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Commit4276457

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Improved tasks 2877-2881
1 parentb665e1e commit4276457

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5 files changed

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5 files changed

+279
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importunittest
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importpandasaspd
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fromtypingimportList
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defcreateDataframe(student_data:List[List[int]])->pd.DataFrame:
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column_name= ['student_id','age']
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result=pd.DataFrame(student_data,columns=column_name)
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returnresult
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classTestCreateDataframe(unittest.TestCase):
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deftest_valid_data(self):
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student_data= [[1,15], [2,11], [3,11], [4,20]]
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expected_df=pd.DataFrame({
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'student_id': [1,2,3,4],
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'age': [15,11,11,20]
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})
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result_df=createDataframe(student_data)
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pd.testing.assert_frame_equal(result_df,expected_df)
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deftest_empty_data(self):
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student_data= []
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expected_df=pd.DataFrame(columns=['student_id','age'])
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result_df=createDataframe(student_data)
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pd.testing.assert_frame_equal(result_df,expected_df)
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deftest_single_row(self):
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student_data= [[5,18]]
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expected_df=pd.DataFrame({
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'student_id': [5],
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'age': [18]
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})
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result_df=createDataframe(student_data)
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pd.testing.assert_frame_equal(result_df,expected_df)
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deftest_negative_age(self):
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student_data= [[6,-10]]
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expected_df=pd.DataFrame({
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'student_id': [6],
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'age': [-10]
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})
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result_df=createDataframe(student_data)
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pd.testing.assert_frame_equal(result_df,expected_df)
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if__name__=='__main__':
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unittest.main()
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importunittest
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importpandasaspd
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fromtypingimportList
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defgetDataframeSize(players:pd.DataFrame)->List[int]:
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return [players.shape[0],players.shape[1]]
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classTestGetDataframeSize(unittest.TestCase):
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deftest_example_case(self):
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# Example DataFrame
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data= {
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"player_id": [846,749,155,583,388,883,355,247,761,642],
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"name": ["Mason","Riley","Bob","Isabella","Zachary","Ava","Violet","Thomas","Jack","Charlie"],
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"age": [21,30,28,32,24,23,18,27,33,36],
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"position": ["Forward","Winger","Striker","Goalkeeper","Midfielder","Defender","Striker","Striker","Midfielder","Center-back"],
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"team": ["RealMadrid","Barcelona","ManchesterUnited","Liverpool","BayernMunich","Chelsea","Juventus","ParisSaint-Germain","ManchesterCity","Arsenal"]
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}
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players=pd.DataFrame(data)
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# Expected result: 10 rows, 5 columns
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expected_output= [10,5]
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self.assertEqual(getDataframeSize(players),expected_output)
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deftest_empty_dataframe(self):
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# Empty DataFrame
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players=pd.DataFrame(columns=["player_id","name","age","position","team"])
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# Expected result: 0 rows, 5 columns
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expected_output= [0,5]
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self.assertEqual(getDataframeSize(players),expected_output)
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deftest_single_row(self):
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# DataFrame with a single row
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data= {
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"player_id": [1],
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"name": ["John"],
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"age": [25],
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"position": ["Forward"],
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"team": ["TestTeam"]
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}
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players=pd.DataFrame(data)
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# Expected result: 1 row, 5 columns
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expected_output= [1,5]
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self.assertEqual(getDataframeSize(players),expected_output)
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deftest_different_columns(self):
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# DataFrame with more columns
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data= {
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"player_id": [1,2],
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"name": ["John","Doe"],
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"age": [25,30],
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"position": ["Forward","Midfielder"],
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"team": ["TestTeam","AnotherTeam"],
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"goals": [15,20]
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}
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players=pd.DataFrame(data)
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# Expected result: 2 rows, 6 columns
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expected_output= [2,6]
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self.assertEqual(getDataframeSize(players),expected_output)
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if__name__=="__main__":
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unittest.main()
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importunittest
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importpandasaspd
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defselectFirstRows(zs:pd.DataFrame)->pd.DataFrame:
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returnzs.head(3)
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classTestSelectFirstRows(unittest.TestCase):
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deftest_example_case(self):
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# Example DataFrame
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data= {
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"employee_id": [3,90,9,60,49,43],
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"name": ["Bob","Alice","Tatiana","Annabelle","Jonathan","Khaled"],
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"department": ["Operations","Sales","Engineering","InformationTechnology","HumanResources","Administration"],
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"salary": [48675,11096,33805,37678,23793,40454]
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}
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employees=pd.DataFrame(data)
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# Expected DataFrame with the first 3 rows
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expected_data= {
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"employee_id": [3,90,9],
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"name": ["Bob","Alice","Tatiana"],
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"department": ["Operations","Sales","Engineering"],
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"salary": [48675,11096,33805]
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}
