Python pandas.core.indexing.maybe_convert_indices() Examples

The following are 20 code examples of pandas.core.indexing.maybe_convert_indices(). 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.indexing , or try the search function .
Example #1
Source File: managers.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def take(self, indexer, axis=1, verify=True, convert=True):
        """
        Take items along any axis.
        """
        self._consolidate_inplace()
        indexer = (np.arange(indexer.start, indexer.stop, indexer.step,
                             dtype='int64')
                   if isinstance(indexer, slice)
                   else np.asanyarray(indexer, dtype='int64'))

        n = self.shape[axis]
        if convert:
            indexer = maybe_convert_indices(indexer, n)

        if verify:
            if ((indexer == -1) | (indexer >= n)).any():
                raise Exception('Indices must be nonzero and less than '
                                'the axis length')

        new_labels = self.axes[axis].take(indexer)
        return self.reindex_indexer(new_axis=new_labels, indexer=indexer,
                                    axis=axis, allow_dups=True)
Example #2
Source File: base.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def _convert_list_indexer(self, keyarr, kind=None):
        if (kind in [None, 'iloc', 'ix'] and
                is_integer_dtype(keyarr) and not self.is_floating() and
                not isinstance(keyarr, ABCPeriodIndex)):

            if self.inferred_type == 'mixed-integer':
                indexer = self.get_indexer(keyarr)
                if (indexer >= 0).all():
                    return indexer
                # missing values are flagged as -1 by get_indexer and negative
                # indices are already converted to positive indices in the
                # above if-statement, so the negative flags are changed to
                # values outside the range of indices so as to trigger an
                # IndexError in maybe_convert_indices
                indexer[indexer < 0] = len(self)
                from pandas.core.indexing import maybe_convert_indices
                return maybe_convert_indices(indexer, len(self))

            elif not self.inferred_type == 'integer':
                keyarr = np.where(keyarr < 0, len(self) + keyarr, keyarr)
                return keyarr

        return None
Example #3
Source File: series.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def _take(self, indices, axis=0, is_copy=False):

        indices = ensure_platform_int(indices)
        new_index = self.index.take(indices)

        if is_categorical_dtype(self):
            # https://github.com/pandas-dev/pandas/issues/20664
            # TODO: remove when the default Categorical.take behavior changes
            indices = maybe_convert_indices(indices, len(self._get_axis(axis)))
            kwargs = {'allow_fill': False}
        else:
            kwargs = {}
        new_values = self._values.take(indices, **kwargs)

        result = (self._constructor(new_values, index=new_index,
                                    fastpath=True).__finalize__(self))

        # Maybe set copy if we didn't actually change the index.
        if is_copy:
            if not result._get_axis(axis).equals(self._get_axis(axis)):
                result._set_is_copy(self)

        return result
Example #4
Source File: base.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def _convert_list_indexer(self, keyarr, kind=None):
        if (kind in [None, 'iloc', 'ix'] and
                is_integer_dtype(keyarr) and not self.is_floating() and
                not isinstance(keyarr, ABCPeriodIndex)):

            if self.inferred_type == 'mixed-integer':
                indexer = self.get_indexer(keyarr)
                if (indexer >= 0).all():
                    return indexer
                # missing values are flagged as -1 by get_indexer and negative
                # indices are already converted to positive indices in the
                # above if-statement, so the negative flags are changed to
                # values outside the range of indices so as to trigger an
                # IndexError in maybe_convert_indices
                indexer[indexer < 0] = len(self)
                from pandas.core.indexing import maybe_convert_indices
                return maybe_convert_indices(indexer, len(self))

            elif not self.inferred_type == 'integer':
                keyarr = np.where(keyarr < 0, len(self) + keyarr, keyarr)
                return keyarr

        return None
Example #5
Source File: series.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def _take(self, indices, axis=0, is_copy=False):

        indices = _ensure_platform_int(indices)
        new_index = self.index.take(indices)

        if is_categorical_dtype(self):
            # https://github.com/pandas-dev/pandas/issues/20664
            # TODO: remove when the default Categorical.take behavior changes
            indices = maybe_convert_indices(indices, len(self._get_axis(axis)))
            kwargs = {'allow_fill': False}
        else:
            kwargs = {}
        new_values = self._values.take(indices, **kwargs)

        result = (self._constructor(new_values, index=new_index,
                                    fastpath=True).__finalize__(self))

