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Commit22455a9

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Improved tasks 2888, 2889, 2890, 2891
1 parent1891ffc commit22455a9

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4 files changed

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4 files changed

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Lines changed: 141 additions & 0 deletions
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importunittest
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importpandasaspd
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frompandas.testingimportassert_frame_equal
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defconcatenateTables(df1:pd.DataFrame,df2:pd.DataFrame)->pd.DataFrame:
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returnpd.concat([df1,df2],ignore_index=True)
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classTestConcatenateTables(unittest.TestCase):
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deftest_concatenate_normal_case(self):
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# Input DataFrames
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df1=pd.DataFrame({
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"student_id": [1,2,3,4],
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"name": ["Mason","Ava","Taylor","Georgia"],
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"age": [8,6,15,17]
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})
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df2=pd.DataFrame({
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"student_id": [5,6],
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"name": ["Leo","Alex"],
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"age": [7,7]
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})
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# Expected Output
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expected=pd.DataFrame({
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"student_id": [1,2,3,4,5,6],
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"name": ["Mason","Ava","Taylor","Georgia","Leo","Alex"],
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"age": [8,6,15,17,7,7]
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})
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# Actual Output
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result=concatenateTables(df1,df2)
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# Assert the result matches the expected DataFrame
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try:
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assert_frame_equal(result,expected)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal:{e}")
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deftest_concatenate_empty_df1(self):
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# Input DataFrames
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df1=pd.DataFrame(columns=["student_id","name","age"]).astype({
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"student_id":"int64",
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"name":"object",
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"age":"int64"
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})
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df2=pd.DataFrame({
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"student_id": [5,6],
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"name": ["Leo","Alex"],
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"age": [7,7]
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})
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# Expected Output
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expected=pd.DataFrame({
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"student_id": [5,6],
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"name": ["Leo","Alex"],
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"age": [7,7]
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})
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# Actual Output
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result=concatenateTables(df1,df2)
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# Assert the result matches the expected DataFrame
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try:
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assert_frame_equal(result,expected)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal when df1 is empty:{e}")
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deftest_concatenate_empty_df2(self):
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# Input DataFrames
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df1=pd.DataFrame({
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"student_id": [1,2,3,4],
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"name": ["Mason","Ava","Taylor","Georgia"],
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"age": [8,6,15,17]
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})
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df2=pd.DataFrame(columns=["student_id","name","age"]).astype({
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"student_id":"int64",
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"name":"object",
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"age":"int64"
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})
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# Expected Output
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expected=df1
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# Actual Output
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result=concatenateTables(df1,df2)
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# Assert the result matches the expected DataFrame
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try:
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assert_frame_equal(result,expected)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal when df2 is empty:{e}")
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deftest_concatenate_both_empty(self):
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# Input DataFrames
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df1=pd.DataFrame(columns=["student_id","name","age"])
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df2=pd.DataFrame(columns=["student_id","name","age"])
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# Expected Output
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expected=pd.DataFrame(columns=["student_id","name","age"])
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# Actual Output
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result=concatenateTables(df1,df2)
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# Assert the result matches the expected DataFrame
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try:
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assert_frame_equal(result,expected)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal when both are empty:{e}")
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deftest_concatenate_different_column_order(self):
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# Input DataFrames
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df1=pd.DataFrame({
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"student_id": [1,2],
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"name": ["Mason","Ava"],
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"age": [8,6]
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})
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df2=pd.DataFrame({
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"name": ["Leo","Alex"],
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"age": [7,7],
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"student_id": [5,6]
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})
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# Expected Output
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expected=pd.DataFrame({
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"student_id": [1,2,5,6],
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"name": ["Mason","Ava","Leo","Alex"],
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"age": [8,6,7,7]
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})
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# Actual Output
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result=concatenateTables(df1,df2)
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# Assert the result matches the expected DataFrame
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try:
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assert_frame_equal(result,expected)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal when columns are in different orders:{e}")
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# Run the tests
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if__name__=="__main__":
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unittest.main()
Lines changed: 82 additions & 0 deletions
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importunittest
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importpandasaspd
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frompandas.testingimportassert_frame_equal
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# Method to be tested
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defpivotTable(weather:pd.DataFrame)->pd.DataFrame:
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result=weather.pivot(index='month',columns='city',values='temperature')
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result.columns.name=None
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returnresult.reset_index()
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# Unit Test Class
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classTestPivotTable(unittest.TestCase):
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deftest_pivot_table(self):
