NumPyArrayToTable

Summary

Converts a NumPy structured array to a table.

Discussion

If a field name from the input array is invalid for the output format, it will be validated. All invalid characters in the input field name are replaced with an underscore (_) in the output field name. Field name restrictions depend on the specific database used.

NumPyArrayToTable will not overwrite an existing table, even if the overwriteOutput environment is set to True.

NumPyArrayToTable only accepts structured arrays. If you have a regular NumPy ndarray, it must first be converted to a structured array. Below, the original array is transposed, and the numpy.core.records.fromarrays method is used to create the new structured array.

import numpy
import arcpy

a = numpy.array([(0.2, 1.0), (0.5, 2.5)])
struct_array = numpy.core.records.fromarrays(
    a.transpose(), numpy.dtype([("Value1", "f8"), ("Value2", "f8")])
)

arcpy.da.NumPyArrayToTable(struct_array, "c:/data/f.gdb/array_output")

NumPy is a fundamental package for scientific computing in Python, including support for a powerful N-dimensional array object. For more information, see Working with NumPy in ArcGIS.

Syntax

NumPyArrayToTable (in_array, out_table)

Parameter	Explanation	Data Type
in_array	A NumPy structured array. The array must include field names and NumPy dtypes.	NumPyArray
out_table	The table to which the records from the NumPy array will be written.	String

Code sample

NumPyArrayToTable example 1

import arcpy
import numpy

# Create a simple array from scratch
inarray = numpy.array(
    [("a", 1, 1111.0), ("b", 2, 2222.22)],
    numpy.dtype(
        [("textfield", "|S256"), ("intfield", numpy.int32), ("doublefield", "<f8")]
    ),
)

# Convert array to a geodatabase table
arcpy.da.NumPyArrayToTable(inarray, "c:/data/gdb.gdb/out_table")

NumPyArrayToTable example 2

import arcpy
import numpy

# Create a simple array from scratch using a list of values
recs = [["M", 64, 75.0], ["F", 25, 60.0]]
dts = {
    "names": ("gender", "age", "weight"),
    "formats": ("S1", numpy.uint8, numpy.float32),
}
array = numpy.rec.fromrecords(recs, dtype=dts)

# Convert array to a geodatabase table
arcpy.da.NumPyArrayToTable(array, "c:/data/gdb.gdb/out_table")