Display raster properties arcpy vs numpy

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Create feature classes from a pandas data frame

I had a large CAD drawing which I had brought into ArcGIS, converted to a feature class and classified groups of features using a 3 letter prefix. I also had an spreadsheet containing a long list of those prefixes, along with additional columns of information for that prefix, including feature class name and shape type.

I wanted to create the feature classes for dozens of these prefixes, based on the values in my converted feature class, and a template feature class for the field structure. The Select geoprocessing tool could have easily split out all the different features per prefix for me, but that would have kept the CAD feature class structure, and not the structure that I wanted.

I figured this would be a good time to get into pandas (and eventually geopandas, maybe).

In Line 28, I load the first 7 columns on the first sheet in the workbook into a pandas data frame. I set the index column to the column called “Prefix”, so those values will be used for the lookup instead of the default int index pandas assigns.

In Line 37, the prefix value from the feature class is used to look up the corresponding feature class name in the pandas data frame. Once the feature class has been successfully created, a selection layer of the matching features is appended into the new feature class. I could use a SearchCursor and store the matching features in a python list to be copied into the new feature class, but that’s something I will test at another time.

Get the ArcCatalog connections folder location for current user

I wrote this gist because I was tired of manually building up the path for the location where ArcCatalog stores SDE, database and ArcGIS Server connection files. I work on several different machines, so it was very painful to have to change my script each time.

I’m considering creating a global functions file which I include with every toolbox/project, where these sorts of functions are readily available.

View list of ArcGIS Server Data Store Items

Recently I had a task where, for >10 ‘clients’, I had to:

  1. Create a unique database user
  2. Grant privileges to certain datasets in a SDE database
  3. Save an mxd showing only what was relevant to that client
  4. Publish a feature service for consumption in ArcGIS Online

While I will leave the specifics of that delightful script for another post, during debugging I came up against an error where the script would fail if the database connection had already been registered with ArcGIS Server.

In lines 15 and 16, I get the location of the ArcCatalog connections folder for the current user. This is dependent on knowing which version of Arc is installed. I have found a slightly better way (written quite verbosely for clarity):

Toggle labels in a map document

I had a request from the Asset Management team to display all the asset management data I had for a particular area, grouped by service category and with labels displaying their unique IDs. My challenge was to turn on the labels for all the layers using a specific expression. However, the ID fields were not named the same in all the layers (again, the joys of working with data received from outside).

On line 19, I set the label expression for the default label class using the correct field name. The square brackets are what ArcGIS is expecting to delimit field names in the label expression dialog. Line 20 turns the labels on, while line 23 turns the layer on.

Generate chainage along a line feature

This is a request which comes up quite often. Normally, the request is to create points along a pipeline at every 1000m (or some other integer). Sometimes it will be for chainage along a road, but it’s always a line feature which defines a route of some kind. The first time I did this, I used ET GeoWizards, which was an excellent starting point. However, with access to an ArcInfo Advanced licence, I decided to try it using only geoprocessing tools found in ArcToolbox. This did not go well. I then turned to something which I should have turned to at the beginning – Python.