def test_pandas_series_loading(self):
"""Pandas Series objects are correctly loaded"""
# Test valid series types
name = ['_x', ' name']
length = [0, 1, 2]
index_key = [None, 'ix', 1]
index_types = ['int', 'char', 'datetime', 'Timestamp']
value_key = [None, 'x', 1]
value_types = ['int', 'char', 'datetime', 'Timestamp', 'float',
'numpy float', 'numpy int']
series_info = product(name, length, index_key, index_types,
value_key, value_types)
for n, l, ikey, itype, vkey, vtype in series_info:
index = sequences[itype](l)
series = pd.Series(sequences[vtype](l), index=index, name=n,)
vkey = vkey or series.name
expected = [{'idx': Data.serialize(i), 'col': vkey,
'val': Data.serialize(v)}
for i, v in zip(index, series)]
data = Data.from_pandas(series, name=n, series_key=vkey)
nt.assert_list_equal(expected, data.values)
nt.assert_equal(n, data.name)
data.to_json()
# Missing a name
series = pd.Series(np.random.randn(10))
data = Data.from_pandas(series)
nt.assert_equal(data.name, 'table')
def test_serialize(self):
"""Objects are serialized to JSON-compatible objects"""
def epoch(obj):
"""Convert to JS Epoch time"""
return int(time.mktime(obj.timetuple())) * 1000
types = [('test', str, 'test'),
(pd.Timestamp('2013-06-08'), int,
epoch(pd.Timestamp('2013-06-08'))),
(datetime.utcnow(), int, epoch(datetime.utcnow())),
(1, int, 1), (1.0, float, 1.0), (np.float32(1), float, 1.0),
(np.int32(1), int, 1), (np.float64(1), float, 1.0),
(np.int64(1), int, 1)]
for puts, pytype, gets in types:
nt.assert_equal(Data.serialize(puts), gets)
class BadType(object):
"""Bad object for type warning"""
test_obj = BadType()
with nt.assert_raises(LoadError) as err:
Data.serialize(test_obj)
nt.assert_equals(err.exception.args[0],
'cannot serialize index of type BadType')
def test_serialize(self):
"""Objects are serialized to JSON-compatible objects"""
def epoch(obj):
"""Convert to JS Epoch time"""
return int(time.mktime(obj.timetuple())) * 1000
types = [('test', str, 'test'),
(pd.Timestamp('2013-06-08'), int,
epoch(pd.Timestamp('2013-06-08'))),
(datetime.utcnow(), int, epoch(datetime.utcnow())),
(1, int, 1),
(1.0, float, 1.0),
(np.float32(1), float, 1.0),
(np.int32(1), int, 1),
(np.float64(1), float, 1.0),
(np.int64(1), int, 1)]
for puts, pytype, gets in types:
nt.assert_equal(Data.serialize(puts), gets)
class BadType(object):
"""Bad object for type warning"""
test_obj = BadType()
with nt.assert_raises(LoadError) as err:
Data.serialize(test_obj)
nt.assert_equals(err.exception.message,
'cannot serialize index of type BadType')
def test_pandas_series_loading(self):
"""Pandas Series objects are correctly loaded"""
# Test valid series types
name = ['_x', ' name']
length = [0, 1, 2]
index_key = [None, 'ix', 1]
index_types = ['int', 'char', 'datetime', 'Timestamp']
value_key = [None, 'x', 1]
value_types = ['int', 'char', 'datetime', 'Timestamp', 'float',
'numpy float', 'numpy int']
series_info = product(name, length, index_key, index_types,
value_key, value_types)
for n, l, ikey, itype, vkey, vtype in series_info:
index = sequences[itype](l)
series = pd.Series(sequences[vtype](l), index=index, name=n,)
vkey = series.name or vkey
expected = [{'idx': Data.serialize(i), 'col': vkey,
'val': Data.serialize(v)}
for i, v in zip(index, series)]
data = Data.from_pandas(series, name=n, series_key=vkey)
nt.assert_list_equal(expected, data.values)
nt.assert_equal(n, data.name)
data.to_json()
# Missing a name
series = pd.Series(np.random.randn(10))
data = Data.from_pandas(series)
nt.assert_equal(data.name, 'table')
