@@ -1040,7 +1040,7 @@ def test_append_all_nans(self):
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store.append('df2', df[10:], dropna=False)
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tm.assert_frame_equal(store['df2'], df)
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- # Test to make sure defaults are to not drop.
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+ # Test to make sure defaults are to not drop.
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# Corresponding to Issue 9382
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df_with_missing = DataFrame({'col1':[0, np.nan, 2], 'col2':[1, np.nan, np.nan]})
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@@ -1059,7 +1059,7 @@ def test_append_all_nans(self):
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with ensure_clean_path(self.path) as path:
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panel_with_missing.to_hdf(path, 'panel_with_missing', format='table')
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- reloaded_panel = read_hdf(path, 'panel_with_missing')
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+ reloaded_panel = read_hdf(path, 'panel_with_missing')
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tm.assert_panel_equal(panel_with_missing, reloaded_panel)
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def test_append_frame_column_oriented(self):
@@ -2440,9 +2440,9 @@ def test_terms(self):
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p4d = tm.makePanel4D()
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wpneg = Panel.fromDict({-1: tm.makeDataFrame(), 0: tm.makeDataFrame(),
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1: tm.makeDataFrame()})
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- store.put('wp', wp, table=True )
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- store.put('p4d', p4d, table=True )
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- store.put('wpneg', wpneg, table=True )
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+ store.put('wp', wp, format='table' )
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+ store.put('p4d', p4d, format='table' )
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+ store.put('wpneg', wpneg, format='table' )
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# panel
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result = store.select('wp', [Term(
@@ -2607,7 +2607,7 @@ def test_same_name_scoping(self):
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import pandas as pd
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df = DataFrame(np.random.randn(20, 2),index=pd.date_range('20130101',periods=20))
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- store.put('df', df, table=True )
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+ store.put('df', df, format='table' )
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expected = df[df.index>pd.Timestamp('20130105')]
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import datetime
@@ -3608,7 +3608,7 @@ def test_frame_select_complex(self):
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df.loc[df.index[0:4],'string'] = 'bar'
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with ensure_clean_store(self.path) as store:
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- store.put('df', df, table=True , data_columns=['string'])
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+ store.put('df', df, format='table' , data_columns=['string'])
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# empty
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result = store.select('df', 'index>df.index[3] & string="bar"')
@@ -3717,7 +3717,7 @@ def test_invalid_filtering(self):
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df = tm.makeTimeDataFrame()
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with ensure_clean_store(self.path) as store:
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- store.put('df', df, table=True )
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+ store.put('df', df, format='table' )
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# not implemented
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self.assertRaises(NotImplementedError, store.select, 'df', "columns=['A'] | columns=['B']")
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