Python pandas.core.common._try_sort() Examples

The following are 11 code examples of pandas.core.common._try_sort(). 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.common , or try the search function .
Example #1
Source File: _core.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def _iter_data(self, data=None, keep_index=False, fillna=None):
        if data is None:
            data = self.data
        if fillna is not None:
            data = data.fillna(fillna)

        # TODO: unused?
        # if self.sort_columns:
        #     columns = com._try_sort(data.columns)
        # else:
        #     columns = data.columns

        for col, values in data.iteritems():
            if keep_index is True:
                yield col, values
            else:
                yield col, values.values
Example #2
Source File: api.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def _sanitize_and_check(indexes):
    kinds = list({type(index) for index in indexes})

    if list in kinds:
        if len(kinds) > 1:
            indexes = [Index(com._try_sort(x))
                       if not isinstance(x, Index) else
                       x for x in indexes]
            kinds.remove(list)
        else:
            return indexes, 'list'

    if len(kinds) > 1 or Index not in kinds:
        return indexes, 'special'
    else:
        return indexes, 'array'
Example #3
Source File: plotting.py    From Computable with MIT License 6 votes vote down vote up 
def _iter_data(self):
        from pandas.core.frame import DataFrame
        if isinstance(self.data, (Series, np.ndarray)):
            yield self.label, np.asarray(self.data)
        elif isinstance(self.data, DataFrame):
            df = self.data

            if self.sort_columns:
                columns = com._try_sort(df.columns)
            else:
                columns = df.columns

            for col in columns:
                # # is this right?
                # empty = df[col].count() == 0
                # values = df[col].values if not empty else np.zeros(len(df))

                values = df[col].values
                yield col, values
Example #4
Source File: index.py    From Computable with MIT License 6 votes vote down vote up 
def _sanitize_and_check(indexes):
    kinds = list(set([type(index) for index in indexes]))

    if list in kinds:
        if len(kinds) > 1:
            indexes = [Index(com._try_sort(x))
                       if not isinstance(x, Index) else x
                       for x in indexes]
            kinds.remove(list)
        else:
            return indexes, 'list'

    if len(kinds) > 1 or Index not in kinds:
        return indexes, 'special'
    else:
        return indexes, 'array'
Example #5
Source File: _core.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up 
def _iter_data(self, data=None, keep_index=False, fillna=None):
        if data is None:
            data = self.data
        if fillna is not None:
            data = data.fillna(fillna)

        # TODO: unused?
        # if self.sort_columns:
        #     columns = _try_sort(data.columns)
        # else:
        #     columns = data.columns

        for col, values in data.iteritems():
            if keep_index is True:
                yield col, values
            else:
                yield col, values.values
Example #6
Source File: api.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up 
def _sanitize_and_check(indexes):
    kinds = list(set([type(index) for index in indexes]))

    if list in kinds:
        if len(kinds) > 1:
            indexes = [Index(com._try_sort(x))
                       if not isinstance(x, Index) else
                       x for x in indexes]
            kinds.remove(list)
        else:
            return indexes, 'list'

    if len(kinds) > 1 or Index not in kinds:
        return indexes, 'special'
    else:
        return indexes, 'array'
Example #7
Source File: _core.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def _iter_data(self, data=None, keep_index=False, fillna=None):
        if data is None:
            data = self.data
        if fillna is not None:
            data = data.fillna(fillna)

        # TODO: unused?
        # if self.sort_columns:
        #     columns = _try_sort(data.columns)
        # else:
        #     columns = data.columns

        for col, values in data.iteritems():
            if keep_index is True:
                yield col, values
            else:
                yield col, values.values
Example #8
Source File: api.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def _sanitize_and_check(indexes):
    kinds = list(set([type(index) for index in indexes]))

    if list in kinds:
        if len(kinds) > 1:
            indexes = [Index(com._try_sort(x))
                       if not isinstance(x, Index) else
                       x for x in indexes]
            kinds.remove(list)
        else:
            return indexes, 'list'

    if len(kinds) > 1 or Index not in kinds:
        return indexes, 'special'
    else:
        return indexes, 'array'
Example #9
Source File: _core.py    From twitter-stock-recommendation with MIT License 6 votes vote down vote up 
def _iter_data(self, data=None, keep_index=False, fillna=None):
        if data is None:
            data = self.data
        if fillna is not None:
            data = data.fillna(fillna)

        # TODO: unused?
        # if self.sort_columns:
        #     columns = com._try_sort(data.columns)
        # else:
        #     columns = data.columns

        for col, values in data.iteritems():
            if keep_index is True:
                yield col, values
            else:
                yield col, values.values
Example #10
Source File: frame.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up 
def _init_dict(self, data, index, columns, dtype=None):
        # pre-filter out columns if we passed it
        if columns is not None:
            columns = _ensure_index(columns)
            data = dict((k, v) for k, v in compat.iteritems(data)
                        if k in columns)
        else:
            columns = Index(_try_sort(list(data.keys())))

        if index is None:
            index = extract_index(list(data.values()))

        sp_maker = lambda x: SparseArray(x, kind=self._default_kind,
                                         fill_value=self._default_fill_value,
                                         copy=True, dtype=dtype)
        sdict = {}
        for k, v in compat.iteritems(data):
            if isinstance(v, Series):
                # Force alignment, no copy necessary
                if not v.index.equals(index):
                    v = v.reindex(index)

                if not isinstance(v, SparseSeries):
                    v = sp_maker(v.values)
            elif isinstance(v, SparseArray):
                v = v.copy()
            else:
                if isinstance(v, dict):
                    v = [v.get(i, np.nan) for i in index]

                v = sp_maker(v)
            sdict[k] = v

        # TODO: figure out how to handle this case, all nan's?
        # add in any other columns we want to have (completeness)
        nan_arr = np.empty(len(index), dtype='float64')
        nan_arr.fill(np.nan)
        nan_arr = sp_maker(nan_arr)
        sdict.update((c, nan_arr) for c in columns if c not in sdict)

        return to_manager(sdict, columns, index)
Example #11
Source File: frame.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def _init_dict(self, data, index, columns, dtype=None):
        # pre-filter out columns if we passed it
        if columns is not None:
            columns = _ensure_index(columns)
            data = dict((k, v) for k, v in compat.iteritems(data)
                        if k in columns)
        else:
            columns = Index(_try_sort(list(data.keys())))

        if index is None:
            index = extract_index(list(data.values()))

        sp_maker = lambda x: SparseArray(x, kind=self._default_kind,
                                         fill_value=self._default_fill_value,
                                         copy=True, dtype=dtype)
        sdict = {}
        for k, v in compat.iteritems(data):
            if isinstance(v, Series):
                # Force alignment, no copy necessary
                if not v.index.equals(index):
                    v = v.reindex(index)

                if not isinstance(v, SparseSeries):
                    v = sp_maker(v.values)
            elif isinstance(v, SparseArray):
                v = v.copy()
            else:
                if isinstance(v, dict):
                    v = [v.get(i, np.nan) for i in index]

                v = sp_maker(v)
            sdict[k] = v

        # TODO: figure out how to handle this case, all nan's?
        # add in any other columns we want to have (completeness)
        nan_arr = np.empty(len(index), dtype='float64')
        nan_arr.fill(np.nan)
        nan_arr = sp_maker(nan_arr)
        sdict.update((c, nan_arr) for c in columns if c not in sdict)

        return to_manager(sdict, columns, index)