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API: Disallow dtypes w/o frequency when casting (pandas-dev#23392)
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Previously deprecated for Series constructor
and the `.astype` method. Now being enforced.

xref pandas-devgh-15987.
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gfyoung authored and Pingviinituutti committed Feb 28, 2019
1 parent 40d6ada commit 87f29a0
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Showing 4 changed files with 46 additions and 64 deletions.
1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.24.0.txt
Original file line number Diff line number Diff line change
Expand Up @@ -942,6 +942,7 @@ Removal of prior version deprecations/changes
- Removal of the previously deprecated module ``pandas.core.datetools`` (:issue:`14105`, :issue:`14094`)
- Strings passed into :meth:`DataFrame.groupby` that refer to both column and index levels will raise a ``ValueError`` (:issue:`14432`)
- :meth:`Index.repeat` and :meth:`MultiIndex.repeat` have renamed the ``n`` argument to ``repeats`` (:issue:`14645`)
- The ``Series`` constructor and ``.astype`` method will now raise a ``ValueError`` if timestamp dtypes are passed in without a frequency (e.g. ``np.datetime64``) for the ``dtype`` parameter (:issue:`15987`)
- Removal of the previously deprecated ``as_indexer`` keyword completely from ``str.match()`` (:issue:`22356`, :issue:`6581`)
- Removed the ``pandas.formats.style`` shim for :class:`pandas.io.formats.style.Styler` (:issue:`16059`)
- :func:`pandas.pnow`, :func:`pandas.match`, :func:`pandas.groupby`, :func:`pd.get_store`, ``pd.Expr``, and ``pd.Term`` have been removed (:issue:`15538`, :issue:`15940`)
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24 changes: 11 additions & 13 deletions pandas/core/dtypes/cast.py
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,6 @@
from datetime import datetime, timedelta

import numpy as np
import warnings

from pandas._libs import tslib, lib, tslibs
from pandas._libs.tslibs import iNaT, OutOfBoundsDatetime, Period
Expand Down Expand Up @@ -664,6 +663,11 @@ def astype_nansafe(arr, dtype, copy=True, skipna=False):
e.g. the item sizes don't align.
skipna: bool, default False
Whether or not we should skip NaN when casting as a string-type.
Raises
------
ValueError
The dtype was a datetime /timedelta dtype, but it had no frequency.
"""

# dispatch on extension dtype if needed
Expand Down Expand Up @@ -745,12 +749,9 @@ def astype_nansafe(arr, dtype, copy=True, skipna=False):
return astype_nansafe(to_timedelta(arr).values, dtype, copy=copy)

if dtype.name in ("datetime64", "timedelta64"):
msg = ("Passing in '{dtype}' dtype with no frequency is "
"deprecated and will raise in a future version. "
msg = ("The '{dtype}' dtype has no frequency. "
"Please pass in '{dtype}[ns]' instead.")
warnings.warn(msg.format(dtype=dtype.name),
FutureWarning, stacklevel=5)
dtype = np.dtype(dtype.name + "[ns]")
raise ValueError(msg.format(dtype=dtype.name))

if copy or is_object_dtype(arr) or is_object_dtype(dtype):
# Explicit copy, or required since NumPy can't view from / to object.
Expand Down Expand Up @@ -1019,16 +1020,14 @@ def maybe_cast_to_datetime(value, dtype, errors='raise'):

if is_datetime64 or is_datetime64tz or is_timedelta64:

# force the dtype if needed
msg = ("Passing in '{dtype}' dtype with no frequency is "
"deprecated and will raise in a future version. "
# Force the dtype if needed.
msg = ("The '{dtype}' dtype has no frequency. "
"Please pass in '{dtype}[ns]' instead.")

if is_datetime64 and not is_dtype_equal(dtype, _NS_DTYPE):
if dtype.name in ('datetime64', 'datetime64[ns]'):
if dtype.name == 'datetime64':
warnings.warn(msg.format(dtype=dtype.name),
FutureWarning, stacklevel=5)
raise ValueError(msg.format(dtype=dtype.name))
dtype = _NS_DTYPE
else:
raise TypeError("cannot convert datetimelike to "
Expand All @@ -1044,8 +1043,7 @@ def maybe_cast_to_datetime(value, dtype, errors='raise'):
elif is_timedelta64 and not is_dtype_equal(dtype, _TD_DTYPE):
if dtype.name in ('timedelta64', 'timedelta64[ns]'):
if dtype.name == 'timedelta64':
warnings.warn(msg.format(dtype=dtype.name),
FutureWarning, stacklevel=5)
raise ValueError(msg.format(dtype=dtype.name))
dtype = _TD_DTYPE
else:
raise TypeError("cannot convert timedeltalike to "
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38 changes: 16 additions & 22 deletions pandas/tests/series/test_constructors.py
Original file line number Diff line number Diff line change
Expand Up @@ -1192,32 +1192,26 @@ def test_constructor_cast_object(self, index):
exp = Series(index).astype(object)
tm.assert_series_equal(s, exp)

