Python pandas.util._validators.validate_bool_kwarg() Examples

The following are 30 code examples of pandas.util._validators.validate_bool_kwarg(). 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.util._validators , or try the search function .
Example #1
Source File: blocks.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up
def _interpolate_with_fill(self, method='pad', axis=0, inplace=False,
                               limit=None, fill_value=None, coerce=False,
                               downcast=None):
        """ fillna but using the interpolate machinery """

        inplace = validate_bool_kwarg(inplace, 'inplace')

        # if we are coercing, then don't force the conversion
        # if the block can't hold the type
        if coerce:
            if not self._can_hold_na:
                if inplace:
                    return [self]
                else:
                    return [self.copy()]

        values = self.values if inplace else self.values.copy()
        values, fill_value = self._try_coerce_args(values, fill_value)
        values = missing.interpolate_2d(values, method=method, axis=axis,
                                        limit=limit, fill_value=fill_value,
                                        dtype=self.dtype)
        values = self._try_coerce_result(values)

        blocks = [self.make_block_same_class(values, ndim=self.ndim)]
        return self._maybe_downcast(blocks, downcast) 
Example #2
Source File: blocks.py    From recruit with Apache License 2.0 6 votes vote down vote up
def _interpolate_with_fill(self, method='pad', axis=0, inplace=False,
                               limit=None, fill_value=None, coerce=False,
                               downcast=None):
        """ fillna but using the interpolate machinery """

        inplace = validate_bool_kwarg(inplace, 'inplace')

        # if we are coercing, then don't force the conversion
        # if the block can't hold the type
        if coerce:
            if not self._can_hold_na:
                if inplace:
                    return [self]
                else:
                    return [self.copy()]

        values = self.values if inplace else self.values.copy()
        values, fill_value = self._try_coerce_args(values, fill_value)
        values = missing.interpolate_2d(values, method=method, axis=axis,
                                        limit=limit, fill_value=fill_value,
                                        dtype=self.dtype)
        values = self._try_coerce_result(values)

        blocks = [self.make_block_same_class(values, ndim=self.ndim)]
        return self._maybe_downcast(blocks, downcast) 
Example #3
Source File: series.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up
def _set_name(self, name, inplace=False):
        """
        Set the Series name.

        Parameters
        ----------
        name : str
        inplace : bool
            whether to modify `self` directly or return a copy
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        ser = self if inplace else self.copy()
        ser.name = name
        return ser

    # ----------------------------------------------------------------------
    # Statistics, overridden ndarray methods

    # TODO: integrate bottleneck 
Example #4
Source File: internals.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up
def _interpolate_with_fill(self, method='pad', axis=0, inplace=False,
                               limit=None, fill_value=None, coerce=False,
                               downcast=None, mgr=None):
        """ fillna but using the interpolate machinery """

        inplace = validate_bool_kwarg(inplace, 'inplace')

        # if we are coercing, then don't force the conversion
        # if the block can't hold the type
        if coerce:
            if not self._can_hold_na:
                if inplace:
                    return [self]
                else:
                    return [self.copy()]

        values = self.values if inplace else self.values.copy()
        values, _, fill_value, _ = self._try_coerce_args(values, fill_value)
        values = missing.interpolate_2d(values, method=method, axis=axis,
                                        limit=limit, fill_value=fill_value,
                                        dtype=self.dtype)
        values = self._try_coerce_result(values)

        blocks = [self.make_block(values, klass=self.__class__, fastpath=True)]
        return self._maybe_downcast(blocks, downcast) 
Example #5
Source File: categorical.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up
def set_ordered(self, value, inplace=False):
        """
        Sets the ordered attribute to the boolean value

        Parameters
        ----------
        value : boolean to set whether this categorical is ordered (True) or
           not (False)
        inplace : boolean (default: False)
           Whether or not to set the ordered attribute inplace or return a copy
           of this categorical with ordered set to the value
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        new_dtype = CategoricalDtype(self.categories, ordered=value)
        cat = self if inplace else self.copy()
        cat._dtype = new_dtype
        if not inplace:
            return cat 
Example #6
Source File: categorical.py    From recruit with Apache License 2.0 6 votes vote down vote up
def set_ordered(self, value, inplace=False):
        """
        Sets the ordered attribute to the boolean value

