Simple arrays of the same dtype are easy to put together. Arcpy has some of this functionality in the arcpy.da section like Extend Table as well as the conversion to-from arc* to numpy Its initial use was for matplotlib and it is functionality has never made it mainstream numpy since the functions are in essence shells for basic numpy array operations with the ugliness of reshaping and reformulating arrays hidden from the gentle user. When I am working with numpy arrays and wish to concatenate or join arrays or columns together, use recfunctions which is housed in the numpy.lib folder. In short, maybe your arcpy.da.ExtendTable(in_features, "OBJECTID " ,nparra圓, ") just isn't cutting it with your dtype and/or environment. Hard to follow with all that toolbox stuff. If anyone wants to take a look, my toolbox is available at: CenterForRegionalChange/QuantileCalc I have tried multiple formulations of the dtype values with the same result from: If I run the same section of code for creating the copy of the structured array using only the existing fields, it also works (at least that far) in the Python Toolbox. So does cutting and pasting the lines of code into the Python window in ArcCatalog. What's odd about this, is the same code differing (as far as I can see) only in externally providing the parameter values works fine in an IDE (Eclipse/PyDev using the same Python interpreter). When I try to add a new field to the the resulting structured array using the code in a Python Toolbox, I get the following error: It extracts the needed fields (OID, and the selected field) from a feature class using arcpy.da.FeatureClassToNumPyArray. It adds a new column to a dataset that containing the quantile that a data field falls into (number of quantiles is an input as is the field, and an option to invert the quantile numbers). I've got a script that I'm trying to get into a python toolbox for use and distribution.Numpy add arrays together code#