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expected_output=pd.DataFrame(expected_data)
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pd.testing.assert_frame_equal(selectFirstRows(employees),expected_output)
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deftest_less_than_three_rows(self):
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# DataFrame with less than 3 rows
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data= {
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"employee_id": [1,2],
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"name": ["John","Doe"],
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"department": ["HR","IT"],
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"salary": [50000,60000]
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}
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employees=pd.DataFrame(data)
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# Expected DataFrame (same as input since there are fewer than 3 rows)
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expected_output=employees.copy()
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pd.testing.assert_frame_equal(selectFirstRows(employees),expected_output)
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deftest_empty_dataframe(self):
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# Empty DataFrame
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employees=pd.DataFrame(columns=["employee_id","name","department","salary"])
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# Expected result: Empty DataFrame with same columns
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expected_output=employees.copy()
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pd.testing.assert_frame_equal(selectFirstRows(employees),expected_output)
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deftest_exactly_three_rows(self):
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# DataFrame with exactly 3 rows
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data= {
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"employee_id": [10,20,30],
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"name": ["Eve","Mark","Lily"],
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"department": ["Finance","Operations","Engineering"],
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"salary": [70000,65000,72000]
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}
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employees=pd.DataFrame(data)
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# Expected DataFrame (same as input since there are exactly 3 rows)
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expected_output=employees.copy()
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pd.testing.assert_frame_equal(selectFirstRows(employees),expected_output)
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if__name__=="__main__":
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unittest.main()
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importunittest
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importpandasaspd
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defselectData(students:pd.DataFrame)->pd.DataFrame:
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returnstudents[students.student_id==101][['name','age']]
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classTestSelectData(unittest.TestCase):
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deftest_example_case(self):
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# Example DataFrame
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data= {
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"student_id": [101,53,128,3],
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"name": ["Ulysses","William","Henry","Henry"],
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"age": [13,10,6,11]
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}
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students=pd.DataFrame(data)
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# Expected output DataFrame with explicit data types
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expected_data= {
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"name":pd.Series(["Ulysses"],dtype="object"),
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"age":pd.Series([13],dtype="int64")
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}
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expected_output=pd.DataFrame(expected_data)
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pd.testing.assert_frame_equal(selectData(students),expected_output,check_dtype=False)
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deftest_no_matching_id(self):
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# DataFrame with no matching student_id = 101
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data= {
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"student_id": [102,53,128,3],
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"name": ["John","William","Henry","Doe"],
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"age": [12,10,6,11]
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}
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students=pd.DataFrame(data)
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# Expected output: Empty DataFrame with columns ['name', 'age']
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expected_output=pd.DataFrame(columns=['name','age'])
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pd.testing.assert_frame_equal(selectData(students),expected_output,check_dtype=False)
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deftest_multiple_students_with_101(self):
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# DataFrame with multiple students having student_id = 101
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data= {
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"student_id": [101,101,128],
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"name": ["Alice","Bob","Charlie"],
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"age": [20,21,22]
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}
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students=pd.DataFrame(data)
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# Expected output: DataFrame with both rows where student_id = 101
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expected_data= {
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"name": ["Alice","Bob"],
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"age": [20,21]
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}
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expected_output=pd.DataFrame(expected_data)
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pd.testing.assert_frame_equal(selectData(students),expected_output,check_dtype=False)
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deftest_empty_dataframe(self):
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# Empty DataFrame with the same structure
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students=pd.DataFrame(columns=["student_id","name","age"])
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# Expected output: Empty DataFrame with columns ['name', 'age']
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expected_output=pd.DataFrame(columns=['name','age'])
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pd.testing.assert_frame_equal(selectData(students),expected_output,check_dtype=False)
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if__name__=="__main__":
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unittest.main()
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importunittest
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importpandasaspd
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defcreateBonusColumn(employees:pd.DataFrame)->pd.DataFrame:
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employees["bonus"]=employees["salary"]*2
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returnemployees
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classTestCreateBonusColumn(unittest.TestCase):
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deftest_create_bonus_column(self):
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# Example DataFrame as input
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data= {
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"name": ["Piper","Grace","Georgia","Willow","Finn","Thomas"],
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"salary": [4548,28150,1103,6593,74576,24433]
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}
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employees=pd.DataFrame(data)
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# Expected output DataFrame
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expected_data= {
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"name": ["Piper","Grace","Georgia","Willow","Finn","Thomas"],
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"salary": [4548,28150,1103,6593,74576,24433],
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"bonus": [9096,56300,2206,13186,149152,48866]
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}
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expected_output=pd.DataFrame(expected_data)
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# Test the function
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result=createBonusColumn(employees)
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# Use pandas testing utilities to compare DataFrames
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pd.testing.assert_frame_equal(result,expected_output)
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if__name__=='__main__':
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unittest.main()

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