        Parameters
        ----------
        value : boolean to set whether this categorical is ordered (True) or
           not (False)
        inplace : boolean (default: False)
           Whether or not to set the ordered attribute inplace or return a copy
           of this categorical with ordered set to the value
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        new_dtype = CategoricalDtype(self.categories, ordered=value)
        cat = self if inplace else self.copy()
        cat._dtype = new_dtype
        if not inplace:
            return cat 
Example #7
Source File: series.py    From recruit with Apache License 2.0 6 votes vote down vote up
def _set_name(self, name, inplace=False):
        """
        Set the Series name.

        Parameters
        ----------
        name : str
        inplace : bool
            whether to modify `self` directly or return a copy
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        ser = self if inplace else self.copy()
        ser.name = name
        return ser

    # ----------------------------------------------------------------------
    # Statistics, overridden ndarray methods

    # TODO: integrate bottleneck 
Example #8
Source File: categorical.py    From vnpy_crypto with MIT License 6 votes vote down vote up
def set_ordered(self, value, inplace=False):
        """
        Sets the ordered attribute to the boolean value

        Parameters
        ----------
        value : boolean to set whether this categorical is ordered (True) or
           not (False)
        inplace : boolean (default: False)
           Whether or not to set the ordered attribute inplace or return a copy
           of this categorical with ordered set to the value
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        new_dtype = CategoricalDtype(self.categories, ordered=value)
        cat = self if inplace else self.copy()
        cat._dtype = new_dtype
        if not inplace:
            return cat 
Example #9
Source File: series.py    From vnpy_crypto with MIT License 6 votes vote down vote up
def _set_name(self, name, inplace=False):
        """
        Set the Series name.

        Parameters
        ----------
        name : str
        inplace : bool
            whether to modify `self` directly or return a copy
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        ser = self if inplace else self.copy()
        ser.name = name
        return ser

    # ----------------------------------------------------------------------
    # Statistics, overridden ndarray methods

    # TODO: integrate bottleneck 
Example #10
Source File: categorical.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up
def set_ordered(self, value, inplace=False):
        """
        Sets the ordered attribute to the boolean value

        Parameters
        ----------
        value : boolean to set whether this categorical is ordered (True) or
           not (False)
        inplace : boolean (default: False)
           Whether or not to set the ordered attribute inplace or return a copy
           of this categorical with ordered set to the value
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        new_dtype = CategoricalDtype(self.categories, ordered=value)
        cat = self if inplace else self.copy()
        cat._dtype = new_dtype
        if not inplace:
            return cat 
Example #11
Source File: categorical.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up
def set_ordered(self, value, inplace=False):
        """
        Sets the ordered attribute to the boolean value

        Parameters
        ----------
        value : boolean to set whether this categorical is ordered (True) or
           not (False)
        inplace : boolean (default: False)
           Whether or not to set the ordered attribute inplace or return a copy
           of this categorical with ordered set to the value
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        new_dtype = CategoricalDtype(self.categories, ordered=value)
        cat = self if inplace else self.copy()
        cat._dtype = new_dtype
        if not inplace:
            return cat 
Example #12
Source File: series.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up
def _set_name(self, name, inplace=False):
        """
        Set the Series name.

        Parameters
        ----------
        name : str
        inplace : bool
            whether to modify `self` directly or return a copy
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        ser = self if inplace else self.copy()
        ser.name = name
        return ser

    # ----------------------------------------------------------------------
    # Statistics, overridden ndarray methods

    # TODO: integrate bottleneck 
Example #13
Source File: internals.py    From vnpy_crypto with MIT License 6 votes vote down vote up
def _interpolate_with_fill(self, method='pad', axis=0, inplace=False,
                               limit=None, fill_value=None, coerce=False,
                               downcast=None, mgr=None):
        """ fillna but using the interpolate machinery """

        inplace = validate_bool_kwarg(inplace, 'inplace')

        # if we are coercing, then don't force the conversion
        # if the block can't hold the type
        if coerce:
            if not self._can_hold_na:
                if inplace:
                    return [self]
                else:
                    return [self.copy()]

        values = self.values if inplace else self.values.copy()
        values, _, fill_value, _ = self._try_coerce_args(values, fill_value)
        values = missing.interpolate_2d(values, method=method, axis=axis,
                                        limit=limit, fill_value=fill_value,
                                        dtype=self.dtype)
        values = self._try_coerce_result(values)

        blocks = [self.make_block_same_class(values, ndim=self.ndim)]
        return self._maybe_downcast(blocks, downcast) 
Example #14
Source File: series.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up
def _set_name(self, name, inplace=False):
        """
        Set the Series name.

