def test_index_series_as_assoc(self):
series_mixed = pandas.Series([1, 2, 3], index=[-1, "a", 1])
self.export_compare(
series_mixed,
wl=b'<|-1 -> 1, "a" -> 2, 1 -> 3|>',
wxf=
b"8:f\x03s\x0bAssociationf\x02s\x04RuleC\xffC\x01f\x02s\x04RuleS\x01aC\x02f\x02s\x04RuleC\x01C\x03",
)
def test_index_series_as_dataset(self):
series_mixed = pandas.Series([1, 2, 3], index=[-1, 'a', 1])
self.export_compare(
series_mixed,
wl=b'Dataset[<|-1 -> 1, "a" -> 2, 1 -> 3|>]',
wxf=
b'8:f\x01s\x07Datasetf\x03s\x0bAssociationf\x02s\x04RuleC\xffC\x01f\x02s\x04RuleS\x01aC\x02f\x02s\x04RuleC\x01C\x03',
pandas_series_head='dataset')
def test_index_series_as_list(self):
series_mixed = pandas.Series([1, 2, 3], index=[-1, 'a', 1])
self.export_compare(
series_mixed,
wl=b'{-1 -> 1, "a" -> 2, 1 -> 3}',
wxf=
b'8:f\x03s\x04Listf\x02s\x04RuleC\xffC\x01f\x02s\x04RuleS\x01aC\x02f\x02s\x04RuleC\x01C\x03',
pandas_series_head='list')
def multiindex_series(self):
mi = pandas.MultiIndex(
levels=[["a", "b"], ["x", "y"], [0]],
labels=[
[1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 1, 1],
[0, -1, 0, -1, 0, -1, 0, -1],
],
)
return pandas.Series(numpy.arange(8), index=mi)
def test_index_nan_series_as_assoc(self):
arr, index = self.create_numpy_data_nan()
series_mixed = pandas.Series(arr, index=index)
self.export_compare(
series_mixed,
wl=
b"<|0 -> 0., 1 -> Indeterminate, 2 -> 2., 3 -> Indeterminate, 4 -> 4.|>",
wxf=
b"8:f\x05s\x0bAssociationf\x02s\x04RuleC\x00r\x00\x00\x00\x00\x00\x00\x00\x00f\x02s\x04RuleC\x01s\rIndeterminatef\x02s\x04RuleC\x02r\x00\x00\x00\x00\x00\x00\x00@f\x02s\x04RuleC\x03s\rIndeterminatef\x02s\x04RuleC\x04r\x00\x00\x00\x00\x00\x00\x10@",
)
def test_index_series_as_dataset(self):
arr, index = self.create_numpy_data_nan()
series_mixed = pandas.Series(arr, index=index)
self.export_compare(
series_mixed,
wl=
b'Dataset[<|0 -> 0., 1 -> Indeterminate, 2 -> 2., 3 -> Indeterminate, 4 -> 4.|>]',
wxf=
b'8:f\x01s\x07Datasetf\x05s\x0bAssociationf\x02s\x04RuleC\x00r\x00\x00\x00\x00\x00\x00\x00\x00f\x02s\x04RuleC\x01s\rIndeterminatef\x02s\x04RuleC\x02r\x00\x00\x00\x00\x00\x00\x00@f\x02s\x04RuleC\x03s\rIndeterminatef\x02s\x04RuleC\x04r\x00\x00\x00\x00\x00\x00\x10@',
pandas_series_head='dataset')
def test_index_series_as_list(self):
arr, index = self.create_numpy_data_nan()
series_mixed = pandas.Series(arr, index=index)
self.export_compare(
series_mixed,
wl=
b'{0 -> 0., 1 -> Indeterminate, 2 -> 2., 3 -> Indeterminate, 4 -> 4.}',
wxf=
b'8:f\x05s\x04Listf\x02s\x04RuleC\x00r\x00\x00\x00\x00\x00\x00\x00\x00f\x02s\x04RuleC\x01s\rIndeterminatef\x02s\x04RuleC\x02r\x00\x00\x00\x00\x00\x00\x00@f\x02s\x04RuleC\x03s\rIndeterminatef\x02s\x04RuleC\x04r\x00\x00\x00\x00\x00\x00\x10@',
pandas_series_head='list')
def test_empty_series(self):
o = pandas.Series([])
self.export_compare(o,
wl=b'<||>',
wxf=b'8:f\x00s\x0bAssociation',
pandas_series_head='association')
self.export_compare(o,
wl=b'{}',
wxf=b'8:f\x00s\x04List',
pandas_series_head='list')
self.export_compare(o,
wl=b'Dataset[<||>]',
wxf=b'8:f\x01s\x07Datasetf\x00s\x0bAssociation',
pandas_series_head='dataset')
def test_empty_series(self):
o = pandas.Series([])
self.export_compare(o,
wl=b"<||>",
wxf=b"8:f\x00s\x0bAssociation",
pandas_series_head="association")
self.export_compare(o,
wl=b"{}",
wxf=b"8:f\x00s\x04List",
pandas_series_head="list")
self.export_compare(
o,
wl=b"Dataset[<||>]",
wxf=b"8:f\x01s\x07Datasetf\x00s\x0bAssociation",
pandas_series_head="dataset",
)
def sparse_series_dict_indexed(self):
constructor_dict = {1: 1.0}
index = [0, 1, 2]
# Series with index passed in
series = pandas.Series(constructor_dict)
return pandas.SparseSeries(series, index=index)
def sparse_series_dict(self):
d = OrderedDict()
d["b"] = 1
d["a"] = 0
d["c"] = 2
return pandas.Series(d, dtype="Sparse[int]")
def multiindex_series(self):
mi = pandas.MultiIndex(levels=[['a', 'b'], ['x', 'y'], [0]],
labels=[[1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 1, 1],
[0, -1, 0, -1, 0, -1, 0, -1]])
return pandas.Series(numpy.arange(8), index=mi)
