def test_input_int_in_np_get_row_empty():
obj = np.array([30, 53, 31, 47, 32])
df = DataFrame(obj, colindex=["AGE"], rowindex=["A", "B", "C", "D", "E"])
with pytest.raises(TypeError) as exc_info:
df.get_row()
exception_raised = exc_info.value
assert exception_raised
def test_input_int_in_list_get_row_imaginary():
obj = [30, 53, 31, 47, 32]
df = DataFrame(obj, colindex=["AGE"], rowindex=["A", "B", "C", "D", "E"])
with pytest.raises(Exception) as exc_info:
df.get_row(1 + 2j)
exception_raised = exc_info.value
assert exception_raised
def test_input_mixed_in_np_get_row_imaginary():
obj = np.array([30, 53.0, "31", True, 32])
df = DataFrame(obj, colindex=["AGE"], rowindex=["A", "B", "C", "D", "E"])
with pytest.raises(Exception) as exc_info:
df.get_row(1 + 2j)
exception_raised = exc_info.value
assert exception_raised
def test_input_int_in_dict_of_lists_get_row_imaginary():
obj = {"age": [30, 53, 31, 47, 32], "albums": [4, 10, 2, 5, 4]}
df = DataFrame(obj,
colindex=["AGE", "ALBUMS"],
rowindex=["A", "B", "C", "D", "E"])
with pytest.raises(Exception) as exc_info:
df.get_row(1 + 2j)
exception_raised = exc_info.value
assert exception_raised
def test_input_int_in_list_of_lists_get_row_empty():
obj = [[30, 53, 31, 47, 32], [4, 10, 2, 5, 4]]
df = DataFrame(obj,
colindex=["AGE", "ALBUMS"],
rowindex=["A", "B", "C", "D", "E"])
with pytest.raises(TypeError) as exc_info:
df.get_row()
exception_raised = exc_info.value
assert exception_raised
def test_input_int_in_dict_of_lists_get_row_wrong():
obj = {
"age": np.array([30, 53, 31, 47, 32]),
"albums": np.array([4, 10, 2, 5, 4]),
}
df = DataFrame(obj,
colindex=["AGE", "ALBUMS"],
rowindex=["A", "B", "C", "D", "E"])
with pytest.raises(Exception) as exc_info:
df.get_row(100)
exception_raised = exc_info.value
assert exception_raised
def test_getrow():
dictionary = {
"pet": np.array(["cat", "dog", "mouse"]),
"age": np.array([1, 2, 3]),
"weight": np.array([1.0, 2.0, 3.0]),
"sick": np.array([True, True, False]),
}
df = DataFrame(dictionary)
pet0 = "cat"
age0 = 1
weight0 = 1.0
sick0 = True
assert df.get_row([0])[0] == pet0
assert df.get_row([0])[1] == age0
assert df.get_row([0])[2] == weight0
assert df.get_row([0])[3] == sick0
def test_input_int_in_np_get_row_by_rowindex():
obj = np.array([30, 53, 31, 47, 32])
df = DataFrame(obj, colindex=["AGE"], rowindex=["A", "B", "C", "D", "E"])
expected_output = [53]
actual_output = df.get_row("B")
assert actual_output == expected_output
def test_input_int_in_list_get_row_by_index():
obj = [30, 53, 31, 47, 32]
df = DataFrame(obj, colindex=["AGE"], rowindex=["A", "B", "C", "D", "E"])
expected_output = [53]
actual_output = df.get_row(1)
assert actual_output == expected_output
def test_input_mixed_in_np_get_row_by_index():
obj = np.array([30, 53.0, "31", True, 32])
df = DataFrame(obj, colindex=["AGE"], rowindex=["A", "B", "C", "D", "E"])
expected_output = ["53.0"]
actual_output = df.get_row(1)
assert actual_output == expected_output
def test_input_mixed_in_list_of_lists_get_row_imaginary():
obj = [
[30.1, 53.1, 31.1, 47.1, 32.1],
[4, 10, 2, 5, 4],
["a", "b", "c", "d", "e"],
[True, False, True, True, False],
]
df = DataFrame(
obj,
colindex=["AGE", "ALBUMS", "C", "D"],
rowindex=["A", "B", "C", "D", "E"],
)
with pytest.raises(Exception) as exc_info:
df.get_row(1 + 2j)
exception_raised = exc_info.value
assert exception_raised
def test_input_int_in_list_of_lists_get_row_by_rowindex():
obj = [[30, 53, 31, 47, 32], [4, 10, 2, 5, 4]]
df = DataFrame(obj,
colindex=["AGE", "ALBUMS"],