        Parameters
        ----------
        name : str
        inplace : bool
            whether to modify `self` directly or return a copy
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        ser = self if inplace else self.copy()
        ser.name = name
        return ser

    # ----------------------------------------------------------------------
    # Statistics, overridden ndarray methods

    # TODO: integrate bottleneck 
Example #15
Source File: internals.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up
def _interpolate_with_fill(self, method='pad', axis=0, inplace=False,
                               limit=None, fill_value=None, coerce=False,
                               downcast=None, mgr=None):
        """ fillna but using the interpolate machinery """

        inplace = validate_bool_kwarg(inplace, 'inplace')

        # if we are coercing, then don't force the conversion
        # if the block can't hold the type
        if coerce:
            if not self._can_hold_na:
                if inplace:
                    return [self]
                else:
                    return [self.copy()]

        values = self.values if inplace else self.values.copy()
        values, _, fill_value, _ = self._try_coerce_args(values, fill_value)
        values = missing.interpolate_2d(values, method=method, axis=axis,
                                        limit=limit, fill_value=fill_value,
                                        dtype=self.dtype)
        values = self._try_coerce_result(values)

        blocks = [self.make_block(values, klass=self.__class__, fastpath=True)]
        return self._maybe_downcast(blocks, downcast) 
Example #16
Source File: blocks.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up
def replace(self, to_replace, value, inplace=False, filter=None,
                regex=False, convert=True):
        inplace = validate_bool_kwarg(inplace, 'inplace')
        to_replace_values = np.atleast_1d(to_replace)
        if not np.can_cast(to_replace_values, bool):
            return self
        return super(BoolBlock, self).replace(to_replace, value,
                                              inplace=inplace, filter=filter,
                                              regex=regex, convert=convert) 
Example #17
Source File: blocks.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up
def putmask(self, mask, new, align=True, inplace=False, axis=0,
                transpose=False):
        """
        putmask the data to the block; we must be a single block and not
        generate other blocks

        return the resulting block

        Parameters
        ----------
        mask  : the condition to respect
        new : a ndarray/object
        align : boolean, perform alignment on other/cond, default is True
        inplace : perform inplace modification, default is False

        Returns
        -------
        a new block, the result of the putmask
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')

        # use block's copy logic.
        # .values may be an Index which does shallow copy by default
        new_values = self.values if inplace else self.copy().values
        new_values, new = self._try_coerce_args(new_values, new)

        if isinstance(new, np.ndarray) and len(new) == len(mask):
            new = new[mask]

        mask = _safe_reshape(mask, new_values.shape)

        new_values[mask] = new
        new_values = self._try_coerce_result(new_values)
        return [self.make_block(values=new_values)] 
Example #18
Source File: categorical.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up
def as_ordered(self, inplace=False):
        """
        Sets the Categorical to be ordered

        Parameters
        ----------
        inplace : boolean (default: False)
           Whether or not to set the ordered attribute inplace or return a copy
           of this categorical with ordered set to True
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        return self.set_ordered(True, inplace=inplace) 
Example #19
Source File: categorical.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up
def as_unordered(self, inplace=False):
        """
        Set the Categorical to be unordered.

        Parameters
        ----------
        inplace : boolean (default: False)
           Whether or not to set the ordered attribute inplace or return a copy
           of this categorical with ordered set to False
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        return self.set_ordered(False, inplace=inplace) 
Example #20
Source File: categorical.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up
def remove_unused_categories(self, inplace=False):
        """
        Removes categories which are not used.

        Parameters
        ----------
        inplace : boolean (default: False)
           Whether or not to drop unused categories inplace or return a copy of
           this categorical with unused categories dropped.

