Python pandas.core.dtypes.generic.ABCSparseArray() Examples

The following are 10 code examples of pandas.core.dtypes.generic.ABCSparseArray(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module pandas.core.dtypes.generic , or try the search function .
Example #1
Source File: test_generic.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_abc_types(self):
        assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
        assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
        assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
        assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
        assert isinstance(self.multi_index, gt.ABCMultiIndex)
        assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
        assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
        assert isinstance(self.period_index, gt.ABCPeriodIndex)
        assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
        assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
        assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
        assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
        assert isinstance(self.df, gt.ABCDataFrame)
        with catch_warnings(record=True):
            simplefilter('ignore', FutureWarning)
            assert isinstance(self.df.to_panel(), gt.ABCPanel)
        assert isinstance(self.sparse_series, gt.ABCSparseSeries)
        assert isinstance(self.sparse_array, gt.ABCSparseArray)
        assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
        assert isinstance(self.categorical, gt.ABCCategorical)
        assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)

        assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
        assert isinstance(pd.Period('2012', freq='A-DEC').freq,
                          gt.ABCDateOffset)
        assert not isinstance(pd.Period('2012', freq='A-DEC'),
                              gt.ABCDateOffset)
        assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
        assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)

        assert isinstance(self.datetime_array, gt.ABCDatetimeArray)
        assert not isinstance(self.datetime_index, gt.ABCDatetimeArray)

        assert isinstance(self.timedelta_array, gt.ABCTimedeltaArray)
        assert not isinstance(self.timedelta_index, gt.ABCTimedeltaArray)
Example #2
Source File: test_generic.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_abc_types(self):
        assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
        assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
        assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
        assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
        assert isinstance(self.multi_index, gt.ABCMultiIndex)
        assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
        assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
        assert isinstance(self.period_index, gt.ABCPeriodIndex)
        assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
        assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
        assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
        assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
        assert isinstance(self.df, gt.ABCDataFrame)
        with catch_warnings(record=True):
            assert isinstance(self.df.to_panel(), gt.ABCPanel)
        assert isinstance(self.sparse_series, gt.ABCSparseSeries)
        assert isinstance(self.sparse_array, gt.ABCSparseArray)
        assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
        assert isinstance(self.categorical, gt.ABCCategorical)
        assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)

        assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
        assert isinstance(pd.Period('2012', freq='A-DEC').freq,
                          gt.ABCDateOffset)
        assert not isinstance(pd.Period('2012', freq='A-DEC'),
                              gt.ABCDateOffset)
        assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
        assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)
Example #3
Source File: test_generic.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_abc_types(self):
        assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
        assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
        assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
        assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
        assert isinstance(self.multi_index, gt.ABCMultiIndex)
        assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
        assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
        assert isinstance(self.period_index, gt.ABCPeriodIndex)
        assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
        assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
        assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
        assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
        assert isinstance(self.df, gt.ABCDataFrame)
        with catch_warnings(record=True):
            simplefilter('ignore', FutureWarning)
            assert isinstance(self.df.to_panel(), gt.ABCPanel)
        assert isinstance(self.sparse_series, gt.ABCSparseSeries)
        assert isinstance(self.sparse_array, gt.ABCSparseArray)
        assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
        assert isinstance(self.categorical, gt.ABCCategorical)
        assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)

        assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
        assert isinstance(pd.Period('2012', freq='A-DEC').freq,
                          gt.ABCDateOffset)
        assert not isinstance(pd.Period('2012', freq='A-DEC'),
                              gt.ABCDateOffset)
        assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
        assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)

        assert isinstance(self.datetime_array, gt.ABCDatetimeArray)
        assert not isinstance(self.datetime_index, gt.ABCDatetimeArray)

        assert isinstance(self.timedelta_array, gt.ABCTimedeltaArray)
        assert not isinstance(self.timedelta_index, gt.ABCTimedeltaArray)
Example #4
Source File: series.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up 
def from_array(cls, arr, index=None, name=None, dtype=None, copy=False,
                   fastpath=False):
        # return a sparse series here
        if isinstance(arr, ABCSparseArray):
            from pandas.core.sparse.series import SparseSeries
            cls = SparseSeries

        return cls(arr, index=index, name=name, dtype=dtype, copy=copy,
                   fastpath=fastpath)
Example #5
Source File: test_generic.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_abc_types(self):
        assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
        assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
        assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
        assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
        assert isinstance(self.multi_index, gt.ABCMultiIndex)
        assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
        assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
        assert isinstance(self.period_index, gt.ABCPeriodIndex)
        assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
        assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
        assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
        assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
        assert isinstance(self.df, gt.ABCDataFrame)
        with catch_warnings(record=True):
            assert isinstance(self.df.to_panel(), gt.ABCPanel)
        assert isinstance(self.sparse_series, gt.ABCSparseSeries)
        assert isinstance(self.sparse_array, gt.ABCSparseArray)
        assert isinstance(self.categorical, gt.ABCCategorical)
        assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)

        assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
        assert isinstance(pd.Period('2012', freq='A-DEC').freq,
                          gt.ABCDateOffset)
        assert not isinstance(pd.Period('2012', freq='A-DEC'),
                              gt.ABCDateOffset)
Example #6
Source File: series.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def from_array(cls, arr, index=None, name=None, dtype=None, copy=False,
                   fastpath=False):
        # return a sparse series here
        if isinstance(arr, ABCSparseArray):
            from pandas.core.sparse.series import SparseSeries
            cls = SparseSeries

