def test_get_row():
dictionary = {"column 1": [1, 2, 3, 4], "column 2": [5, 6, 7, 8]}
df = dataframe(dictionary)
answer = df.get_row(0)
expected_answer = [1, 5]
assert answer == expected_answer
def test_sum_numbers_avoid_nonnumerical():
dictionary = {"column 1": [1, 2, 3, 4], "column 2": ["a", "b", "c", "d"]}
df = dataframe(dictionary)
answer = df.sum()
expected_answer = [10]
assert answer == expected_answer
def test_mean_numbers():
dictionary = {"column 1": [1, 2, 3, 4], "column 2": [5, 6, 7, 8]}
df = dataframe(dictionary)
answer = df.mean()
expected_answer = [2.5, 6.5]
assert answer == expected_answer
def test_sum_numbers():
dictionary = {"column 1": [1, 2, 3, 4], "column 2": [5, 6, 7, 8]}
df = dataframe(dictionary)
answer = df.sum()
expected_answer = [10, 26]
assert answer == expected_answer
def test_var_numbers():
dictionary = {"column 1": [1, 2, 3, 4, 5], "column 2": [5, 6, 7, 8, 9]}
df = dataframe(dictionary)
answer = df.var()
expected_answer = [2, 2]
assert answer == expected_answer
def test_range_numbers():
dictionary = {"column 1": [1, 2, 3, 4], "column 2": [5, 6, 7, 8]}
df = dataframe(dictionary)
answer = df.range()
expected_answer = [3, 3]
assert answer == expected_answer
def test_set_item():
dictionary = {"c1": [1, 2, 3, 4],
"c2": ["a", "b", "c", "d"],
"c3": [5.5, 6.5, 7.5, 8.5],
"c4": [True, False, True, False]}
df = dataframe(dictionary)
df['c1'] = [1, 0, 0, 0]
answer = df['c1']
expected_answer = np.asarray([1, 0, 0, 0])
assert np.all(answer == expected_answer)
def test_mode_numbers():
dictionary = {
"column 1": [1, 2, 3, 4, 3, 5, 2, 3, 4, 5, 1, 2, 2, 2, 2],
"column 2": [5, 6, 7, 8, 8, 8, 8, 5, 1, 8, 2, 1, 4, 8]
}
df = dataframe(dictionary)
answer = df.mode()
expected_answer = [2, 8]
assert answer == expected_answer
def test_std_numbers():
dictionary = {"column 1": [1, 2, 3, 4, 5], "column 2": [5, 6, 7, 8, 9]}
df = dataframe(dictionary)
list = df.std()
answer = []
for i in range(0, len(list)):
rounded_number = round(list[i], 2)
answer.append(rounded_number)
expected_answer = [1.41, 1.41]
assert answer == expected_answer
def test_del_item():
dictionary = {
"c1": [1, 2, 3, 4],
"c2": ["a", "b", "c", "d"],
"c3": [5.5, 6.5, 7.5, 8.5],
"c4": [True, False, True, False]
}
df = dataframe(dictionary)
del df['c1']
try:
df['c1']
except Exception:
answer = True
expected_answer = True
assert answer == expected_answer
from ie_pandas import dataframe
test_data = {
"column 1": [1, 2, 3, 4, 5],
"column 2": [True, False, True, False, False],
"column 3": ['t1', 't2', 't3', 't4', 't5'],
"column 4": [16, 17, 18, 19, 20]
}
df = dataframe(test_data)
print(df)