def test_constructor_generic_timestamp_deprecated(self):
# see gh-15524

with tm.assert_produces_warning(FutureWarning):
dtype = np.timedelta64
s = Series([], dtype=dtype)

assert s.empty
assert s.dtype == 'm8[ns]'

with tm.assert_produces_warning(FutureWarning):
dtype = np.datetime64
s = Series([], dtype=dtype)
@pytest.mark.parametrize("dtype", [
np.datetime64,
np.timedelta64,
])
def test_constructor_generic_timestamp_no_frequency(self, dtype):
# see gh-15524, gh-15987
msg = "dtype has no frequency. Please pass in"

assert s.empty
assert s.dtype == 'M8[ns]'
with tm.assert_raises_regex(ValueError, msg):
Series([], dtype=dtype)

# These timestamps have the wrong frequencies,
# so an Exception should be raised now.
msg = "cannot convert timedeltalike"
with tm.assert_raises_regex(TypeError, msg):
Series([], dtype='m8[ps]')
@pytest.mark.parametrize("dtype,msg", [
("m8[ps]", "cannot convert timedeltalike"),
("M8[ps]", "cannot convert datetimelike"),
])
def test_constructor_generic_timestamp_bad_frequency(self, dtype, msg):
# see gh-15524, gh-15987

msg = "cannot convert datetimelike"
with tm.assert_raises_regex(TypeError, msg):
Series([], dtype='M8[ps]')
Series([], dtype=dtype)

@pytest.mark.parametrize('dtype', [None, 'uint8', 'category'])
def test_constructor_range_dtype(self, dtype):
Expand Down
47 changes: 18 additions & 29 deletions pandas/tests/series/test_dtypes.py
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,6 @@

import string
import sys
import warnings
from datetime import datetime, timedelta

import numpy as np
Expand All @@ -21,7 +20,7 @@
from pandas.compat import lrange, range, u


class TestSeriesDtypes():
class TestSeriesDtypes(object):

def test_dt64_series_astype_object(self):
dt64ser = Series(date_range('20130101', periods=3))
Expand Down Expand Up @@ -396,40 +395,30 @@ def test_astype_categoricaldtype_with_args(self):
with pytest.raises(TypeError):
s.astype(type_, categories=['a', 'b'], ordered=False)

def test_astype_generic_timestamp_deprecated(self):
# see gh-15524
@pytest.mark.parametrize("dtype", [
np.datetime64,
np.timedelta64,
])
def test_astype_generic_timestamp_no_frequency(self, dtype):
# see gh-15524, gh-15987
data = [1]
s = Series(data)

with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
s = Series(data)
dtype = np.datetime64
result = s.astype(dtype)
expected = Series(data, dtype=dtype)
tm.assert_series_equal(result, expected)

with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
s = Series(data)
dtype = np.timedelta64
result = s.astype(dtype)
expected = Series(data, dtype=dtype)
tm.assert_series_equal(result, expected)
msg = "dtype has no frequency. Please pass in"
with tm.assert_raises_regex(ValueError, msg):
s.astype(dtype)

@pytest.mark.parametrize("dtype", np.typecodes['All'])
def test_astype_empty_constructor_equality(self, dtype):
# see gh-15524

if dtype not in ('S', 'V'): # poor support (if any) currently
with warnings.catch_warnings(record=True):
if dtype in ('M', 'm'):
# Generic timestamp dtypes ('M' and 'm') are deprecated,
# but we test that already in series/test_constructors.py
warnings.simplefilter("ignore", FutureWarning)

init_empty = Series([], dtype=dtype)
as_type_empty = Series([]).astype(dtype)
tm.assert_series_equal(init_empty, as_type_empty)
if dtype not in (
"S", "V", # poor support (if any) currently
"M", "m" # Generic timestamps raise a ValueError. Already tested.
):
init_empty = Series([], dtype=dtype)
as_type_empty = Series([]).astype(dtype)
tm.assert_series_equal(init_empty, as_type_empty)

def test_complex(self):
# see gh-4819: complex access for ndarray compat
Expand Down

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