ign``, which is "r".
            If a naive option is given renders without multicol.
            Pipe decorators can also be added to non-naive values to draw vertical
            rules, e.g. "\|r" will draw a rule on the left side of right aligned merged
            cells.

            .. versionchanged:: 1.4.0
        siunitx : bool, default False
            Set to ``True`` to structure LaTeX compatible with the {siunitx} package.
        environment : str, optional
            If given, the environment that will replace 'table' in ``\\begin{table}``.
            If 'longtable' is specified then a more suitable template is
            rendered. If not given defaults to
            ``pandas.options.styler.latex.environment``, which is `None`.

            .. versionadded:: 1.4.0
        encoding : str, optional
            Character encoding setting. Defaults
            to ``pandas.options.styler.render.encoding``, which is "utf-8".
        convert_css : bool, default False
            Convert simple cell-styles from CSS to LaTeX format. Any CSS not found in
            conversion table is dropped. A style can be forced by adding option
            `--latex`. See notes.

        Returns
        -------
        str or None
            If `buf` is None, returns the result as a string. Otherwise returns `None`.

        See Also
        --------
        Styler.format: Format the text display value of cells.

        Notes
        -----
        **Latex Packages**

        For the following features we recommend the following LaTeX inclusions:

        ===================== ==========================================================
        Feature               Inclusion
        ===================== ==========================================================
        sparse columns        none: included within default {tabular} environment
        sparse rows           \\usepackage{multirow}
        hrules                \\usepackage{booktabs}
        colors                \\usepackage[table]{xcolor}
        siunitx               \\usepackage{siunitx}
        bold (with siunitx)   | \\usepackage{etoolbox}
                              | \\robustify\\bfseries
                              | \\sisetup{detect-all = true}  *(within {document})*
        italic (with siunitx) | \\usepackage{etoolbox}
                              | \\robustify\\itshape
                              | \\sisetup{detect-all = true}  *(within {document})*
        environment           \\usepackage{longtable} if arg is "longtable"
                              | or any other relevant environment package
        hyperlinks            \\usepackage{hyperref}
        ===================== ==========================================================

        **Cell Styles**

        LaTeX styling can only be rendered if the accompanying styling functions have
        been constructed with appropriate LaTeX commands. All styling
        functionality is built around the concept of a CSS ``(<attribute>, <value>)``
        pair (see `Table Visualization <../../user_guide/style.ipynb>`_), and this
        should be replaced by a LaTeX
        ``(<command>, <options>)`` approach. Each cell will be styled individually
        using nested LaTeX commands with their accompanied options.

        For example the following code will highlight and bold a cell in HTML-CSS:

        >>> df = pd.DataFrame([[1,2], [3,4]])
        >>> s = df.style.highlight_max(axis=None,
        ...                            props='background-color:red; font-weight:bold;')
        >>> s.to_html()  # doctest: +SKIP

        The equivalent using LaTeX only commands is the following:

        >>> s = df.style.highlight_max(axis=None,
        ...                            props='cellcolor:{red}; bfseries: ;')
        >>> s.to_latex()  # doctest: +SKIP

        Internally these structured LaTeX ``(<command>, <options>)`` pairs
        are translated to the
        ``display_value`` with the default structure:
        ``\<command><options> <display_value>``.
        Where there are multiple commands the latter is nested recursively, so that
        the above example highlighted cell is rendered as
        ``\cellcolor{red} \bfseries 4``.

        Occasionally this format does not suit the applied command, or
        combination of LaTeX packages that is in use, so additional flags can be
        added to the ``<options>``, within the tuple, to result in different
        positions of required braces (the **default** being the same as ``--nowrap``):

        =================================== ============================================
        Tuple Format                           Output Structure
        =================================== ============================================
        (<command>,<options>)               \\<command><options> <display_value>
        (<command>,<options> ``--nowrap``)  \\<command><options> <display_value>
        (<command>,<options> ``--rwrap``)   \\<command><options>{<display_value>}
        (<command>,<options> ``--wrap``)    {\\<command><options> <display_value>}
        (<command>,<options> ``--lwrap``)   {\\<command><options>} <display_value>
        (<command>,<options> ``--dwrap``)   {\\<command><options>}{<display_value>}
        =================================== ============================================

        For example the `textbf` command for font-weight
        should always be used with `--rwrap` so ``('textbf', '--rwrap')`` will render a
        working cell, wrapped with braces, as ``\textbf{<display_value>}``.

        A more comprehensive example is as follows:

        >>> df = pd.DataFrame([[1, 2.2, "dogs"], [3, 4.4, "cats"], [2, 6.6, "cows"]],
        ...                   index=["ix1", "ix2", "ix3"],
        ...                   columns=["Integers", "Floats", "Strings"])
        >>> s = df.style.highlight_max(
        ...     props='cellcolor:[HTML]{FFFF00}; color:{red};'
        ...           'textit:--rwrap; textbf:--rwrap;'
        ... )
        >>> s.to_latex()  # doctest: +SKIP

        .. figure:: ../../_static/style/latex_1.png

        **Table Styles**

        Internally Styler uses its ``table_styles`` object to parse the
        ``column_format``, ``position``, ``position_float``, and ``label``
        input arguments. These arguments are added to table styles in the format:

        .. code-block:: python

            set_table_styles([
                {"selector": "column_format", "props": f":{column_format};"},
                {"selector": "position", "props": f":{position};"},
                {"selector": "position_float", "props": f":{position_float};"},
                {"selector": "label", "props": f":{{{label.replace(':','§')}}};"}
            ], overwrite=False)

