The feature class, layer, table, or table view.

A list (or tuple) of field names. For a single field, you can use a string instead of a list of strings.

Use an asterisk (*) instead of a list of fields if you want to access all fields from the input table (raster and BLOB fields are excluded). However, for faster performance and reliable field order, it is recommended that the list of fields be narrowed to only those that are actually needed.

Raster and BLOB fields are not supported. Geometry objects are not supported using the SHAPE@ token, but geometry information can be included using other tokens such as SHAPE@XY (tuple of the feature's centroid coordinates), SHAPE@AREA, and SHAPE@LENGTH.

Additional information can be accessed using tokens (such as OID@) in place of field names:

import arcpy
array = arcpy.da.FeatureClassToNumPyArray(fc, ["OID@", "SHAPE@XY"])

# The first row would look similar to the following:
#  (1, [-147.82339477539062, 64.86953735351562])
print(array[0])

SHAPE@M and SHAPE@Z tokens will only return values if the in_table contains point features and is m-aware (or z-aware). If the in_table contains polygon, polyline, or multipart features, SHAPE@M and SHAPE@Z will return a nan. Any feature class that is not m-aware or z-aware will not support SHAPE@M and SHAPE@Z tokens.

(The default value is *)

An optional expression that limits the records returned. For more information on WHERE clauses and SQL statements, see .

(The default value is "")

The spatial reference of the feature class. It can be specified with either a SpatialReference object or string equivalent.

import arcpy
SR = arcpy.Describe(fc2).spatialReference
arcpy.da.FeatureClassToNumPyArray(fc,
                                  ["OID@", "SHAPE@XY", "EDUCATION"], 
                                  spatial_reference=SR)

(The default value is None)

Deconstruct a feature into its individual points or vertices. If explode_to_points is set to True, a multipoint feature with five points, for example, is represented by five rows.

(The default value is False)

Control whether records using nulls are skipped. It can be either a Boolean True or False, or a Python function or lambda expression.

When set to True, if any of the record's attributes is null (including geometry), the record is skipped. With a False setting, skip_nulls attempts to use all records regardless of nulls. In a NumPy array, a null is represented as a nan (not a number) for floating-point numeric values but not for integers.

import arcpy
array = arcpy.da.FeatureClassToNumPyArray(fc, fields, skip_nulls=True)

A Python function or lambda expression can be used to allow finer control, including logging the OID values of all records that include a null value. In both examples below, the lambda expression or function is used to identify OIDs that include null records.

import arcpy
def getnull(oid):
    nullRows.append(oid)
    return True
nullRows = list()
array = arcpy.da.FeatureClassToNumPyArray(table, fields, skip_nulls=getnull)
print(nullRows)

import arcpy
nullRows = list()
array = arcpy.da.FeatureClassToNumPyArray(fc, fields, 
                                    skip_nulls=lambda oid: nullRows.append(oid))
print(nullRows)

(The default value is False)

Replaces null values from the input with a new value.

null_value is replaced before skip_nulls is evaluated.

import arcpy
fields = ['field1', 'field2']
arcpy.da.FeatureClassToNumPyArray(fc, fields, null_value=-9999)

import arcpy
fields = ['field1', 'field2']
nullDict = {'field1':-999999, 'field2':-9999}
arcpy.da.FeatureClassToNumPyArray(fc, fields, null_value=nullDict)

(The default value is None)