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

The following are 17 code examples of pandas.core.dtypes.generic.ABCMultiIndex(). 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: excel.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def _format_header_regular(self):
        has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
        if has_aliases or self.header:
            coloffset = 0

            if self.index:
                coloffset = 1
                if isinstance(self.df.index, ABCMultiIndex):
                    coloffset = len(self.df.index[0])

            colnames = self.columns
            if has_aliases:
                if len(self.header) != len(self.columns):
                    raise ValueError('Writing {cols} cols but got {alias} '
                                     'aliases'.format(cols=len(self.columns),
                                                      alias=len(self.header)))
                else:
                    colnames = self.header

            for colindex, colname in enumerate(colnames):
                yield ExcelCell(self.rowcounter, colindex + coloffset, colname,
                                self.header_style)
Example #2
Source File: excel.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def _format_header_regular(self):
        has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
        if has_aliases or self.header:
            coloffset = 0

            if self.index:
                coloffset = 1
                if isinstance(self.df.index, ABCMultiIndex):
                    coloffset = len(self.df.index[0])

            colnames = self.columns
            if has_aliases:
                if len(self.header) != len(self.columns):
                    raise ValueError('Writing {cols} cols but got {alias} '
                                     'aliases'.format(cols=len(self.columns),
                                                      alias=len(self.header)))
                else:
                    colnames = self.header

            for colindex, colname in enumerate(colnames):
                yield ExcelCell(self.rowcounter, colindex + coloffset, colname,
                                self.header_style)
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: 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 #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: excel.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def _format_regular_rows(self):
        has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
        if has_aliases or self.header:
            self.rowcounter += 1

        # output index and index_label?
        if self.index:
            # check aliases
            # if list only take first as this is not a MultiIndex
            if (self.index_label and
                    isinstance(self.index_label, (list, tuple, np.ndarray,
                                                  Index))):
                index_label = self.index_label[0]
            # if string good to go
            elif self.index_label and isinstance(self.index_label, str):
                index_label = self.index_label
            else:
                index_label = self.df.index.names[0]

            if isinstance(self.columns, ABCMultiIndex):
                self.rowcounter += 1

            if index_label and self.header is not False:
                yield ExcelCell(self.rowcounter - 1, 0, index_label,
                                self.header_style)

            # write index_values
            index_values = self.df.index
            if isinstance(self.df.index, ABCPeriodIndex):
                index_values = self.df.index.to_timestamp()

            for idx, idxval in enumerate(index_values):
                yield ExcelCell(self.rowcounter + idx, 0, idxval,
                                self.header_style)

            coloffset = 1
        else:
            coloffset = 0

        for cell in self._generate_body(coloffset):
            yield cell
Example #7
Source File: excel.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def _format_body(self):

        if isinstance(self.df.index, ABCMultiIndex):
            return self._format_hierarchical_rows()
        else:
            return self._format_regular_rows()
Example #8
Source File: html.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def write_style(self):
        # We use the "scoped" attribute here so that the desired
        # style properties for the data frame are not then applied
        # throughout the entire notebook.
        template_first = """\
            <style scoped>"""
        template_last = """\
            </style>"""
        template_select = """\
                .dataframe %s {
                    %s: %s;
                }"""
        element_props = [('tbody tr th:only-of-type',
                          'vertical-align',
                          'middle'),
                         ('tbody tr th',
                          'vertical-align',
                          'top')]
        if isinstance(self.columns, ABCMultiIndex):
            element_props.append(('thead tr th',
                                  'text-align',
                                  'left'))
            if self.show_row_idx_names:
                element_props.append(('thead tr:last-of-type th',
                                      'text-align',
                                      'right'))
        else:
            element_props.append(('thead th',
                                  'text-align',
                                  'right'))
        template_mid = '\n\n'.join(map(lambda t: template_select % t,
                                       element_props))
        template = dedent('\n'.join((template_first,
                                     template_mid,
                                     template_last)))
        self.write(template)
Example #9
Source File: html.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def _write_body(self, indent):
        self.write('<tbody>', indent)
        fmt_values = {i: self.fmt._format_col(i) for i in range(self.ncols)}

        # write values
        if self.fmt.index and isinstance(self.frame.index, ABCMultiIndex):
            self._write_hierarchical_rows(
                fmt_values, indent + self.indent_delta)
        else:
            self._write_regular_rows(
                fmt_values, indent + self.indent_delta)

        self.write('</tbody>', indent)
Example #10
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 #11
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 #12
Source File: excel.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def _format_regular_rows(self):
        has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
        if has_aliases or self.header:
            self.rowcounter += 1

        # output index and index_label?
        if self.index:
            # check aliases
            # if list only take first as this is not a MultiIndex
            if (self.index_label and
                    isinstance(self.index_label, (list, tuple, np.ndarray,
                                                  Index))):
                index_label = self.index_label[0]
            # if string good to go
            elif self.index_label and isinstance(self.index_label, str):
                index_label = self.index_label
            else:
                index_label = self.df.index.names[0]

            if isinstance(self.columns, ABCMultiIndex):
                self.rowcounter += 1

            if index_label and self.header is not False:
                yield ExcelCell(self.rowcounter - 1, 0, index_label,
                                self.header_style)