        return cls(arr, index=index, name=name, dtype=dtype, copy=copy,
                   fastpath=fastpath)
Example #7
Source File: test_generic.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_abc_types(self):
        assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
        assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
        assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
        assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
        assert isinstance(self.multi_index, gt.ABCMultiIndex)
        assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
        assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
        assert isinstance(self.period_index, gt.ABCPeriodIndex)
        assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
        assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
        assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
        assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
        assert isinstance(self.df, gt.ABCDataFrame)
        with catch_warnings(record=True):
            assert isinstance(self.df.to_panel(), gt.ABCPanel)
        assert isinstance(self.sparse_series, gt.ABCSparseSeries)
        assert isinstance(self.sparse_array, gt.ABCSparseArray)
        assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
        assert isinstance(self.categorical, gt.ABCCategorical)
        assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)

        assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
        assert isinstance(pd.Period('2012', freq='A-DEC').freq,
                          gt.ABCDateOffset)
        assert not isinstance(pd.Period('2012', freq='A-DEC'),
                              gt.ABCDateOffset)
        assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
        assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)
Example #8
Source File: format.py    From vnpy_crypto with MIT License 4 votes vote down vote up 
def _format_strings(self):
        if self.float_format is None:
            float_format = get_option("display.float_format")
            if float_format is None:
                fmt_str = ('{{x: .{prec:d}g}}'
                           .format(prec=get_option("display.precision")))
                float_format = lambda x: fmt_str.format(x=x)
        else:
            float_format = self.float_format

        formatter = (
            self.formatter if self.formatter is not None else
            (lambda x: pprint_thing(x, escape_chars=('\t', '\r', '\n'))))

        def _format(x):
            if self.na_rep is not None and is_scalar(x) and isna(x):
                if x is None:
                    return 'None'
                elif x is pd.NaT:
                    return 'NaT'
                return self.na_rep
            elif isinstance(x, PandasObject):
                return u'{x}'.format(x=x)
            else:
                # object dtype
                return u'{x}'.format(x=formatter(x))

        vals = self.values
        if isinstance(vals, Index):
            vals = vals._values
        elif isinstance(vals, ABCSparseArray):
            vals = vals.values

        is_float_type = lib.map_infer(vals, is_float) & notna(vals)
        leading_space = is_float_type.any()

        fmt_values = []
        for i, v in enumerate(vals):
            if not is_float_type[i] and leading_space:
                fmt_values.append(u' {v}'.format(v=_format(v)))
            elif is_float_type[i]:
                fmt_values.append(float_format(v))
            else:
                fmt_values.append(u' {v}'.format(v=_format(v)))

        return fmt_values
Example #9
Source File: format.py    From Splunking-Crime with GNU Affero General Public License v3.0 4 votes vote down vote up 
def _format_strings(self):
        if self.float_format is None:
            float_format = get_option("display.float_format")
            if float_format is None:
                fmt_str = ('{{x: .{prec:d}g}}'
                           .format(prec=get_option("display.precision")))
                float_format = lambda x: fmt_str.format(x=x)
        else:
            float_format = self.float_format

        formatter = (
            self.formatter if self.formatter is not None else
            (lambda x: pprint_thing(x, escape_chars=('\t', '\r', '\n'))))

        def _format(x):
            if self.na_rep is not None and lib.checknull(x):
                if x is None:
                    return 'None'
                elif x is pd.NaT:
                    return 'NaT'
                return self.na_rep
            elif isinstance(x, PandasObject):
                return u'{x}'.format(x=x)
            else:
                # object dtype
                return u'{x}'.format(x=formatter(x))

        vals = self.values
        if isinstance(vals, Index):
            vals = vals._values
        elif isinstance(vals, ABCSparseArray):
            vals = vals.values

        is_float_type = lib.map_infer(vals, is_float) & notna(vals)
        leading_space = is_float_type.any()

        fmt_values = []
        for i, v in enumerate(vals):
            if not is_float_type[i] and leading_space:
                fmt_values.append(u' {v}'.format(v=_format(v)))
            elif is_float_type[i]:
                fmt_values.append(float_format(v))
            else:
                fmt_values.append(u' {v}'.format(v=_format(v)))

        return fmt_values
Example #10
Source File: format.py    From elasticintel with GNU General Public License v3.0 4 votes vote down vote up 
def _format_strings(self):
        if self.float_format is None:
            float_format = get_option("display.float_format")
            if float_format is None:
                fmt_str = ('{{x: .{prec:d}g}}'
                           .format(prec=get_option("display.precision")))
                float_format = lambda x: fmt_str.format(x=x)
        else:
            float_format = self.float_format

        formatter = (
            self.formatter if self.formatter is not None else
            (lambda x: pprint_thing(x, escape_chars=('\t', '\r', '\n'))))

        def _format(x):
            if self.na_rep is not None and lib.checknull(x):
                if x is None:
                    return 'None'
                elif x is pd.NaT:
                    return 'NaT'
                return self.na_rep
            elif isinstance(x, PandasObject):
                return u'{x}'.format(x=x)
            else:
                # object dtype
                return u'{x}'.format(x=formatter(x))

        vals = self.values
        if isinstance(vals, Index):
            vals = vals._values
        elif isinstance(vals, ABCSparseArray):
            vals = vals.values

        is_float_type = lib.map_infer(vals, is_float) & notna(vals)
        leading_space = is_float_type.any()

        fmt_values = []
        for i, v in enumerate(vals):
            if not is_float_type[i] and leading_space:
                fmt_values.append(u' {v}'.format(v=_format(v)))
            elif is_float_type[i]:
                fmt_values.append(float_format(v))
            else:
                fmt_values.append(u' {v}'.format(v=_format(v)))

        return fmt_values