rowindex=["A", "B", "C", "D", "E"])
expected_output = [53, 10]
actual_output = df.get_row("B")
assert actual_output == expected_output
def test_input_int_in_dict_of_lists_get_row_by_index():
obj = {"age": [30, 53, 31, 47, 32], "albums": [4, 10, 2, 5, 4]}
df = DataFrame(obj,
colindex=["AGE", "ALBUMS"],
rowindex=["A", "B", "C", "D", "E"])
expected_output = [53, 10]
actual_output = df.get_row(1)
assert actual_output == expected_output
def test_getrow():
dictionary = {
"pet": np.array(["cat", "dog", "mouse"]),
"age": np.array([1, 2, 3]),
"weight": np.array([1.0, 2.0, 3.0]),
"sick": np.array([True, True, False]),
}
row0 = ["cat", 1, 1.0, True]
row1 = ["dog", 2, 2.0, True]
df = DataFrame(dictionary)
assert df.get_row([0, 1])[0] == row0
assert df.get_row([0, 1])[1] == row1
def test_input_mixed_in_list_of_lists_get_row_by_index():
obj = [
[30.1, 53.1, 31.1, 47.1, 32.1],
[4, 10, 2, 5, 4],
["a", "b", "c", "d", "e"],
[True, False, True, True, False],
]
df = DataFrame(
obj,
colindex=["AGE", "ALBUMS", "C", "D"],
rowindex=["A", "B", "C", "D", "E"],
)
expected_output = [53.1, 10, "b", False]
actual_output = df.get_row(1)
assert actual_output == expected_output
def test_get_row_no_params():
# Test whether get_row function returns a ValueError
# when specifying no row
# Use pytest structure for testing the error-handling
with pytest.raises(ValueError) as ValError:
_data = np.array([
[1, 1.3254, False, "R1"],
[3, 4.123, True, "R 2"],
[3, 1.4, False, "R 3"],
[2, 14.0, False, "R 4"],
[12, 41.0, True, "R5"],
])
_columns = ["IntCol", "FloatCol", "BoolCol", "StringCol"]
_index = [0, 1, 2, 3, 4]
df = DataFrame(data=_data, columns=_columns)
output = df.get_row()
def test_getrow():
# Test whether get_row specifying the 4th row
# returns the 4th row
_data = np.array([
[1, 1.3254, False, "R1"],
[3, 4.123, True, "R 2"],
[3, 1.4, False, "R 3"],
[2, 14.0, False, "R 4"],
[12, 41.0, True, "R5"],
])
_columns = ["IntCol", "FloatCol", "BoolCol", "StringCol"]
df = DataFrame(data=_data, columns=_columns)
row = 3
expected_output = [2, 14.0, False, "R 4"]
output = df.get_row(row)
# Test if created object equals the desired object
assert np.array_equal(output, expected_output)
def test_get_negative_row():
# Tested behaviour: Return row counting from the end
# when specifying a negative row key.
_data = np.array([
[1, 1.3254, False, "R1"],
[3, 4.123, True, "R 2"],
[3, 1.4, False, "R 3"],
[2, 14.0, False, "R 4"],
[12, 41.0, True, "R5"],
])
_columns = ["IntCol", "FloatCol", "BoolCol", "StringCol"]
_index = [0, 1, 2, 3, 4]
df = DataFrame(data=_data, columns=_columns)
row = -1
expected_output = [12, 41.0, True, "R5"]
output = df.get_row(row)
# Test if created object equals the desired object
assert np.array_equal(output, expected_output)
def test_get_row_string_rowkey():
# Tests whether get_row function raises a TypeError
# when specifying a string as row key.
# Use pytest structure for testing the error-handling
with pytest.raises(TypeError) as TypError:
_data = np.array([
[1, 1.3254, False, "R1"],
[3, 4.123, True, "R 2"],
[3, 1.4, False, "R 3"],
[2, 14.0, False, "R 4"],
[12, 41.0, True, "R5"],
])
_columns = ["IntCol", "FloatCol", "BoolCol", "StringCol"]
_index = [0, 1, 2, 3, 4]
df = DataFrame(data=_data, columns=_columns)
# Specify string as row index
row = "a"
output = df.get_row(row)
def test_get_row_errors():
with pytest.raises(IndexError):
myDF = DataFrame(npDict1)
x = myDF.get_row(5)
def test_get_row(dictionary, arg, expected):
myDF = DataFrame(dictionary)
assert myDF.get_row(arg) == expected
