def test_setattr_new(self):
int_missing_data = [[1, 0, 0], [0, 2, 3], [0, 3, 4], [1, 2, 3]]
columns = ["col1", "col2", "col3"]
data = pd.DataFrame(int_missing_data, columns=columns)
base = MethodBase(
x_train=data,
x_test=None,
split=True,
target_field="",
target_mapping=None,
report_name="test",
test_split_percentage=0.5,
)
base.col4 = 4
self.assertIsNotNone(base.col4)
def test_setter(self):
data = [[1, 0, 0], [0, 2, 3], [0, 3, 4], [1, 2, 3]]
int_missing_data_rep = [[1, 0, 0], [0, 2, 3], [0, 3, 4], [1, 2, 3]]
base = MethodBase(
x_train=data,
x_test=None,
split=False,
target_field="",
target_mapping=None,
report_name="test",
test_split_percentage=0.5,
)
base.x_train = int_missing_data_rep
self.assertEqual(base.x_train, int_missing_data_rep)
def test_write_traindata_tocsv(self):
int_missing_data = [[1, 0, 0], [0, 2, 3], [0, 3, 4], [1, 2, 3]]
columns = ["col1", "col2", "col3"]
data = pd.DataFrame(int_missing_data, columns=columns)
base = MethodBase(
x_train=data,
x_test=None,
split=True,
target_field="",
report_name="test",
target_mapping=None,
test_split_percentage=0.5,
)
base.to_csv("titanic123")
os.remove("titanic123_train.csv")
os.remove("titanic123_test.csv")
self.assertTrue(True)
def test_where(self):
data = [[1, 0, 0], [0, 2, 3], [0, 3, 4], [1, 2, 3]]
columns = ["col1", "col2", "col3"]
data = pd.DataFrame(data, columns=columns)
base = MethodBase(
x_train=data,
x_test=None,
split=False,
target_field="",
report_name="test",
target_mapping=None,
test_split_percentage=0.5,
)
subset = base.where(col1=0, col2=2, col3=[3, 4])
validate = subset.values.tolist()
self.assertListEqual(validate, [[0, 2, 3]])
def test_groupbyanalysis(self):
data = pd.DataFrame({
"A": [1, 1, 2, 2],
"B": [1, 2, 3, 4],
"C": np.random.randn(4),
"D": ["A", "A", "B", "B"],
})
base = MethodBase(
x_train=data,
x_test=None,
split=False,
target_field="",
target_mapping=None,
report_name="test",
test_split_percentage=0.5,
)
base.groupby_analysis(["A"])
self.assertTrue(True)
def test_ytest_dne(self):
data = [[1, 0, 0], [0, 2, 3], [0, 3, 4], [1, 2, 3]]
columns = ["col1", "col2", "col3"]
data = pd.DataFrame(data, columns=columns)
base = MethodBase(
x_train=data,
x_test=None,
split=True,
target_field="",
report_name=None,
target_mapping=None,
test_split_percentage=0.5,
)
base.y_test = [1, 1]
validate = base.y_test.tolist() == [
1, 1
] and base._data_properties.x_test["label"].tolist() == [1, 1]
self.assertTrue(validate)
def test_setattr_old(self):
int_missing_data = [[1, 0, 0], [0, 2, 3], [0, 3, 4], [1, 2, 3]]
columns = ["col1", "col2", "col3"]
data = pd.DataFrame(int_missing_data, columns=columns)
base = MethodBase(
x_train=data,
x_test=None,
split=True,
target_field="",
report_name="test",
target_mapping=None,
test_split_percentage=0.5,
)
base._data_properties.target_field = "col3"
self.assertEqual("col3", base.target_field)
def test_ytest_split(self):
data = [[1, 0, 0], [0, 2, 3], [0, 3, 4], [1, 2, 3]]
columns = ["col1", "col2", "col3"]
data = pd.DataFrame(data, columns=columns)
base = MethodBase(
x_train=data,
x_test=None,
split=True,
target_field="col3",
report_name=None,
target_mapping=None,
test_split_percentage=0.5,
)
validate = len(base.y_test) == 2
self.assertTrue(validate)
def test_setitem_tupleeven(self):
int_missing_data = [[1, 0, 0], [0, 2, 3], [0, 3, 4], [1, 2, 3]]
columns = ["col1", "col2", "col3"]
data = pd.DataFrame(int_missing_data, columns=columns)
base = MethodBase(
x_train=data,
x_test=None,
split=True,
target_field="",
target_mapping=None,
report_name=None,
test_split_percentage=0.5,
)
base["col4"] = ([5, 5], [2, 2])
validate = any(base.x_train["col4"].isnull()) and any(
base.x_test["col4"].isnull())
self.assertFalse(validate)
