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Added test to reject float16; fixed typos

This commit is contained in:
Christopher C. Aycock 2016-12-16 10:39:28 -05:00
parent 1f208a8179
commit ffcf0c23fe
2 changed files with 29 additions and 21 deletions
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4
pandas/tools/merge.py
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@ -1013,7 +1013,7 @@ _type_casters = {
'object': _ensure_object,
}
_cyton_types = {
_cython_types = {
'uint8': 'uint8_t',
'uint32': 'uint32_t',
'uint16': 'uint16_t',
@ -1031,7 +1031,7 @@ _cyton_types = {
def _get_cython_type(dtype):
""" Given a dtype, return a C name like 'int64_t' or 'double' """
type_name = _get_dtype(dtype).name
ctype = _cyton_types.get(type_name, 'object')
ctype = _cython_types.get(type_name, 'object')
if ctype == 'error':
raise MergeError('unsupported type: ' + type_name)
return ctype

46
pandas/tools/tests/test_merge_asof.py
View File

@ -657,7 +657,7 @@ class TestAsOfMerge(tm.TestCase):
# GH13936
for dtype in [np.uint8, np.uint16, np.uint32, np.uint64,
np.int8, np.int16, np.int32, np.int64,
np.float32, np.float64]:
np.float16, np.float32, np.float64]:
df1 = pd.DataFrame({
'value': [5, 2, 25, 100, 78, 120, 79],
'symbol': list("ABCDEFG")},
@ -672,22 +672,26 @@ class TestAsOfMerge(tm.TestCase):
df1 = df1.sort_values('value').reset_index(drop=True)
result = pd.merge_asof(df1, df2, on='value')
if dtype == np.float16:
with self.assertRaises(MergeError):
pd.merge_asof(df1, df2, on='value')
else:
result = pd.merge_asof(df1, df2, on='value')
expected = pd.DataFrame({
'symbol': list("BACEGDF"),
'value': [2, 5, 25, 78, 79, 100, 120],
'result': list('xxxxxyz')},
columns=['symbol', 'value', 'result'])
expected.value = dtype(expected.value)
expected = pd.DataFrame({
'symbol': list("BACEGDF"),
'value': [2, 5, 25, 78, 79, 100, 120],
'result': list('xxxxxyz')},
columns=['symbol', 'value', 'result'])
expected.value = dtype(expected.value)
assert_frame_equal(result, expected)
assert_frame_equal(result, expected)
def test_on_specialized_type_by_int(self):
# GH13936
for dtype in [np.uint8, np.uint16, np.uint32, np.uint64,
np.int8, np.int16, np.int32, np.int64,
np.float32, np.float64]:
np.float16, np.float32, np.float64]:
df1 = pd.DataFrame({
'value': [5, 2, 25, 100, 78, 120, 79],
'key': [1, 2, 3, 2, 3, 1, 2],
@ -704,17 +708,21 @@ class TestAsOfMerge(tm.TestCase):
df1 = df1.sort_values('value').reset_index(drop=True)
result = pd.merge_asof(df1, df2, on='value', by='key')
if dtype == np.float16:
with self.assertRaises(MergeError):
pd.merge_asof(df1, df2, on='value', by='key')
else:
result = pd.merge_asof(df1, df2, on='value', by='key')
expected = pd.DataFrame({
'symbol': list("BACEGDF"),
'key': [2, 1, 3, 3, 2, 2, 1],
'value': [2, 5, 25, 78, 79, 100, 120],
'result': [np.nan, 'x', np.nan, np.nan, np.nan, 'y', 'x']},
columns=['symbol', 'key', 'value', 'result'])
expected.value = dtype(expected.value)
expected = pd.DataFrame({
'symbol': list("BACEGDF"),
'key': [2, 1, 3, 3, 2, 2, 1],
'value': [2, 5, 25, 78, 79, 100, 120],
'result': [np.nan, 'x', np.nan, np.nan, np.nan, 'y', 'x']},
columns=['symbol', 'key', 'value', 'result'])
expected.value = dtype(expected.value)
assert_frame_equal(result, expected)
assert_frame_equal(result, expected)
def test_on_float_by_int(self):
# type specialize both "by" and "on" parameters