        # Maybe set copy if we didn't actually change the index.
        if is_copy:
            if not result._get_axis(axis).equals(self._get_axis(axis)):
                result._set_is_copy(self)

        return result
Example #6
Source File: internals.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def take(self, indexer, axis=1, verify=True, convert=True):
        """
        Take items along any axis.
        """
        self._consolidate_inplace()
        indexer = (np.arange(indexer.start, indexer.stop, indexer.step,
                             dtype='int64')
                   if isinstance(indexer, slice)
                   else np.asanyarray(indexer, dtype='int64'))

        n = self.shape[axis]
        if convert:
            indexer = maybe_convert_indices(indexer, n)

        if verify:
            if ((indexer == -1) | (indexer >= n)).any():
                raise Exception('Indices must be nonzero and less than '
                                'the axis length')

        new_labels = self.axes[axis].take(indexer)
        return self.reindex_indexer(new_axis=new_labels, indexer=indexer,
                                    axis=axis, allow_dups=True)
Example #7
Source File: internals.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def take(self, indexer, axis=1, verify=True, convert=True):
        """
        Take items along any axis.
        """
        self._consolidate_inplace()
        indexer = (np.arange(indexer.start, indexer.stop, indexer.step,
                             dtype='int64')
                   if isinstance(indexer, slice)
                   else np.asanyarray(indexer, dtype='int64'))

        n = self.shape[axis]
        if convert:
            indexer = maybe_convert_indices(indexer, n)

        if verify:
            if ((indexer == -1) | (indexer >= n)).any():
                raise Exception('Indices must be nonzero and less than '
                                'the axis length')

        new_labels = self.axes[axis].take(indexer)
        return self.reindex_indexer(new_axis=new_labels, indexer=indexer,
                                    axis=axis, allow_dups=True)
Example #8
Source File: managers.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def take(self, indexer, axis=1, verify=True, convert=True):
        """
        Take items along any axis.
        """
        self._consolidate_inplace()
        indexer = (np.arange(indexer.start, indexer.stop, indexer.step,
                             dtype='int64')
                   if isinstance(indexer, slice)
                   else np.asanyarray(indexer, dtype='int64'))

        n = self.shape[axis]
        if convert:
            indexer = maybe_convert_indices(indexer, n)

        if verify:
            if ((indexer == -1) | (indexer >= n)).any():
                raise Exception('Indices must be nonzero and less than '
                                'the axis length')

        new_labels = self.axes[axis].take(indexer)
        return self.reindex_indexer(new_axis=new_labels, indexer=indexer,
                                    axis=axis, allow_dups=True)
Example #9
Source File: series.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def _take(self, indices, axis=0, convert=True, is_copy=False):
        if convert:
            indices = maybe_convert_indices(indices, len(self._get_axis(axis)))

        indices = _ensure_platform_int(indices)
        new_index = self.index.take(indices)
        new_values = self._values.take(indices)

        result = (self._constructor(new_values, index=new_index,
                                    fastpath=True).__finalize__(self))

        # Maybe set copy if we didn't actually change the index.
        if is_copy:
            if not result._get_axis(axis).equals(self._get_axis(axis)):
                result._set_is_copy(self)

        return result
Example #10
Source File: base.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def _convert_list_indexer(self, keyarr, kind=None):
        if (kind in [None, 'iloc', 'ix'] and
                is_integer_dtype(keyarr) and not self.is_floating() and
                not isinstance(keyarr, ABCPeriodIndex)):

