def test_TableFormulaCore_Excel(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
fold = os.path.split(__file__)[0]
assert TableFormula.delta is not None
file = os.path.join(fold, "data", "BNP.PA.txt")
table = TableFormula(file, sep=",")
table.sort(lambda v: v["Date"])
assert len(table) > 0
tempfold = os.path.join(fold, "temp_store")
if not os.path.exists(tempfold):
os.mkdir(tempfold)
tempexc = os.path.join(tempfold, "temp_excel_table.xls")
if os.path.exists(tempexc):
os.remove(tempexc)
assert not os.path.exists(tempexc)
table.save_as_excel(tempexc)
assert os.path.exists(tempexc)
tempexc = os.path.join(tempfold, "temp_excel_table.xlsx")
if os.path.exists(tempexc):
os.remove(tempexc)
assert not os.path.exists(tempexc)
table.save_as_excel(tempexc)
assert os.path.exists(tempexc)
def test_TableFormulaCore_Excel(self):
fLOG(__file__, self._testMethodName,
OutputPrint=__name__ == "__main__")
fold = os.path.split(__file__)[0]
assert TableFormula.delta is not None
file = os.path.join(fold, "data", "BNP.PA.txt")
table = TableFormula(file, sep=",")
table.sort(lambda v: v["Date"])
assert len(table) > 0
tempfold = os.path.join(fold, "temp_store")
if not os.path.exists(tempfold):
os.mkdir(tempfold)
tempexc = os.path.join(tempfold, "temp_excel_table.xls")
if os.path.exists(tempexc):
os.remove(tempexc)
assert not os.path.exists(tempexc)
table.save_as_excel(tempexc)
assert os.path.exists(tempexc)
tempexc = os.path.join(tempfold, "temp_excel_table.xlsx")
if os.path.exists(tempexc):
os.remove(tempexc)
assert not os.path.exists(tempexc)
table.save_as_excel(tempexc)
assert os.path.exists(tempexc)
def test_multiply_implicit(self):
fLOG(__file__, self._testMethodName, OutputPrint=__name__ == "__main__")
text = """city\tdate
A\tjan
A\tfeb
B\tfeb""".replace(" ", "")
table = TableFormula(text)
assert len(table) == 3
mul = table.multiply_column_by_row_instance(
lambda v: v["date"],
lambda v: v["city"])
exp = """KEY\tA|city\tA|date\tB|city\tB|date
feb\tA\tfeb\tB\tfeb
jan\tA\tjan\tNone\tNone""".replace(" ", "")
exp = TableFormula(exp)
exp.sort(lambda v: v["KEY"])
mul.sort(lambda v: v["KEY"])
delta = mul.delta(exp)
if len(delta) > 0:
for _ in delta:
fLOG(_)
assert False
def test_multiply_implicit(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
text = """city\tdate
A\tjan
A\tfeb
B\tfeb""".replace(" ", "")
table = TableFormula(text)
assert len(table) == 3
mul = table.multiply_column_by_row_instance(lambda v: v["date"],
lambda v: v["city"])
exp = """KEY\tA|city\tA|date\tB|city\tB|date
feb\tA\tfeb\tB\tfeb
jan\tA\tjan\tNone\tNone""".replace(" ", "")
exp = TableFormula(exp)
exp.sort(lambda v: v["KEY"])
mul.sort(lambda v: v["KEY"])
delta = mul.delta(exp)
if len(delta) > 0:
for _ in delta:
fLOG(_)
assert False
def test_TableFormulaCore(self):
fLOG(__file__, self._testMethodName, OutputPrint=__name__ == "__main__")
fold = os.path.split(__file__)[0]
assert TableFormula.delta is not None
file = os.path.join(fold, "data", "BNP.PA.txt")
table = TableFormula(file, sep=",")
table.sort(lambda v: v["Date"])
assert len(table) > 0
table = TableFormula("name d_a d_b d_c#A 1 2 3#A 1.1 2.1 3.1#B 3 4 5"
.replace(" ", "\t").replace("#", "\n"))
assert "d_a\td_b\td_c" in str(table)
dist = table.get_distinct_values("name")
assert len(dist) > 0
table.add_column("has_A", lambda v: 1. if "A" in v["name"] else 0.)
