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CLN: Split and parameterize test_to_timedelta.py #44843

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Merged
merged 2 commits into from
Dec 10, 2021
Merged

CLN: Split and parameterize test_to_timedelta.py #44843

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CLN: test_to_timedelta.py
mroeschke Dec 9, 2021
d312f37
Merge remote-tracking branch 'upstream/master' into ref/to_timedelta
mroeschke Dec 10, 2021
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95 changes: 43 additions & 52 deletions pandas/tests/tools/test_to_timedelta.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,52 +30,45 @@ def test_to_timedelta_readonly(self, readonly):
expected = to_timedelta([])
tm.assert_index_equal(result, expected)

def test_to_timedelta(self):

def test_to_timedelta_null(self):
result = to_timedelta(["", ""])
assert isna(result).all()

def test_to_timedelta_same_np_timedelta64(self):
# pass thru
result = to_timedelta(np.array([np.timedelta64(1, "s")]))
expected = pd.Index(np.array([np.timedelta64(1, "s")]))
tm.assert_index_equal(result, expected)

def test_to_timedelta_series(self):
# Series
expected = Series([timedelta(days=1), timedelta(days=1, seconds=1)])
result = to_timedelta(Series(["1d", "1days 00:00:01"]))
tm.assert_series_equal(result, expected)

def test_to_timedelta_units(self):
# with units
result = TimedeltaIndex(
[np.timedelta64(0, "ns"), np.timedelta64(10, "s").astype("m8[ns]")]
)
expected = to_timedelta([0, 10], unit="s")
tm.assert_index_equal(result, expected)

@pytest.mark.parametrize(
"dtype, unit",
[
["int64", "s"],
["int64", "m"],
["int64", "h"],
["timedelta64[s]", "s"],
["timedelta64[D]", "D"],
],
)
def test_to_timedelta_units_dtypes(self, dtype, unit):
# arrays of various dtypes
arr = np.array([1] * 5, dtype="int64")
result = to_timedelta(arr, unit="s")
expected = TimedeltaIndex([np.timedelta64(1, "s")] * 5)
tm.assert_index_equal(result, expected)

arr = np.array([1] * 5, dtype="int64")
result = to_timedelta(arr, unit="m")
expected = TimedeltaIndex([np.timedelta64(1, "m")] * 5)
tm.assert_index_equal(result, expected)

arr = np.array([1] * 5, dtype="int64")
result = to_timedelta(arr, unit="h")
expected = TimedeltaIndex([np.timedelta64(1, "h")] * 5)
tm.assert_index_equal(result, expected)

arr = np.array([1] * 5, dtype="timedelta64[s]")
result = to_timedelta(arr)
expected = TimedeltaIndex([np.timedelta64(1, "s")] * 5)
tm.assert_index_equal(result, expected)

arr = np.array([1] * 5, dtype="timedelta64[D]")
result = to_timedelta(arr)
expected = TimedeltaIndex([np.timedelta64(1, "D")] * 5)
arr = np.array([1] * 5, dtype=dtype)
result = to_timedelta(arr, unit=unit)
expected = TimedeltaIndex([np.timedelta64(1, unit)] * 5)
tm.assert_index_equal(result, expected)

def test_to_timedelta_oob_non_nano(self):
Expand All @@ -91,31 +84,30 @@ def test_to_timedelta_oob_non_nano(self):
with pytest.raises(OutOfBoundsTimedelta, match=msg):
TimedeltaArray._from_sequence(arr)

def test_to_timedelta_dataframe(self):
@pytest.mark.parametrize(
"arg", [np.arange(10).reshape(2, 5), pd.DataFrame(np.arange(10).reshape(2, 5))]
)
@pytest.mark.parametrize("errors", ["ignore", "raise", "coerce"])
def test_to_timedelta_dataframe(self, arg, errors):
# GH 11776
arr = np.arange(10).reshape(2, 5)
df = pd.DataFrame(np.arange(10).reshape(2, 5))
for arg in (arr, df):
with pytest.raises(TypeError, match="1-d array"):
to_timedelta(arg)
for errors in ["ignore", "raise", "coerce"]:
with pytest.raises(TypeError, match="1-d array"):
to_timedelta(arg, errors=errors)
with pytest.raises(TypeError, match="1-d array"):
to_timedelta(arg, errors=errors)

def test_to_timedelta_invalid(self):
def test_to_timedelta_invalid_errors(self):