            if self.inferred_type == 'mixed-integer':
                indexer = self.get_indexer(keyarr)
                if (indexer >= 0).all():
                    return indexer
                # missing values are flagged as -1 by get_indexer and negative
                # indices are already converted to positive indices in the
                # above if-statement, so the negative flags are changed to
                # values outside the range of indices so as to trigger an
                # IndexError in maybe_convert_indices
                indexer[indexer < 0] = len(self)
                from pandas.core.indexing import maybe_convert_indices
                return maybe_convert_indices(indexer, len(self))

            elif not self.inferred_type == 'integer':
                keyarr = np.where(keyarr < 0, len(self) + keyarr, keyarr)
                return keyarr

        return None
Example #11
Source File: series.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def _take(self, indices, axis=0, is_copy=False):

        indices = ensure_platform_int(indices)
        new_index = self.index.take(indices)

        if is_categorical_dtype(self):
            # https://github.com/pandas-dev/pandas/issues/20664
            # TODO: remove when the default Categorical.take behavior changes
            indices = maybe_convert_indices(indices, len(self._get_axis(axis)))
            kwargs = {'allow_fill': False}
        else:
            kwargs = {}
        new_values = self._values.take(indices, **kwargs)

        result = (self._constructor(new_values, index=new_index,
                                    fastpath=True).__finalize__(self))

        # Maybe set copy if we didn't actually change the index.
        if is_copy:
            if not result._get_axis(axis).equals(self._get_axis(axis)):
                result._set_is_copy(self)

        return result
Example #12
Source File: base.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up 
def _convert_list_indexer(self, keyarr, kind=None):
        if (kind in [None, 'iloc', 'ix'] and
                is_integer_dtype(keyarr) and not self.is_floating() and
                not isinstance(keyarr, ABCPeriodIndex)):

            if self.inferred_type == 'mixed-integer':
                indexer = self.get_indexer(keyarr)
                if (indexer >= 0).all():
                    return indexer
                # missing values are flagged as -1 by get_indexer and negative
                # indices are already converted to positive indices in the
                # above if-statement, so the negative flags are changed to
                # values outside the range of indices so as to trigger an
                # IndexError in maybe_convert_indices
                indexer[indexer < 0] = len(self)
                from pandas.core.indexing import maybe_convert_indices
                return maybe_convert_indices(indexer, len(self))

            elif not self.inferred_type == 'integer':
                keyarr = np.where(keyarr < 0, len(self) + keyarr, keyarr)
                return keyarr

        return None
Example #13
Source File: series.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up 
def _take(self, indices, axis=0, convert=True, is_copy=False):
        if convert:
            indices = maybe_convert_indices(indices, len(self._get_axis(axis)))

        indices = _ensure_platform_int(indices)
        new_index = self.index.take(indices)
        new_values = self._values.take(indices)

        result = (self._constructor(new_values, index=new_index,
                                    fastpath=True).__finalize__(self))

        # Maybe set copy if we didn't actually change the index.
        if is_copy:
            if not result._get_axis(axis).equals(self._get_axis(axis)):
                result._set_is_copy(self)

        return result
Example #14
Source File: internals.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up 
def take(self, indexer, axis=1, verify=True, convert=True):
        """
        Take items along any axis.
        """
        self._consolidate_inplace()
        indexer = (np.arange(indexer.start, indexer.stop, indexer.step,
                             dtype='int64')
                   if isinstance(indexer, slice)
                   else np.asanyarray(indexer, dtype='int64'))

        n = self.shape[axis]
        if convert:
            indexer = maybe_convert_indices(indexer, n)

        if verify:
            if ((indexer == -1) | (indexer >= n)).any():
                raise Exception('Indices must be nonzero and less than '
                                'the axis length')

        new_labels = self.axes[axis].take(indexer)
        return self.reindex_indexer(new_axis=new_labels, indexer=indexer,
                                    axis=axis, allow_dups=True)
Example #15
Source File: base.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def _convert_list_indexer(self, keyarr, kind=None):
        if (kind in [None, 'iloc', 'ix'] and
                is_integer_dtype(keyarr) and not self.is_floating() and
                not isinstance(keyarr, ABCPeriodIndex)):