assert len(table) > 0
x = 1. / 3
table.add_column_smooth("has_A_smooth", lambda v: v[
"has_A"], [-1, 0, 1], [x, x, x])
assert len(table) > 0
fil = table.filter(lambda v: v["d_b"] == 2)
assert len(table) > 0
rnd = table.random(5)
assert len(rnd) > 0
rnd = table.random(1, True)
assert len(rnd) > 0
fil = table.filter_quantile(lambda v: v["d_b"], 0, 0.4)
assert len(fil) > 0
total = table.aggregate(lambda v: v["d_c"])
assert total > 0
table.sort(lambda v: v["d_b"] + v["d_c"])
assert len(table) > 0
union = table.union(table)
assert len(union) > len(table)
group = table.groupby(lambda v: v["name"],
[lambda v: v["d_a"],
lambda v: v["d_b"]],
["name", "sum_d_a", "sum_d_b"])
assert len(group) > 0
groupmax = table.groupby(lambda v: v["name"],
[lambda v: v["d_a"],
lambda v: v["d_b"]],
["name", "max_d_a", "max_d_b"],
[max, max])
assert len(groupmax) > 0
group = table.groupby(lambda v: v["name"],
[lambda v: v["d_a"]],
["name", "weight", "sum_d_a"],
[lambda vec, w: sum(vec) / w],
lambda v: v["d_b"])
innerjoin = table.innerjoin(group, lambda v: v["name"],
lambda v: v["name"], "group")
assert len(innerjoin) > 0
ext = table.extract_columns(["name", "d_a"])
assert len(ext) > 0
ext = table.remove_columns(["d_a"])
assert len(ext) > 0
d = table.todict(lambda v: v["name"], lambda v: v["d_b"], True)
assert len(d) > 0
d = table.select(lambda v: (v["name"], v["d_b"]))
assert len(list(d)) > 0
table.create_index(lambda v: (v["name"], v["d_a"]))
row = table.get(('A', 1.1))
assert row
value = table.get(('A', 1.1), 2)
assert value
table = TableFormula("name d_a d_b d_c#A 1 2 3#A 1.1 2.1 3.1#B 3 4 5"
.replace(" ", "\t").replace("#", "\n"))
table.add_column("key_add", lambda v: "unique")
mul = table.multiply_column_by_row_instance(
lambda v: v["key_add"],
lambda v: v["name"])
assert len(mul) > 0
table = TableFormula("key_name sum_a len_b avg_c#A 1 2 3#A 1.1 2.1 3.1#B 3 4 5"
.replace(" ", "\t").replace("#", "\n"))
gr = table.groupby_implicit(lambda v: v["key_name"])
assert len(gr) > 0
def test_TableFormulaCore(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
fold = os.path.split(__file__)[0]
assert TableFormula.delta is not None
file = os.path.join(fold, "data", "BNP.PA.txt")
table = TableFormula(file, sep=",")
table.sort(lambda v: v["Date"])
assert len(table) > 0
table = TableFormula(
"name d_a d_b d_c#A 1 2 3#A 1.1 2.1 3.1#B 3 4 5".replace(
" ", "\t").replace("#", "\n"))
assert "d_a\td_b\td_c" in str(table)
dist = table.get_distinct_values("name")
assert len(dist) > 0
table.add_column("has_A", lambda v: 1. if "A" in v["name"] else 0.)
assert len(table) > 0
x = 1. / 3
table.add_column_smooth("has_A_smooth", lambda v: v["has_A"],
[-1, 0, 1], [x, x, x])
assert len(table) > 0
fil = table.filter(lambda v: v["d_b"] == 2)
assert len(table) > 0
rnd = table.random(5)
assert len(rnd) > 0
rnd = table.random(1, True)
assert len(rnd) > 0
fil = table.filter_quantile(lambda v: v["d_b"], 0, 0.4)
assert len(fil) > 0
total = table.aggregate(lambda v: v["d_c"])
assert total > 0
table.sort(lambda v: v["d_b"] + v["d_c"])
assert len(table) > 0
union = table.union(table)
assert len(union) > len(table)
group = table.groupby(lambda v: v["name"],
[lambda v: v["d_a"], lambda v: v["d_b"]],
["name", "sum_d_a", "sum_d_b"])
assert len(group) > 0
groupmax = table.groupby(lambda v: v["name"],
[lambda v: v["d_a"], lambda v: v["d_b"]],
["name", "max_d_a", "max_d_b"], [max, max])
assert len(groupmax) > 0
group = table.groupby(lambda v: v["name"], [lambda v: v["d_a"]],
["name", "weight", "sum_d_a"],
[lambda vec, w: sum(vec) / w],
lambda v: v["d_b"])
innerjoin = table.innerjoin(group, lambda v: v["name"],
lambda v: v["name"], "group")
assert len(innerjoin) > 0
ext = table.extract_columns(["name", "d_a"])
assert len(ext) > 0
ext = table.remove_columns(["d_a"])
assert len(ext) > 0
d = table.todict(lambda v: v["name"], lambda v: v["d_b"], True)
assert len(d) > 0
d = table.select(lambda v: (v["name"], v["d_b"]))
assert len(list(d)) > 0
table.create_index(lambda v: (v["name"], v["d_a"]))
row = table.get(('A', 1.1))
assert row
value = table.get(('A', 1.1), 2)
assert value
table = TableFormula(
"name d_a d_b d_c#A 1 2 3#A 1.1 2.1 3.1#B 3 4 5".replace(
" ", "\t").replace("#", "\n"))
table.add_column("key_add", lambda v: "unique")
mul = table.multiply_column_by_row_instance(lambda v: v["key_add"],
lambda v: v["name"])
assert len(mul) > 0
table = TableFormula(
"key_name sum_a len_b avg_c#A 1 2 3#A 1.1 2.1 3.1#B 3 4 5".replace(
" ", "\t").replace("#", "\n"))
gr = table.groupby_implicit(lambda v: v["key_name"])
assert len(gr) > 0
