArcGIS Help link in your question. It can take an ArcGIS date field and convert it to several datatypes, including integer. Here's the syntax: ConvertTimeField_management (in_table, input_time_field, {input_time_format}, output_time_field, ...


I'm sorry if I am misunderstanding the question, but it seems like you could add a new field of text type, and then use the field calculator (either from the table itself or in the python window) to calculate the new field with str( !Node_ID!) + str( !Date_ID!). This would take each row and return a string of the Node_ID and Date_ID together. This is ...

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