146 lines
7.2 KiB
Python
146 lines
7.2 KiB
Python
import random
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import sys
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from pathlib import Path
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import numpy as np
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import subprocess
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import importlib
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import codewars_test
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import pandas as pd
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# Update paths and filename
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path_answer = "/content/" # changed
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filename = "answer_bab3_percobaan4.py" # changed
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# Import the answer module
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pc = importlib.import_module(filename[:-3], ".")
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cmd = subprocess.run([sys.executable, f"{path_answer}{filename}"], capture_output=True) # changed
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@codewars_test.describe("BAB 3 | Percobaan 4")
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def fixed_tests():
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@codewars_test.it("1. Test Memuat Data")
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def test_load_data():
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print("========================================================================")
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# Assuming expected columns are "Customer ID", "Age" and "Total Spent (USD)"
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expected_columns = ["Customer ID","Age", "Total Spent (USD)"]
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try:
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codewars_test.assert_equals(list(pc.data_load().columns), expected_columns, "====> URL dataset yang digunakan tidak sesuai; kolom pada dataset berbeda")
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except Exception as e:
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codewars_test.fail(f"====> Error loading data; Terdapat Typo pada kode: {str(e)}")
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expected_rows = 50
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try:
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codewars_test.assert_equals(len(pc.data_load()), expected_rows, "====> URL dataset yang digunakan tidak sesuai; kolom pada dataset berbeda")
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except Exception as e:
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codewars_test.fail(f"====> Error checking row count; Terdapat Typo pada Kode: {str(e)}")
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print("")
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@codewars_test.it("2. TestShow First Five Rows")
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def test_show_first_five_rows():
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# Call the function and capture the output
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print("========================================================================")
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try:
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actual_output = pc.head_rows().shape[0] # Get the number of rows
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expected_rows = 5
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# Assert that the expected output matches the actual output
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codewars_test.assert_equals(actual_output, expected_rows, "pada head_rows(); Output Tidak Sesuai; Seharusnya menampilkan 5 baris data; Output anda" )
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except Exception as e:
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codewars_test.fail(f"====> Error pada head_rows(); Terdapat Typo pada kode function: {str(e)}")
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print("")
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@codewars_test.it("3. Test calculates descriptive statistics for Customer Age")
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def test_age_descriptive_stats():
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print("========================================================================")
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# Assert few basic statistics on age
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expected_mean =34.54
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expected_std =13.069999921927455
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expected_median = 33.5
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expected_skew = 0.2325824223215271
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try:
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codewars_test.assert_equals(pc.data_load()["Age"].mean(), expected_mean, "Age mean should be positive")
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codewars_test.assert_equals(pc.data_load()["Age"].std(), expected_std, "Age standard deviation should be positive")
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codewars_test.assert_equals(pc.data_load()["Age"].median(), expected_median, "Age mean should be positive")
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codewars_test.assert_equals(pc.data_load()["Age"].skew(), expected_skew, "Age standard deviation should be positive")
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quartile = pc.data_load()["Age"].quantile([0.25, 0.5, 0.75])
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codewars_test.assert_equals(type(quartile), pd.Series, "Quartiles should be a pandas Series")
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except Exception as e:
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codewars_test.fail(f"====> Error pada head_rows(); Terdapat Typo pada kode function: {str(e)}")
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print("")
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@codewars_test.it("4. Test quartiles's value | Age")
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def test_quartile_values():
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print("========================================================================")
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# Assuming quartiles are for "Age" (adjust expected values as needed)
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try:
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expected_quartiles = np.array([22.25, 33.50, 45.00]) # Adjust these based on your data
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tolerance = 5 # Adjust tolerance for approximate value comparison
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calculated_quartiles = pc.data_load()["Age"].quantile([0.25, 0.5, 0.75])
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codewars_test.assert_equals(np.allclose(calculated_quartiles, expected_quartiles, atol=tolerance), True, "Quartiles should be close to expected values")
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except Exception as e:
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codewars_test.fail(f"====> Error pada head_rows(); Terdapat Typo pada kode function: {str(e)}")
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print("")
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@codewars_test.it("5. Test calculates descriptive statistics for Total Spent")
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def test_total_spent_descriptive_stats():
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print("========================================================================")
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# Assert few basic statistics on total spent
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expected_mean =114.0
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expected_std =52.45989721993868
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expected_median = 110.0
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expected_skew = 0.19622312582543433
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try:
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codewars_test.assert_equals(pc.data_load()["Total Spent (USD)"].mean(), expected_mean, "Total Spent mean should be positive")
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codewars_test.assert_equals(pc.data_load()["Total Spent (USD)"].std(), expected_std, "Total Spent standard deviation should be positive")
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codewars_test.assert_equals(pc.data_load()["Total Spent (USD)"].median(), expected_median, "Age mean should be positive")
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codewars_test.assert_equals(pc.data_load()["Total Spent (USD)"].skew(), expected_skew, "Age standard deviation should be positive")
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quartile = pc.data_load()["Total Spent (USD)"].quantile([0.25, 0.5, 0.75])
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codewars_test.assert_equals(type(quartile), pd.Series, "Quartiles should be a pandas Series")
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except Exception as e:
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codewars_test.fail(f"====> Error pada head_rows(); Terdapat Typo pada kode function: {str(e)}")
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print("")
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@codewars_test.it("6. Test quartiles's value | Total Spent (USD)")
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def test_quartile_values():
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print("========================================================================")
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# Assuming quartiles are for "Age" (adjust expected values as needed)
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expected_quartiles = np.array([71.25, 110.00, 153.75]) # Adjust these based on your data
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tolerance = 5
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# Adjust tolerance for approximate value comparison
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try:
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calculated_quartiles = pc.data_load()["Total Spent (USD)"].quantile([0.25, 0.5, 0.75])
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codewars_test.assert_equals(np.allclose(calculated_quartiles, expected_quartiles, atol=tolerance), True, "Quartiles should be close to expected values")
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except Exception as e:
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codewars_test.fail(f"====> Error pada head_rows(); Terdapat Typo pada kode function: {str(e)}")
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print("")
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@codewars_test.it("7. calculates correlation coefficient")
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def test_correlation():
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print("========================================================================")
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# Assert correlation coefficient is a number
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try:
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corr_= pc.correlation()
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codewars_test.assert_equals(isinstance(corr_, float), True, ">>>> Error pada fungsi correlation(); Variabel 'correlation' Tidak Terdefinisi; Cek nama variabel")
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except Exception as e:
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codewars_test.fail(f"====> Error pada correlation(); Terdapat Typo pada kode function: {str(e)}")
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except NameError as e:
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codewars_test.fail(f"====> Error pada correlation(); Terdapat Typo pada kode function: {str(e)}")
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print("")
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