danepitkin commented on code in PR #35656:
URL: https://github.com/apache/arrow/pull/35656#discussion_r1212301675
##########
python/pyarrow/types.pxi:
##########
@@ -1122,6 +1150,19 @@ cdef class DurationType(DataType):
"""
return timeunit_to_string(self.duration_type.unit())
+ def to_pandas_dtype(self):
+ """
+ Return the equivalent NumPy / Pandas dtype.
+
+ Examples
+ --------
+ >>> import pyarrow as pa
+ >>> d = pa.duration('ms')
+ >>> d.to_pandas_dtype()
+ timedelta64[ms]
+ """
+ return _get_pandas_type(_Type_TIMESTAMP, self.unit)
Review Comment:
Great catch! You're correct that this isn't tested yet.
##########
python/pyarrow/types.pxi:
##########
@@ -40,10 +42,20 @@ cdef dict _pandas_type_map = {
_Type_HALF_FLOAT: np.float16,
_Type_FLOAT: np.float32,
_Type_DOUBLE: np.float64,
- _Type_DATE32: np.dtype('datetime64[ns]'),
- _Type_DATE64: np.dtype('datetime64[ns]'),
- _Type_TIMESTAMP: np.dtype('datetime64[ns]'),
- _Type_DURATION: np.dtype('timedelta64[ns]'),
+ _Type_DATE32: np.dtype('datetime64[D]'),
Review Comment:
Thank you! Numpy supports [D]ay, but pandas does not.
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