def test_float_nulls(self):
num_values = 100
path = random_path()
self.test_files.append(path)
writer = FeatherWriter(path)
null_mask = np.random.randint(0, 10, size=num_values) < 3
dtypes = ['f4', 'f8']
expected_cols = []
for name in dtypes:
values = np.random.randn(num_values).astype(name)
writer.write_array(name, values, null_mask)
values[null_mask] = np.nan
expected_cols.append(values)
writer.close()
ex_frame = pd.DataFrame(dict(zip(dtypes, expected_cols)),
columns=dtypes)
result = feather.read_dataframe(path)
assert_frame_equal(result, ex_frame)
def test_integer_with_nulls(self):
# pandas requires upcast to float dtype
path = random_path()
self.test_files.append(path)
int_dtypes = ['i1', 'i2', 'i4', 'i8', 'u1', 'u2', 'u4', 'u8']
num_values = 100
writer = FeatherWriter(path)
null_mask = np.random.randint(0, 10, size=num_values) < 3
expected_cols = []
for name in int_dtypes:
values = np.random.randint(0, 100, size=num_values)
writer.write_array(name, values, null_mask)
expected = values.astype('f8')
expected[null_mask] = np.nan
expected_cols.append(expected)
ex_frame = pd.DataFrame(dict(zip(int_dtypes, expected_cols)),
columns=int_dtypes)
writer.close()
result = feather.read_dataframe(path)
assert_frame_equal(result, ex_frame)
def test_float_nulls(self):
num_values = 100
path = random_path()
self.test_files.append(path)
writer = FeatherWriter(path)
null_mask = np.random.randint(0, 10, size=num_values) < 3
dtypes = ['f4', 'f8']
expected_cols = []
for name in dtypes:
values = np.random.randn(num_values).astype(name)
writer.write_array(name, values, null_mask)
values[null_mask] = np.nan
expected_cols.append(values)
writer.close()
ex_frame = pd.DataFrame(dict(zip(dtypes, expected_cols)),
columns=dtypes)
result = feather.read_dataframe(path)
assert_frame_equal(result, ex_frame)
def test_integer_with_nulls(self):
# pandas requires upcast to float dtype
path = random_path()
self.test_files.append(path)
int_dtypes = ['i1', 'i2', 'i4', 'i8', 'u1', 'u2', 'u4', 'u8']
num_values = 100
writer = FeatherWriter(path)
null_mask = np.random.randint(0, 10, size=num_values) < 3
expected_cols = []
for name in int_dtypes:
values = np.random.randint(0, 100, size=num_values)
writer.write_array(name, values, null_mask)
expected = values.astype('f8')
expected[null_mask] = np.nan
expected_cols.append(expected)
ex_frame = pd.DataFrame(dict(zip(int_dtypes, expected_cols)),
columns=int_dtypes)
writer.close()
result = feather.read_dataframe(path)
assert_frame_equal(result, ex_frame)
def test_boolean_nulls(self):
# pandas requires upcast to object dtype
path = random_path()
self.test_files.append(path)
num_values = 100
np.random.seed(0)
writer = FeatherWriter(path)
mask = np.random.randint(0, 10, size=num_values) < 3
values = np.random.randint(0, 10, size=num_values) < 5
writer.write_array('bools', values, mask)
expected = values.astype(object)
expected[mask] = None
writer.close()
ex_frame = pd.DataFrame({'bools': expected})
result = feather.read_dataframe(path)
assert_frame_equal(result, ex_frame)
def test_boolean_nulls(self):
# pandas requires upcast to object dtype
path = random_path()
self.test_files.append(path)
num_values = 100
np.random.seed(0)
writer = FeatherWriter(path)
mask = np.random.randint(0, 10, size=num_values) < 3
values = np.random.randint(0, 10, size=num_values) < 5
writer.write_array('bools', values, mask)
expected = values.astype(object)
expected[mask] = None
writer.close()
ex_frame = pd.DataFrame({'bools': expected})
result = feather.read_dataframe(path)
assert_frame_equal(result, ex_frame)