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Version: Python


The dh_null_to_nan method converts Deephaven primitive null values in the given numpy array to numpy.nan. No conversion is performed on non-primitive values.


The input numpy array is modified in place if it is a float or double type. If that is not the desired behavior, pass a copy of the new array instead. For input arrays of other types, a new array is always returned and the input numpy array is unmodified.


np_array: numpy.ndarray,
type_promotion: bool = False,
) -> numpy.ndarray



The numpy array to convert.

type_promotion optionalbool

When True, integer, boolean, or character arrays are converted to new np.float64 arrays and Deephaven null values in them are converted to np.nan. Numpy arrays of float or double types are not affected by this flag, and Deephaven nulls will always be converted to np.nan in place.

When False, integer, boolean, or character arrays will cause an exception to be raised. Default is False.


A numpy.ndarray.


In the example below, we create a simple Deephaven table with null values. We then convert the table to a numpy array and use dh_null_to_nan to convert the Deephaven null values to numpy.nan.

from deephaven import new_table
from deephaven.column import int_col
from deephaven.constants import NULL_INT

source = new_table(
[int_col("Number1", [1, NULL_INT, 3]), int_col("Number2", [1, 2, NULL_INT])]

from deephaven.numpy import to_numpy
from deephaven.jcompat import dh_null_to_nan

np = to_numpy(source)

np_nan = dh_null_to_nan(np, True)