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# Input DataFrame
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input_data= {
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"city": ["Jacksonville","Jacksonville","Jacksonville","Jacksonville","Jacksonville",
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"ElPaso","ElPaso","ElPaso","ElPaso","ElPaso"],
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"month": ["January","February","March","April","May",
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"January","February","March","April","May"],
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"temperature": [13,23,38,5,34,20,6,26,2,43]
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}
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weather=pd.DataFrame(input_data)
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# Expected Output DataFrame
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expected_data= {
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"month": ["April","February","January","March","May"],
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"ElPaso": [2,6,20,26,43],
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"Jacksonville": [5,23,13,38,34]
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}
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expected_df=pd.DataFrame(expected_data)
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# Actual Output
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result_df=pivotTable(weather)
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# Assert the DataFrames are equal
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try:
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assert_frame_equal(result_df,expected_df)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal:{e}")
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deftest_empty_dataframe(self):
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# Test for an empty input DataFrame
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weather=pd.DataFrame(columns=["city","month","temperature"])
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expected_df=pd.DataFrame(columns=["month"])
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# Actual Output
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result_df=pivotTable(weather)
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# Assert the DataFrames are equal
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try:
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assert_frame_equal(result_df,expected_df)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal for empty input:{e}")
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deftest_single_row_dataframe(self):
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# Test for a single row input DataFrame
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input_data= {
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"city": ["ElPaso"],
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"month": ["January"],
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"temperature": [20]
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}
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weather=pd.DataFrame(input_data)
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# Expected Output DataFrame
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expected_data= {
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"month": ["January"],
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"ElPaso": [20]
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}
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expected_df=pd.DataFrame(expected_data)
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# Actual Output
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result_df=pivotTable(weather)
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# Assert the DataFrames are equal
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try:
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assert_frame_equal(result_df,expected_df)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal for single row input:{e}")
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# Run the tests
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if__name__=="__main__":
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unittest.main()
Lines changed: 82 additions & 0 deletions
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importunittest
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importpandasaspd
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frompandas.testingimportassert_frame_equal
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defmeltTable(report:pd.DataFrame)->pd.DataFrame:
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returnreport.melt(id_vars='product',var_name='quarter',value_name='sales')
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# Unit Test Class
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classTestMeltTable(unittest.TestCase):
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deftest_melt_table(self):
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# Input DataFrame
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input_data= {
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"product": ["Umbrella","SleepingBag"],
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"quarter_1": [417,800],
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"quarter_2": [224,936],
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"quarter_3": [379,93],
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"quarter_4": [611,875]
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}
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report=pd.DataFrame(input_data)
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# Expected Output DataFrame
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expected_data= {
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"product": ["Umbrella","SleepingBag","Umbrella","SleepingBag","Umbrella","SleepingBag","Umbrella","SleepingBag"],
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"quarter": ["quarter_1","quarter_1","quarter_2","quarter_2","quarter_3","quarter_3","quarter_4","quarter_4"],
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"sales": [417,800,224,936,379,93,611,875]
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}
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expected_df=pd.DataFrame(expected_data)
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# Actual Output
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result_df=meltTable(report)
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# Assert DataFrames are equal
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try:
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assert_frame_equal(result_df,expected_df)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal:{e}")
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deftest_empty_dataframe(self):
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# Test with an empty DataFrame
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report=pd.DataFrame(columns=["product","quarter_1","quarter_2","quarter_3","quarter_4"])
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expected_df=pd.DataFrame(columns=["product","quarter","sales"])
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# Actual Output
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result_df=meltTable(report)
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# Assert DataFrames are equal
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try:
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assert_frame_equal(result_df,expected_df)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal for empty input:{e}")
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deftest_single_row_dataframe(self):
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# Test with a single row DataFrame
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input_data= {
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"product": ["Umbrella"],
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"quarter_1": [417],
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"quarter_2": [224],
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"quarter_3": [379],
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"quarter_4": [611]
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}
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report=pd.DataFrame(input_data)
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# Expected Output DataFrame
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expected_data= {
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"product": ["Umbrella","Umbrella","Umbrella","Umbrella"],
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"quarter": ["quarter_1","quarter_2","quarter_3","quarter_4"],
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"sales": [417,224,379,611]
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}
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expected_df=pd.DataFrame(expected_data)
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# Actual Output
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result_df=meltTable(report)
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# Assert DataFrames are equal
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try:
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assert_frame_equal(result_df,expected_df)
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exceptAssertionErrorase:
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self.fail(f"DataFrames are not equal for single row input:{e}")
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# Run the tests
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if__name__=="__main__":
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unittest.main()

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