# bad value for errors parameter
msg = "errors must be one of"
with pytest.raises(ValueError, match=msg):
to_timedelta(["foo"], errors="never")

@pytest.mark.parametrize("arg", [[1, 2], 1])
def test_to_timedelta_invalid_unit(self, arg):
# these will error
msg = "invalid unit abbreviation: foo"
with pytest.raises(ValueError, match=msg):
to_timedelta([1, 2], unit="foo")
with pytest.raises(ValueError, match=msg):
to_timedelta(1, unit="foo")
to_timedelta(arg, unit="foo")

def test_to_timedelta_time(self):
# time not supported ATM
msg = (
"Value must be Timedelta, string, integer, float, timedelta or convertible"
Expand All @@ -124,10 +116,12 @@ def test_to_timedelta_invalid(self):
to_timedelta(time(second=1))
assert to_timedelta(time(second=1), errors="coerce") is pd.NaT

def test_to_timedelta_bad_value(self):
msg = "Could not convert 'foo' to NumPy timedelta"
with pytest.raises(ValueError, match=msg):
to_timedelta(["foo", "bar"])

def test_to_timedelta_bad_value_coerce(self):
tm.assert_index_equal(
TimedeltaIndex([pd.NaT, pd.NaT]),
to_timedelta(["foo", "bar"], errors="coerce"),
Expand All @@ -138,6 +132,7 @@ def test_to_timedelta_invalid(self):
to_timedelta(["1 day", "bar", "1 min"], errors="coerce"),
)

def test_to_timedelta_invalid_errors_ignore(self):
# gh-13613: these should not error because errors='ignore'
invalid_data = "apple"
assert invalid_data == to_timedelta(invalid_data, errors="ignore")
Expand Down Expand Up @@ -213,11 +208,10 @@ def test_to_timedelta_on_missing_values(self):
actual = to_timedelta(ser)
tm.assert_series_equal(actual, expected)

actual = to_timedelta(np.nan)
assert actual.value == timedelta_NaT.astype("int64")

actual = to_timedelta(pd.NaT)
assert actual.value == timedelta_NaT.astype("int64")
@pytest.mark.parametrize("val", [np.nan, pd.NaT])
def test_to_timedelta_on_missing_values_scalar(self, val):
actual = to_timedelta(val)
assert actual.value == np.timedelta64("NaT").astype("int64")

def test_to_timedelta_float(self):
# https://github.com/pandas-dev/pandas/issues/25077
Expand All @@ -237,16 +231,13 @@ def test_to_timedelta_ignore_strings_unit(self):
result = to_timedelta(arr, unit="ns", errors="ignore")
tm.assert_numpy_array_equal(result, arr)

def test_to_timedelta_nullable_int64_dtype(self):
@pytest.mark.parametrize(
"expected_val, result_val", [[timedelta(days=2), 2], [None, None]]
)
def test_to_timedelta_nullable_int64_dtype(self, expected_val, result_val):
# GH 35574
expected = Series([timedelta(days=1), timedelta(days=2)])
result = to_timedelta(Series([1, 2], dtype="Int64"), unit="days")

tm.assert_series_equal(result, expected)

# IntegerArray Series with nulls
expected = Series([timedelta(days=1), None])
result = to_timedelta(Series([1, None], dtype="Int64"), unit="days")
expected = Series([timedelta(days=1), expected_val])
result = to_timedelta(Series([1, result_val], dtype="Int64"), unit="days")

tm.assert_series_equal(result, expected)

Expand Down