def assert_series_equal(cls, left, right, *args, **kwargs):
if left.dtype.name == "json":
assert left.dtype == right.dtype
left = pd.Series(JSONArray(left.values.astype(object)),
index=left.index,
name=left.name)
right = pd.Series(
JSONArray(right.values.astype(object)),
index=right.index,
name=right.name,
)
tm.assert_series_equal(left, right, *args, **kwargs)
def data_for_grouping():
return JSONArray([
{
"b": 1
},
{
"b": 1
},
{},
{},
{
"a": 0,
"c": 2
},
{
"a": 0,
"c": 2
},
{
"b": 1
},
{
"c": 2
},
])
def test_custom_asserts(self):
# This would always trigger the KeyError from trying to put
# an array of equal-length UserDicts inside an ndarray.
data = JSONArray([
collections.UserDict({"a": 1}),
collections.UserDict({"b": 2}),
collections.UserDict({"c": 3}),
])
a = pd.Series(data)
self.assert_series_equal(a, a)
self.assert_frame_equal(a.to_frame(), a.to_frame())
b = pd.Series(data.take([0, 0, 1]))
msg = r"ExtensionArray are different"
with pytest.raises(AssertionError, match=msg):
self.assert_series_equal(a, b)
with pytest.raises(AssertionError, match=msg):
self.assert_frame_equal(a.to_frame(), b.to_frame())
def data():
"""Length-100 PeriodArray for semantics test."""
data = make_data()
# Why the while loop? NumPy is unable to construct an ndarray from
# equal-length ndarrays. Many of our operations involve coercing the
# EA to an ndarray of objects. To avoid random test failures, we ensure
# that our data is coercible to an ndarray. Several tests deal with only
# the first two elements, so that's what we'll check.
while len(data[0]) == len(data[1]):
data = make_data()
return JSONArray(data)
def data_missing_for_sorting():
return JSONArray([{"b": 1}, {}, {"a": 4}])
def data_for_sorting():
return JSONArray([{"b": 1}, {"c": 4}, {"a": 2, "c": 3}])
def data_missing():
"""Length 2 array with [NA, Valid]"""
return JSONArray([{}, {"a": 10}])