            if self.inferred_type == 'mixed-integer':
                indexer = self.get_indexer(keyarr)
                if (indexer >= 0).all():
                    return indexer
                # missing values are flagged as -1 by get_indexer and negative
                # indices are already converted to positive indices in the
                # above if-statement, so the negative flags are changed to
                # values outside the range of indices so as to trigger an
                # IndexError in maybe_convert_indices
                indexer[indexer < 0] = len(self)
                from pandas.core.indexing import maybe_convert_indices
                return maybe_convert_indices(indexer, len(self))

            elif not self.inferred_type == 'integer':
                keyarr = np.where(keyarr < 0, len(self) + keyarr, keyarr)
                return keyarr

        return None
Example #16
Source File: internals.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def _preprocess_slice_or_indexer(slice_or_indexer, length, allow_fill):
    if isinstance(slice_or_indexer, slice):
        return 'slice', slice_or_indexer, lib.slice_len(slice_or_indexer,
                                                        length)
    elif (isinstance(slice_or_indexer, np.ndarray) and
          slice_or_indexer.dtype == np.bool_):
        return 'mask', slice_or_indexer, slice_or_indexer.sum()
    else:
        indexer = np.asanyarray(slice_or_indexer, dtype=np.int64)
        if not allow_fill:
            indexer = maybe_convert_indices(indexer, length)
        return 'fancy', indexer, len(indexer)
Example #17
Source File: internals.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up 
def _preprocess_slice_or_indexer(slice_or_indexer, length, allow_fill):
    if isinstance(slice_or_indexer, slice):
        return 'slice', slice_or_indexer, lib.slice_len(slice_or_indexer,
                                                        length)
    elif (isinstance(slice_or_indexer, np.ndarray) and
          slice_or_indexer.dtype == np.bool_):
        return 'mask', slice_or_indexer, slice_or_indexer.sum()
    else:
        indexer = np.asanyarray(slice_or_indexer, dtype=np.int64)
        if not allow_fill:
            indexer = maybe_convert_indices(indexer, length)
        return 'fancy', indexer, len(indexer)
Example #18
Source File: managers.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def _preprocess_slice_or_indexer(slice_or_indexer, length, allow_fill):
    if isinstance(slice_or_indexer, slice):
        return ('slice', slice_or_indexer,
                libinternals.slice_len(slice_or_indexer, length))
    elif (isinstance(slice_or_indexer, np.ndarray) and
          slice_or_indexer.dtype == np.bool_):
        return 'mask', slice_or_indexer, slice_or_indexer.sum()
    else:
        indexer = np.asanyarray(slice_or_indexer, dtype=np.int64)
        if not allow_fill:
            indexer = maybe_convert_indices(indexer, length)
        return 'fancy', indexer, len(indexer)
Example #19
Source File: internals.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def _preprocess_slice_or_indexer(slice_or_indexer, length, allow_fill):
    if isinstance(slice_or_indexer, slice):
        return ('slice', slice_or_indexer,
                libinternals.slice_len(slice_or_indexer, length))
    elif (isinstance(slice_or_indexer, np.ndarray) and
          slice_or_indexer.dtype == np.bool_):
        return 'mask', slice_or_indexer, slice_or_indexer.sum()
    else:
        indexer = np.asanyarray(slice_or_indexer, dtype=np.int64)
        if not allow_fill:
            indexer = maybe_convert_indices(indexer, length)
        return 'fancy', indexer, len(indexer)
Example #20
Source File: managers.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def _preprocess_slice_or_indexer(slice_or_indexer, length, allow_fill):
    if isinstance(slice_or_indexer, slice):
        return ('slice', slice_or_indexer,
                libinternals.slice_len(slice_or_indexer, length))
    elif (isinstance(slice_or_indexer, np.ndarray) and
          slice_or_indexer.dtype == np.bool_):
        return 'mask', slice_or_indexer, slice_or_indexer.sum()
    else:
        indexer = np.asanyarray(slice_or_indexer, dtype=np.int64)
        if not allow_fill:
            indexer = maybe_convert_indices(indexer, length)
        return 'fancy', indexer, len(indexer)