        Returns
        -------
        cat : Categorical with unused categories dropped or None if inplace.

        See Also
        --------
        rename_categories
        reorder_categories
        add_categories
        remove_categories
        set_categories
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        cat = self if inplace else self.copy()
        idx, inv = np.unique(cat._codes, return_inverse=True)

        if idx.size != 0 and idx[0] == -1:  # na sentinel
            idx, inv = idx[1:], inv - 1

        new_categories = cat.dtype.categories.take(idx)
        new_dtype = CategoricalDtype._from_fastpath(new_categories,
                                                    ordered=self.ordered)
        cat._dtype = new_dtype
        cat._codes = coerce_indexer_dtype(inv, new_dtype.categories)

        if not inplace:
            return cat 
Example #21
Source File: blocks.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up
def _interpolate(self, method=None, index=None, values=None,
                     fill_value=None, axis=0, limit=None,
                     limit_direction='forward', limit_area=None,
                     inplace=False, downcast=None, **kwargs):
        """ interpolate using scipy wrappers """

        inplace = validate_bool_kwarg(inplace, 'inplace')
        data = self.values if inplace else self.values.copy()

        # only deal with floats
        if not self.is_float:
            if not self.is_integer:
                return self
            data = data.astype(np.float64)

        if fill_value is None:
            fill_value = self.fill_value

        if method in ('krogh', 'piecewise_polynomial', 'pchip'):
            if not index.is_monotonic:
                raise ValueError("{0} interpolation requires that the "
                                 "index be monotonic.".format(method))
        # process 1-d slices in the axis direction

        def func(x):

            # process a 1-d slice, returning it
            # should the axis argument be handled below in apply_along_axis?
            # i.e. not an arg to missing.interpolate_1d
            return missing.interpolate_1d(index, x, method=method, limit=limit,
                                          limit_direction=limit_direction,
                                          limit_area=limit_area,
                                          fill_value=fill_value,
                                          bounds_error=False, **kwargs)

        # interp each column independently
        interp_values = np.apply_along_axis(func, axis, data)

        blocks = [self.make_block_same_class(interp_values)]
        return self._maybe_downcast(blocks, downcast) 
Example #22
Source File: list.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up
def consolidate(self, inplace=True):
        """
        Internally consolidate chunks of data

        Parameters
        ----------
        inplace : boolean, default True
            Modify the calling object instead of constructing a new one

        Returns
        -------
        splist : SparseList
            If inplace=False, new object, otherwise reference to existing
            object
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        if not inplace:
            result = self.copy()
        else:
            result = self

        if result.is_consolidated:
            return result

        result._consolidate_inplace()
        return result 
Example #23
Source File: test_validate_kwargs.py    From recruit with Apache License 2.0 5 votes vote down vote up
def test_validate_bool_kwarg_fail(name, value):
    msg = ("For argument \"%s\" expected type bool, received type %s" %
           (name, type(value).__name__))

    with pytest.raises(ValueError, match=msg):
        validate_bool_kwarg(value, name) 
Example #24
Source File: internals.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up
def replace(self, to_replace, value, inplace=False, filter=None,
                regex=False, convert=True, mgr=None):
        inplace = validate_bool_kwarg(inplace, 'inplace')
        to_replace_values = np.atleast_1d(to_replace)
        if not np.can_cast(to_replace_values, bool):
            return self
        return super(BoolBlock, self).replace(to_replace, value,
                                              inplace=inplace, filter=filter,
                                              regex=regex, convert=convert,
                                              mgr=mgr) 
Example #25
Source File: internals.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up
def _interpolate(self, method=None, index=None, values=None,
                     fill_value=None, axis=0, limit=None,
                     limit_direction='forward', inplace=False, downcast=None,
                     mgr=None, **kwargs):
        """ interpolate using scipy wrappers """

        inplace = validate_bool_kwarg(inplace, 'inplace')
        data = self.values if inplace else self.values.copy()

        # only deal with floats
        if not self.is_float:
            if not self.is_integer:
                return self
            data = data.astype(np.float64)

        if fill_value is None:
            fill_value = self.fill_value

        if method in ('krogh', 'piecewise_polynomial', 'pchip'):
            if not index.is_monotonic:
                raise ValueError("{0} interpolation requires that the "
                                 "index be monotonic.".format(method))
        # process 1-d slices in the axis direction

        def func(x):

