def test_df_sum():
test_df = sloth.dataframe(test_data)
sum_list = test_df.sum()
expected_sum_list = [
'String col', 18, 2, 30, -0.5612979999999999, 'String col'
]
assert sum_list == expected_sum_list
def test_df_mean():
test_df = sloth.dataframe(test_data)
mean_list = test_df.mean()
expected_mean_list = [
'String col', 3.6, 0.4, 6.0, -0.11225959999999997, 'String col'
]
assert mean_list == expected_mean_list
def check_df_sum():
test_df = dataframe(test_data)
sum_list = test_df.sum()
expected_sum_list = [
'String col', 18, 2, 21, -0.8375299999999999, 'String col'
]
assert sum_list == expected_sum_list
def check_df_mean():
test_df = dataframe(test_data)
mean_list = test_df.mean()
expected_mean_list = [
'String col', 3.6000000000000005, 0.4, 4.2, -0.16750599999999993,
'String col'
]
assert mean_list == expected_mean_list
def check_df_nparray():
test_df = dataframe(test_data)
for array in test_df.columns:
assert isinstance(test_df[array], np.ndarray)
def check_df_median():
test_df = dataframe(test_data)
median_list = test_df.median()
expected_median_list = ['String col', 4, 0, 2, 0.0, 'String col']
assert median_list == expected_median_list
def test_set_item():
test_df = sloth.dataframe(test_data)
dfcolumns = test_df.columns
expected_column2 = test_data.keys()
assert dfcolumns == expected_column2
def test_set_item():
test_df = sloth.dataframe(test_data)
dflen = len(test_df)
expected_column2 = 5
assert dflen == expected_column2
def test_df_showrow():
test_df = sloth.dataframe(test_data)
row_list = test_df.showrow(3)
expected_row_list = ['fish', 0, 0, 8, 1.047249, False]
assert row_list == expected_row_list
def check_df_showrow():
test_df = dataframe(test_data)
row_list = test_df.showrow(3)
expected_row_list = f"Row nº3: ['fish', 0, 0, 8, 1.047249, False]"
assert row_list == expected_row_list
def test_df_min():
test_df = sloth.dataframe(test_data)
min_list = test_df.min()
expected_min_list = ['cat', 0, 0, 1, -1.509059, False]
assert min_list == expected_min_list
def test_df_index():
test_df = sloth.dataframe(test_data)
column2 = test_df["num_legs"]
expected_column2 = np.array([2, 4, 8, 0, 4])
assert all(column2 == expected_column2)
def check_df_max():
test_df = dataframe(test_data)
max_list = test_df.max()
expected_max_list = ['monkey', 8, 2, 9, 1.047249, False]
assert max_list == expected_max_list
def test_df_median():
test_df = sloth.dataframe(test_data)
median_list = test_df.median()
expected_median_list = ['String col', 4, 0, 8, 0.119209, 'String col']
assert median_list == expected_median_list
def test_set_item():
test_df = sloth.dataframe(test_data)
test_df["num_legs"] = 2
expected_column2 = np.array([2, 2, 2, 2, 2])
assert all(test_df["num_legs"] == expected_column2)
def test_df_max():
test_df = sloth.dataframe(test_data)
max_list = test_df.max()
expected_max_list = ['spider', 8, 2, 10, 1.047249, True]
assert max_list == expected_max_list
def test_set_item():
test_df = sloth.dataframe(test_data)
dfindex = test_df.index
expected_column2 = np.array([0, 1, 2, 3, 4])
assert all(dfindex == expected_column2)
def test_df_columns():
test_df = sloth.dataframe(test_data)
col_list = list(test_df.columns)
expect_col_list = ['species','num_legs','num_wings','num_specimen_seen','statistics','mammal']
assert col_list == expect_col_list
