Python indexing._maybe_numeric_slice方法代码示例

# 需要导入模块: from pandas.core import indexing [as 别名]
# 或者: from pandas.core.indexing import _maybe_numeric_slice [as 别名]
def _highlight_handler(self, subset=None, color='yellow', axis=None,
                           max_=True):
        subset = _non_reducing_slice(_maybe_numeric_slice(self.data, subset))
        self.apply(self._highlight_extrema, color=color, axis=axis,
                   subset=subset, max_=max_)
        return self 

# 需要导入模块: from pandas.core import indexing [as 别名]
# 或者: from pandas.core.indexing import _maybe_numeric_slice [as 别名]
def background_gradient(self, cmap='PuBu', low=0, high=0, axis=0,
                            subset=None):
        """
        Color the background in a gradient according to
        the data in each column (optionally row).
        Requires matplotlib.

        Parameters
        ----------
        cmap: str or colormap
            matplotlib colormap
        low, high: float
            compress the range by these values.
        axis: int or str
            1 or 'columns' for columnwise, 0 or 'index' for rowwise
        subset: IndexSlice
            a valid slice for ``data`` to limit the style application to

        Returns
        -------
        self : Styler

        Notes
        -----
        Tune ``low`` and ``high`` to keep the text legible by
        not using the entire range of the color map. These extend
        the range of the data by ``low * (x.max() - x.min())``
        and ``high * (x.max() - x.min())`` before normalizing.
        """
        subset = _maybe_numeric_slice(self.data, subset)
        subset = _non_reducing_slice(subset)
        self.apply(self._background_gradient, cmap=cmap, subset=subset,
                   axis=axis, low=low, high=high)
        return self 

# 需要导入模块: from pandas.core import indexing [as 别名]
# 或者: from pandas.core.indexing import _maybe_numeric_slice [as 别名]
def background_gradient(self, cmap='PuBu', low=0, high=0, axis=0,
                            subset=None):
        """
        Color the background in a gradient according to
        the data in each column (optionally row).
        Requires matplotlib.

        .. versionadded:: 0.17.1

        Parameters
        ----------
        cmap: str or colormap
            matplotlib colormap
        low, high: float
            compress the range by these values.
        axis: int or str
            1 or 'columns' for columnwise, 0 or 'index' for rowwise
        subset: IndexSlice
            a valid slice for ``data`` to limit the style application to

        Returns
        -------
        self : Styler

        Notes
        -----
        Tune ``low`` and ``high`` to keep the text legible by
        not using the entire range of the color map. These extend
        the range of the data by ``low * (x.max() - x.min())``
        and ``high * (x.max() - x.min())`` before normalizing.
        """
        subset = _maybe_numeric_slice(self.data, subset)
        subset = _non_reducing_slice(subset)
        self.apply(self._background_gradient, cmap=cmap, subset=subset,
                   axis=axis, low=low, high=high)
        return self 

# 需要导入模块: from pandas.core import indexing [as 别名]
# 或者: from pandas.core.indexing import _maybe_numeric_slice [as 别名]
def test_maybe_numeric_slice(self):
        df = pd.DataFrame({'A': [1, 2], 'B': ['c', 'd'], 'C': [True, False]})
        result = _maybe_numeric_slice(df, slice_=None)
        expected = pd.IndexSlice[:, ['A']]
        assert result == expected

        result = _maybe_numeric_slice(df, None, include_bool=True)
        expected = pd.IndexSlice[:, ['A', 'C']]
        result = _maybe_numeric_slice(df, [1])
        expected = [1]
        assert result == expected 

# 需要导入模块: from pandas.core import indexing [as 别名]
# 或者: from pandas.core.indexing import _maybe_numeric_slice [as 别名]
def background_gradient(self, cmap='PuBu', low=0, high=0, axis=0,
                            subset=None, text_color_threshold=0.408):
        """
        Color the background in a gradient according to
        the data in each column (optionally row).

        Requires matplotlib.

        Parameters
        ----------
        cmap : str or colormap
            matplotlib colormap
        low, high : float
            compress the range by these values.
        axis : int or str
            1 or 'columns' for columnwise, 0 or 'index' for rowwise
        subset : IndexSlice
            a valid slice for ``data`` to limit the style application to
        text_color_threshold : float or int
            luminance threshold for determining text color. Facilitates text
            visibility across varying background colors. From 0 to 1.
            0 = all text is dark colored, 1 = all text is light colored.

            .. versionadded:: 0.24.0

        Returns
        -------
        self : Styler

        Raises
        ------
        ValueError
            If ``text_color_threshold`` is not a value from 0 to 1.

        Notes
        -----
        Set ``text_color_threshold`` or tune ``low`` and ``high`` to keep the
        text legible by not using the entire range of the color map. The range
        of the data is extended by ``low * (x.max() - x.min())`` and ``high *
        (x.max() - x.min())`` before normalizing.
        """
        subset = _maybe_numeric_slice(self.data, subset)
        subset = _non_reducing_slice(subset)
        self.apply(self._background_gradient, cmap=cmap, subset=subset,
                   axis=axis, low=low, high=high,
                   text_color_threshold=text_color_threshold)
        return self 

# 需要导入模块: from pandas.core import indexing [as 别名]
# 或者: from pandas.core.indexing import _maybe_numeric_slice [as 别名]
def bar(self, subset=None, axis=0, color='#d65f5f', width=100,
            align='left'):
        """
        Color the background ``color`` proptional to the values in each column.
        Excludes non-numeric data by default.

        Parameters
        ----------
        subset: IndexSlice, default None
            a valid slice for ``data`` to limit the style application to
        axis: int
        color: str or 2-tuple/list
            If a str is passed, the color is the same for both
            negative and positive numbers. If 2-tuple/list is used, the
            first element is the color_negative and the second is the
            color_positive (eg: ['#d65f5f', '#5fba7d'])
        width: float
            A number between 0 or 100. The largest value will cover ``width``
            percent of the cell's width
        align : {'left', 'zero',' mid'}, default 'left'
            - 'left' : the min value starts at the left of the cell
            - 'zero' : a value of zero is located at the center of the cell
            - 'mid' : the center of the cell is at (max-min)/2, or
              if values are all negative (positive) the zero is aligned
              at the right (left) of the cell

              .. versionadded:: 0.20.0

        Returns
        -------
        self : Styler
        """
        subset = _maybe_numeric_slice(self.data, subset)
        subset = _non_reducing_slice(subset)

        base = 'width: 10em; height: 80%;'

        if not(is_list_like(color)):
            color = [color, color]
        elif len(color) == 1:
            color = [color[0], color[0]]
        elif len(color) > 2:
            msg = ("Must pass `color` as string or a list-like"
                   " of length 2: [`color_negative`, `color_positive`]\n"
                   "(eg: color=['#d65f5f', '#5fba7d'])")
            raise ValueError(msg)

        if align == 'left':
            self.apply(self._bar_left, subset=subset, axis=axis, color=color,
                       width=width, base=base)
        elif align == 'zero':
            self.apply(self._bar_center_zero, subset=subset, axis=axis,
                       color=color, width=width, base=base)
        elif align == 'mid':
            self.apply(self._bar_center_mid, subset=subset, axis=axis,
                       color=color, width=width, base=base)
        else:
            msg = ("`align` must be one of {'left', 'zero',' mid'}")
            raise ValueError(msg)

        return self