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Multiple Data Driven Frames Using Python

Johnkelly4

I've been trying to write a script that can do the following:

Example:
-Two frames on a layout, one on top and one on the bottom
-10 data driven pages
-It would display DDP's 1, 3, 5, 7, 9 top frame and DDP's 2, 4, 6, 8, 10 on the bottom frame, for a total of 5 sheets of paper.

Below is what I have come up with so far. The script runs them one at a time instead of together. Anyone know what I am missing?

import arcpy
import time

mxd = arcpy.mapping.MapDocument("CURRENT")

#Lists all dataframes within the mxd
df1 = arcpy.mapping.ListDataFrames(mxd,"Layers")[0]
df2 = arcpy.mapping.ListDataFrames(mxd,"Layer 02")[0]
lyr = arcpy.mapping.ListLayers(mxd, "", df2)[0]
rows = arcpy.SearchCursor(lyr,"CATEGORY = 'Even'",
                          fields="Shape; Id; CATEGORY; Name",
                          sort_fields="Id A")

for pageNum in range(1, mxd.dataDrivenPages.pageCount + 1,2):  
  mxd.dataDrivenPages.currentPageID = pageNum
  for row in rows:
    df2.extent = row.Shape.extent
    df2.scale = 2400
    arcpy.RefreshActiveView()
    time.sleep(2)
    print row.getValue("Name")
del mxd

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Johnkelly4

Got it! Thanks again for all your help!!

Johnkelly4

Ah ok, I think I will be fine in that case. Will I be able to call on different field information with this? For example: I have a field called scale that determines the scale for each extent (1:2,400, 1:3,600, etc). So could something like this work:

import time  
mxd = arcpy.mapping.MapDocument("CURRENT")  
df1 = arcpy.mapping.ListDataFrames(mxd,"Layers")[0]  
df2 = arcpy.mapping.ListDataFrames(mxd,"Layer02")[0]
fc = "D:\Practice\Arcpy\New_Shapefile.shp"
index = fc # my DDP index layer

features = {row[0]:row[1] for row in arcpy.da.SearchCursor
            (index,['ID','SHAPE@','Scale'])} # all index features  
for pageNum in range(1,mxd.dataDrivenPages.pageCount,2):  
    mxd.dataDrivenPages.currentPageID = pageNum  
    df1.extent = features[pageNum].extent
    df1.scale = Scale
    df2.extent = features[pageNum+1].extent
    df2.scale = Scale
    arcpy.RefreshActiveView
    print ['ID']
    arcpy.mapping.ExportToPDF(mxd, r"D:\Practice\Arcpy\Page_" + str(pageNum) + ".pdf")
    time.sleep(2)
del mxd

DarrenWiens2

It just doesn't actually read the available IDs. It assumes that every ID exists between 1 and the length of the list. If you happened to have IDs 1, 2, 3, 5 (missing 4), when the loop is on 3 it will look for value 4 (pageNum+1), but since it's not there, there will be an error. If all your IDs exist, there should be no problem.

Johnkelly4

Thank you sir! Your version seemed to work (and was much cleaner). What exactly did you mean by 'nice' data and missing IDs? What kinds of problems do you see with this?

DarrenWiens2

This seems to work using a modern cursor. This works for 'nice' data, but you may have to do some work if you're missing IDs or something.

>>> import time
... mxd = arcpy.mapping.MapDocument("CURRENT")
... df1 = arcpy.mapping.ListDataFrames(mxd,"Layers1")[0]
... df2 = arcpy.mapping.ListDataFrames(mxd,"Layers2")[0] 
... index = 'buff' # my DDP index layer
... features = {row[0]:row[1] for row in arcpy.da.SearchCursor(index,['ID','SHAPE@'])} # all index features
... for pageNum in range(1,mxd.dataDrivenPages.pageCount,2):
...    mxd.dataDrivenPages.currentPageID = pageNum
...    df1.extent = features[pageNum].extent
...    df2.extent = features[pageNum+1].extent
...    arcpy.RefreshActiveView
...    time.sleep(2)

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