Пример #1
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 def testappendDFReturnsEmptyDataFame(self):
     stocksData = {
     }
     npsy = NumpySciPy()
     df = npsy.initDataFrame(stocksData)
     actual = npsy.appendDF(dataframe=df,appendDataFrame=df)
     expected = pd.DataFrame(df).append(df)
Пример #2
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 def testdropDuplicateDFReturnsEmptyDataFame(self):
     stocksData = {
     }
     npsy = NumpySciPy()
     df = npsy.initDataFrame(stocksData)
     df = npsy.appendDF(dataframe=df,appendDataFrame=df)
     actual = npsy.dropDuplicatesDF(df)
     expected = pd.DataFrame(stocksData).append(df).drop_duplicates()
Пример #3
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 def testdropDuplicateReturnsDataFame(self):
     stockData = {
         "Blackstone": [49.56, 50.70, 51.18, 52.80, 52.87, 24.24, 24.60, 49.56, 26.90, 26.66]
     }
     npsy = NumpySciPy()
     df = npsy.initDataFrame(stockData)
     df = npsy.appendDF(dataframe=df,appendDataFrame=df)
     actual = npsy.dropDuplicatesDF(df)
     expected = pd.DataFrame(stockData).append(df).drop_duplicates()
Пример #4
0
 def testappendDFReturnsDataFame(self):
     stocksData = {
         "Blackstone": [49.56, 50.70, 51.18, 52.80, 52.87, 24.24, 24.60, 26.04, 26.90, 26.66],
         "KKR": [24.24, 24.60, 26.04, 26.90, 26.66, 24.24, 24.60, 26.04, 26.90, 26.66]
     }
     npsy = NumpySciPy()
     df = npsy.initDataFrame(stocksData)
     actual = npsy.appendDF(dataframe=df,appendDataFrame=df)
     expected = pd.DataFrame(stocksData).append(df)