            # process a 1-d slice, returning it
            # should the axis argument be handled below in apply_along_axis?
            # i.e. not an arg to missing.interpolate_1d
            return missing.interpolate_1d(index, x, method=method, limit=limit,
                                          limit_direction=limit_direction,
                                          fill_value=fill_value,
                                          bounds_error=False, **kwargs)

        # interp each column independently
        interp_values = np.apply_along_axis(func, axis, data)

        blocks = [self.make_block(interp_values, klass=self.__class__,
                                  fastpath=True)]
        return self._maybe_downcast(blocks, downcast) 
Example #26
Source File: categorical.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up
def remove_unused_categories(self, inplace=False):
        """ Removes categories which are not used.

        Parameters
        ----------
        inplace : boolean (default: False)
           Whether or not to drop unused categories inplace or return a copy of
           this categorical with unused categories dropped.

        Returns
        -------
        cat : Categorical with unused categories dropped or None if inplace.

        See also
        --------
        rename_categories
        reorder_categories
        add_categories
        remove_categories
        set_categories
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        cat = self if inplace else self.copy()
        idx, inv = np.unique(cat._codes, return_inverse=True)

        if idx.size != 0 and idx[0] == -1:  # na sentinel
            idx, inv = idx[1:], inv - 1

        new_categories = cat.dtype.categories.take(idx)
        new_dtype = CategoricalDtype._from_fastpath(new_categories,
                                                    ordered=self.ordered)
        cat._dtype = new_dtype
        cat._codes = coerce_indexer_dtype(inv, new_dtype.categories)

        if not inplace:
            return cat 
Example #27
Source File: internals.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up
def replace(self, to_replace, value, inplace=False, filter=None,
                regex=False, convert=True, mgr=None):
        """ replace the to_replace value with value, possible to create new
        blocks here this is just a call to putmask. regex is not used here.
        It is used in ObjectBlocks.  It is here for API
        compatibility.
        """

        inplace = validate_bool_kwarg(inplace, 'inplace')
        original_to_replace = to_replace

        # try to replace, if we raise an error, convert to ObjectBlock and
        # retry
        try:
            values, _, to_replace, _ = self._try_coerce_args(self.values,
                                                             to_replace)
            mask = missing.mask_missing(values, to_replace)
            if filter is not None:
                filtered_out = ~self.mgr_locs.isin(filter)
                mask[filtered_out.nonzero()[0]] = False

            blocks = self.putmask(mask, value, inplace=inplace)
            if convert:
                blocks = [b.convert(by_item=True, numeric=False,
                                    copy=not inplace) for b in blocks]
            return blocks
        except (TypeError, ValueError):

            # try again with a compatible block
            block = self.astype(object)
            return block.replace(
                to_replace=original_to_replace, value=value, inplace=inplace,
                filter=filter, regex=regex, convert=convert) 
Example #28
Source File: categorical.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up
def as_unordered(self, inplace=False):
        """
        Sets the Categorical to be unordered

        Parameters
        ----------
        inplace : boolean (default: False)
           Whether or not to set the ordered attribute inplace or return a copy
           of this categorical with ordered set to False
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        return self.set_ordered(False, inplace=inplace) 
Example #29
Source File: categorical.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up
def as_ordered(self, inplace=False):
        """
        Sets the Categorical to be ordered

        Parameters
        ----------
        inplace : boolean (default: False)
           Whether or not to set the ordered attribute inplace or return a copy
           of this categorical with ordered set to True
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        return self.set_ordered(True, inplace=inplace) 
Example #30
Source File: list.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up
def consolidate(self, inplace=True):
        """
        Internally consolidate chunks of data

        Parameters
        ----------
        inplace : boolean, default True
            Modify the calling object instead of constructing a new one

        Returns
        -------
        splist : SparseList
            If inplace=False, new object, otherwise reference to existing
            object
        """
        inplace = validate_bool_kwarg(inplace, 'inplace')
        if not inplace:
            result = self.copy()
        else:
            result = self

        if result.is_consolidated:
            return result

        result._consolidate_inplace()
        return result