def test_init_scenario_1():
dict_x = {
"name": ["Tom", "Harry", "Dick", "Jerry"],
"age": [10, 20, 30, 40]
}
df1 = DataFrame(dict_x)
expected_output = [
{
"name": "Tom",
"age": 10
},
{
"name": "Harry",
"age": 20
},
{
"name": "Dick",
"age": 30
},
{
"name": "Jerry",
"age": 40
},
]
actual_output = df1.get_rows(0, 4)
# assert np.array_equal(actual_output, expected_output)
assert actual_output == expected_output
def test_colnames():
dict_x = {
"name": ["Tom", "Harry", "Dick", "Jerry"],
"age": [10, 20, 30, 40]
}
df1 = DataFrame(dict_x)
expected_output = ["name", "age"]
actual_output = df1.column_names()
assert actual_output == expected_output
def test_median():
dict_x = {
"name": ["Tom", "Harry", "Dick", "Jerry"],
"age": [10, 20, 30, 40],
"cars": [1, 2, 3, 4],
}
df1 = DataFrame(dict_x)
expected_output = [{"age": 25, "cars": 2.5}]
actual_output = df1.median()
assert actual_output == expected_output
def test_sum():
dict_x = {
"name": ["Tom", "Harry", "Dick", "Jerry"],
"age": [10, 20, 30, 40],
"cars": [1, 2, 3, 4],
}
df1 = DataFrame(dict_x)
expected_output = [{'age': 100, 'cars': 10}]
actual_output = df1.sum()
assert actual_output == expected_output
def test_init_error_scenario_1():
with pytest.raises(ValueError) as excinfo:
dict_x = [["Tom", "Harry", "Dick", "Jerry"], [10, 20, 30, 40]]
df1 = DataFrame(dict_x)
assert str(
excinfo.value) == "Wrong_Input_Type: Only dictionary is acceptable"
def test_init_error_scenario_4():
with pytest.raises(ValueError) as excinfo:
dict_x = {
"name": ["Tom", "Harry", "Dick", "Jerry"],
"age": [10, 20, "30", 40]
}
df1 = DataFrame(dict_x)
assert str(
excinfo.value) == "All the values in a column should be the same type"
def test_init_error_scenario_3():
with pytest.raises(ValueError) as excinfo:
dict_x = {
"name": ["Tom", "Harry", "Dick", "Jerry"],
"age": [None, 20, 30, 40]
}
df1 = DataFrame(dict_x)
assert (
str(excinfo.value) ==
"Wrong_Data_Type: Only integer, float,boolean and string are accepted")
def test_init_error_scenario_2():
with pytest.raises(ValueError) as excinfo:
dict_x = {
"name": ("Tom", "Harry", "Dick", "Jerry"),
"age": (10, 20, 30, 40)
}
df1 = DataFrame(dict_x)
assert (
str(excinfo.value) ==
"Wrong_Input_Type: Only dictionaryof list or Numpy array is acccepted")
from ie_pandas.DataFrame import DataFrame
import pytest
import numpy as np
dict_x = {"name": ["Tom", "Harry", "Dick", "Jerry"], "age": [10, 20, 30, 40]}
df1 = DataFrame(dict_x)
def test_get_row_scenario_1():
expected_output = np.array([10, 20, 30, 40])
actual_output = df1["age"]
assert np.array_equal(actual_output, expected_output)
def test_get_row_error_scenario_1():
with pytest.raises(ValueError) as excinfo:
df1["Nationality"]
assert (str(excinfo.value) ==
"Wrong_Column_Name: Column is not present in the DataFrame")
import pytest
import numpy as np
from ie_pandas.DataFrame import DataFrame
_dic1 = {
"name": ["Georges", "Alexandre", "Kelly"],
"Family": ["Koury", "Trump", "McKinsey"],
"age": [25, 26, 30],
}
_df = DataFrame(_dic1)
_dic2 = {"a": [3, 4, 5, 6], 1: [3, 4, 5, 6]}
_df2 = DataFrame(_dic2)
_dic3 = {
"list": [10, 11, 12, 13],
"numpy": np.array([7, 8, 9, 10]),
"str": ["a", "b", "c", "d"],
}
_df3 = DataFrame(_dic3)
@pytest.mark.parametrize(
"expected, colnames",
[
(np.array([25, 26, 30]), ("age")),
(
np.array([