Python Series.append方法代碼示例

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import append [as 別名]
def test_series_append_aware_naive(self):
        rng1 = date_range('1/1/2011 01:00', periods=1, freq='H')
        rng2 = date_range('1/1/2011 02:00', periods=1, freq='H',
                          tz='US/Eastern')
        ser1 = Series(np.random.randn(len(rng1)), index=rng1)
        ser2 = Series(np.random.randn(len(rng2)), index=rng2)
        ts_result = ser1.append(ser2)

        expected = ser1.index.astype(object).append(ser2.index.astype(object))
        assert ts_result.index.equals(expected)

        # mixed
        rng1 = date_range('1/1/2011 01:00', periods=1, freq='H')
        rng2 = lrange(100)
        ser1 = Series(np.random.randn(len(rng1)), index=rng1)
        ser2 = Series(np.random.randn(len(rng2)), index=rng2)
        ts_result = ser1.append(ser2)

        expected = ser1.index.astype(object).append(ser2.index)
        assert ts_result.index.equals(expected) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import append [as 別名]
def test_series_append_dst(self):
        rng1 = date_range('1/1/2016 01:00', periods=3, freq='H',
                          tz='US/Eastern')
        rng2 = date_range('8/1/2016 01:00', periods=3, freq='H',
                          tz='US/Eastern')
        ser1 = Series([1, 2, 3], index=rng1)
        ser2 = Series([10, 11, 12], index=rng2)
        ts_result = ser1.append(ser2)

        exp_index = DatetimeIndex(['2016-01-01 01:00', '2016-01-01 02:00',
                                   '2016-01-01 03:00', '2016-08-01 01:00',
                                   '2016-08-01 02:00', '2016-08-01 03:00'],
                                  tz='US/Eastern')
        exp = Series([1, 2, 3, 10, 11, 12], index=exp_index)
        tm.assert_series_equal(ts_result, exp)
        assert ts_result.index.tz == rng1.tz

    # ----------------------------------------------------------------- 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import append [as 別名]
def test_series_append_aware(self):
        rng1 = date_range('1/1/2011 01:00', periods=1, freq='H',
                          tz='US/Eastern')
        rng2 = date_range('1/1/2011 02:00', periods=1, freq='H',
                          tz='US/Eastern')
        ser1 = Series([1], index=rng1)
        ser2 = Series([2], index=rng2)
        ts_result = ser1.append(ser2)

        exp_index = DatetimeIndex(['2011-01-01 01:00', '2011-01-01 02:00'],
                                  tz='US/Eastern')
        exp = Series([1, 2], index=exp_index)
        tm.assert_series_equal(ts_result, exp)
        assert ts_result.index.tz == rng1.tz

        rng1 = date_range('1/1/2011 01:00', periods=1, freq='H', tz='UTC')
        rng2 = date_range('1/1/2011 02:00', periods=1, freq='H', tz='UTC')
        ser1 = Series([1], index=rng1)
        ser2 = Series([2], index=rng2)
        ts_result = ser1.append(ser2)

        exp_index = DatetimeIndex(['2011-01-01 01:00', '2011-01-01 02:00'],
                                  tz='UTC')
        exp = Series([1, 2], index=exp_index)
        tm.assert_series_equal(ts_result, exp)
        utc = rng1.tz
        assert utc == ts_result.index.tz

        # GH#7795
        # different tz coerces to object dtype, not UTC
        rng1 = date_range('1/1/2011 01:00', periods=1, freq='H',
                          tz='US/Eastern')
        rng2 = date_range('1/1/2011 02:00', periods=1, freq='H',
                          tz='US/Central')
        ser1 = Series([1], index=rng1)
        ser2 = Series([2], index=rng2)
        ts_result = ser1.append(ser2)
        exp_index = Index([Timestamp('1/1/2011 01:00', tz='US/Eastern'),
                           Timestamp('1/1/2011 02:00', tz='US/Central')])
        exp = Series([1, 2], index=exp_index)
        tm.assert_series_equal(ts_result, exp) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import append [as 別名]
def _concat_indexes(indexes):
    return indexes[0].append(indexes[1:]) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import append [as 別名]
def get_result(self):

        # series only
        if self._is_series:

            # stack blocks
            if self.axis == 0:
                name = com.consensus_name_attr(self.objs)

                mgr = self.objs[0]._data.concat([x._data for x in self.objs],
                                                self.new_axes)
                cons = _concat._get_series_result_type(mgr, self.objs)
                return cons(mgr, name=name).__finalize__(self, method='concat')

            # combine as columns in a frame
            else:
                data = dict(zip(range(len(self.objs)), self.objs))
                cons = _concat._get_series_result_type(data)

                index, columns = self.new_axes
                df = cons(data, index=index)
                df.columns = columns
                return df.__finalize__(self, method='concat')

        # combine block managers
        else:
            mgrs_indexers = []
            for obj in self.objs:
                mgr = obj._data
                indexers = {}
                for ax, new_labels in enumerate(self.new_axes):
                    if ax == self.axis:
                        # Suppress reindexing on concat axis
                        continue

                    obj_labels = mgr.axes[ax]
                    if not new_labels.equals(obj_labels):
                        indexers[ax] = obj_labels.reindex(new_labels)[1]

                mgrs_indexers.append((obj._data, indexers))

            new_data = concatenate_block_managers(
                mgrs_indexers, self.new_axes, concat_axis=self.axis,
                copy=self.copy)
            if not self.copy:
                new_data._consolidate_inplace()

            cons = _concat._get_frame_result_type(new_data, self.objs)
            return (cons._from_axes(new_data, self.new_axes)
                    .__finalize__(self, method='concat')) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import append [as 別名]
def get_result(self):

        # series only
        if self._is_series:

            # stack blocks
            if self.axis == 0:
                name = com._consensus_name_attr(self.objs)

                mgr = self.objs[0]._data.concat([x._data for x in self.objs],
                                                self.new_axes)
                cons = _concat._get_series_result_type(mgr, self.objs)
                return cons(mgr, name=name).__finalize__(self, method='concat')

            # combine as columns in a frame
            else:
                data = dict(zip(range(len(self.objs)), self.objs))
                cons = _concat._get_series_result_type(data)

                index, columns = self.new_axes
                df = cons(data, index=index)
                df.columns = columns
                return df.__finalize__(self, method='concat')

        # combine block managers
        else:
            mgrs_indexers = []
            for obj in self.objs:
                mgr = obj._data
                indexers = {}
                for ax, new_labels in enumerate(self.new_axes):
                    if ax == self.axis:
                        # Suppress reindexing on concat axis
                        continue

                    obj_labels = mgr.axes[ax]
                    if not new_labels.equals(obj_labels):
                        indexers[ax] = obj_labels.reindex(new_labels)[1]

                mgrs_indexers.append((obj._data, indexers))

            new_data = concatenate_block_managers(
                mgrs_indexers, self.new_axes, concat_axis=self.axis,
                copy=self.copy)
            if not self.copy:
                new_data._consolidate_inplace()

            cons = _concat._get_frame_result_type(new_data, self.objs)
            return (cons._from_axes(new_data, self.new_axes)
                    .__finalize__(self, method='concat'))