            # write index_values
            index_values = self.df.index
            if isinstance(self.df.index, ABCPeriodIndex):
                index_values = self.df.index.to_timestamp()

            for idx, idxval in enumerate(index_values):
                yield ExcelCell(self.rowcounter + idx, 0, idxval,
                                self.header_style)

            coloffset = 1
        else:
            coloffset = 0

        for cell in self._generate_body(coloffset):
            yield cell
Example #13
Source File: excel.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def _format_body(self):

        if isinstance(self.df.index, ABCMultiIndex):
            return self._format_hierarchical_rows()
        else:
            return self._format_regular_rows()
Example #14
Source File: html.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def write_style(self):
        # We use the "scoped" attribute here so that the desired
        # style properties for the data frame are not then applied
        # throughout the entire notebook.
        template_first = """\
            <style scoped>"""
        template_last = """\
            </style>"""
        template_select = """\
                .dataframe %s {
                    %s: %s;
                }"""
        element_props = [('tbody tr th:only-of-type',
                          'vertical-align',
                          'middle'),
                         ('tbody tr th',
                          'vertical-align',
                          'top')]
        if isinstance(self.columns, ABCMultiIndex):
            element_props.append(('thead tr th',
                                  'text-align',
                                  'left'))
            if self.show_row_idx_names:
                element_props.append(('thead tr:last-of-type th',
                                      'text-align',
                                      'right'))
        else:
            element_props.append(('thead th',
                                  'text-align',
                                  'right'))
        template_mid = '\n\n'.join(map(lambda t: template_select % t,
                                       element_props))
        template = dedent('\n'.join((template_first,
                                     template_mid,
                                     template_last)))
        self.write(template)
Example #15
Source File: html.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def _write_body(self, indent):
        self.write('<tbody>', indent)
        fmt_values = {i: self.fmt._format_col(i) for i in range(self.ncols)}

        # write values
        if self.fmt.index and isinstance(self.frame.index, ABCMultiIndex):
            self._write_hierarchical_rows(
                fmt_values, indent + self.indent_delta)
        else:
            self._write_regular_rows(
                fmt_values, indent + self.indent_delta)

        self.write('</tbody>', indent)
Example #16
Source File: excel.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 4 votes vote down vote up 
def _format_header_mi(self):
        if self.columns.nlevels > 1:
            if not self.index:
                raise NotImplementedError("Writing to Excel with MultiIndex"
                                          " columns and no index "
                                          "('index'=False) is not yet "
                                          "implemented.")

        has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
        if not (has_aliases or self.header):
            return

        columns = self.columns
        level_strs = columns.format(sparsify=self.merge_cells, adjoin=False,
                                    names=False)
        level_lengths = get_level_lengths(level_strs)
        coloffset = 0
        lnum = 0

        if self.index and isinstance(self.df.index, ABCMultiIndex):
            coloffset = len(self.df.index[0]) - 1

        if self.merge_cells:
            # Format multi-index as a merged cells.
            for lnum in range(len(level_lengths)):
                name = columns.names[lnum]
                yield ExcelCell(lnum, coloffset, name, self.header_style)

            for lnum, (spans, levels, level_codes) in enumerate(zip(
                    level_lengths, columns.levels, columns.codes)):
                values = levels.take(level_codes)
                for i in spans:
                    if spans[i] > 1:
                        yield ExcelCell(lnum, coloffset + i + 1, values[i],
                                        self.header_style, lnum,
                                        coloffset + i + spans[i])
                    else:
                        yield ExcelCell(lnum, coloffset + i + 1, values[i],
                                        self.header_style)
        else:
            # Format in legacy format with dots to indicate levels.
            for i, values in enumerate(zip(*level_strs)):
                v = ".".join(map(pprint_thing, values))
                yield ExcelCell(lnum, coloffset + i + 1, v, self.header_style)

        self.rowcounter = lnum
Example #17
Source File: excel.py    From recruit with Apache License 2.0 4 votes vote down vote up 
def _format_header_mi(self):
        if self.columns.nlevels > 1:
            if not self.index:
                raise NotImplementedError("Writing to Excel with MultiIndex"
                                          " columns and no index "
                                          "('index'=False) is not yet "
                                          "implemented.")

        has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
        if not (has_aliases or self.header):
            return

        columns = self.columns
        level_strs = columns.format(sparsify=self.merge_cells, adjoin=False,
                                    names=False)
        level_lengths = get_level_lengths(level_strs)
        coloffset = 0
        lnum = 0

        if self.index and isinstance(self.df.index, ABCMultiIndex):
            coloffset = len(self.df.index[0]) - 1

        if self.merge_cells:
            # Format multi-index as a merged cells.
            for lnum in range(len(level_lengths)):
                name = columns.names[lnum]
                yield ExcelCell(lnum, coloffset, name, self.header_style)

            for lnum, (spans, levels, level_codes) in enumerate(zip(
                    level_lengths, columns.levels, columns.codes)):
                values = levels.take(level_codes)
                for i in spans:
                    if spans[i] > 1:
                        yield ExcelCell(lnum, coloffset + i + 1, values[i],
                                        self.header_style, lnum,
                                        coloffset + i + spans[i])
                    else:
                        yield ExcelCell(lnum, coloffset + i + 1, values[i],
                                        self.header_style)
        else:
            # Format in legacy format with dots to indicate levels.
            for i, values in enumerate(zip(*level_strs)):
                v = ".".join(map(pprint_thing, values))
                yield ExcelCell(lnum, coloffset + i + 1, v, self.header_style)

        self.rowcounter = lnum