        Exception is made for the ``hrules`` argument which, in fact, controls all three
        commands: ``toprule``, ``bottomrule`` and ``midrule`` simultaneously. Instead of
        setting ``hrules`` to ``True``, it is also possible to set each
        individual rule definition, by manually setting the ``table_styles``,
        for example below we set a regular ``toprule``, set an ``hline`` for
        ``bottomrule`` and exclude the ``midrule``:

        .. code-block:: python

            set_table_styles([
                {'selector': 'toprule', 'props': ':toprule;'},
                {'selector': 'bottomrule', 'props': ':hline;'},
            ], overwrite=False)

        If other ``commands`` are added to table styles they will be detected, and
        positioned immediately above the '\\begin{tabular}' command. For example to
        add odd and even row coloring, from the {colortbl} package, in format
        ``\rowcolors{1}{pink}{red}``, use:

        .. code-block:: python

            set_table_styles([
                {'selector': 'rowcolors', 'props': ':{1}{pink}{red};'}
            ], overwrite=False)

        A more comprehensive example using these arguments is as follows:

        >>> df.columns = pd.MultiIndex.from_tuples([
        ...     ("Numeric", "Integers"),
        ...     ("Numeric", "Floats"),
        ...     ("Non-Numeric", "Strings")
        ... ])
        >>> df.index = pd.MultiIndex.from_tuples([
        ...     ("L0", "ix1"), ("L0", "ix2"), ("L1", "ix3")
        ... ])
        >>> s = df.style.highlight_max(
        ...     props='cellcolor:[HTML]{FFFF00}; color:{red}; itshape:; bfseries:;'
        ... )
        >>> s.to_latex(
        ...     column_format="rrrrr", position="h", position_float="centering",
        ...     hrules=True, label="table:5", caption="Styled LaTeX Table",
        ...     multirow_align="t", multicol_align="r"
        ... )  # doctest: +SKIP

        .. figure:: ../../_static/style/latex_2.png

        **Formatting**

        To format values :meth:`Styler.format` should be used prior to calling
        `Styler.to_latex`, as well as other methods such as :meth:`Styler.hide`
        for example:

        >>> s.clear()
        >>> s.table_styles = []
        >>> s.caption = None
        >>> s.format({
        ...    ("Numeric", "Integers"): '\${}',
        ...    ("Numeric", "Floats"): '{:.3f}',
        ...    ("Non-Numeric", "Strings"): str.upper
        ... })  # doctest: +SKIP
                        Numeric      Non-Numeric
                  Integers   Floats    Strings
        L0    ix1       $1   2.200      DOGS
              ix2       $3   4.400      CATS
        L1    ix3       $2   6.600      COWS

        >>> s.to_latex()  # doctest: +SKIP
        \begin{tabular}{llrrl}
        {} & {} & \multicolumn{2}{r}{Numeric} & {Non-Numeric} \\
        {} & {} & {Integers} & {Floats} & {Strings} \\
        \multirow[c]{2}{*}{L0} & ix1 & \\$1 & 2.200 & DOGS \\
         & ix2 & \$3 & 4.400 & CATS \\
        L1 & ix3 & \$2 & 6.600 & COWS \\
        \end{tabular}

        **CSS Conversion**

        This method can convert a Styler constructured with HTML-CSS to LaTeX using
        the following limited conversions.

        ================== ==================== ============= ==========================
        CSS Attribute      CSS value            LaTeX Command LaTeX Options
        ================== ==================== ============= ==========================
        font-weight        | bold               | bfseries
                           | bolder             | bfseries
        font-style         | italic             | itshape
                           | oblique            | slshape
        background-color   | red                cellcolor     | {red}--lwrap
                           | #fe01ea                          | [HTML]{FE01EA}--lwrap
                           | #f0e                             | [HTML]{FF00EE}--lwrap
                           | rgb(128,255,0)                   | [rgb]{0.5,1,0}--lwrap
                           | rgba(128,0,0,0.5)                | [rgb]{0.5,0,0}--lwrap
                           | rgb(25%,255,50%)                 | [rgb]{0.25,1,0.5}--lwrap
        color              | red                color         | {red}
                           | #fe01ea                          | [HTML]{FE01EA}
                           | #f0e                             | [HTML]{FF00EE}
                           | rgb(128,255,0)                   | [rgb]{0.5,1,0}
                           | rgba(128,0,0,0.5)                | [rgb]{0.5,0,0}
                           | rgb(25%,255,50%)                 | [rgb]{0.25,1,0.5}
        ================== ==================== ============= ==========================

        It is also possible to add user-defined LaTeX only styles to a HTML-CSS Styler
        using the ``--latex`` flag, and to add LaTeX parsing options that the
        converter will detect within a CSS-comment.

        >>> df = pd.DataFrame([[1]])
        >>> df.style.set_properties(
        ...     **{"font-weight": "bold /* --dwrap */", "Huge": "--latex--rwrap"}
        ... ).to_latex(convert_css=True)  # doctest: +SKIP
        \begin{tabular}{lr}
        {} & {0} \\
        0 & {\bfseries}{\Huge{1}} \\
        \end{tabular}

        Examples
        --------
        Below we give a complete step by step example adding some advanced features
        and noting some common gotchas.

        First we create the DataFrame and Styler as usual, including MultiIndex rows
        and columns, which allow for more advanced formatting options:

        >>> cidx = pd.MultiIndex.from_arrays([
        ...     ["Equity", "Equity", "Equity", "Equity",
        ...      "Stats", "Stats", "Stats", "Stats", "Rating"],
        ...     ["Energy", "Energy", "Consumer", "Consumer", "", "", "", "", ""],
        ...     ["BP", "Shell", "H&M", "Unilever",
        ...      "Std Dev", "Variance", "52w High", "52w Low", ""]
        ... ])
        >>> iidx = pd.MultiIndex.from_arrays([
        ...     ["Equity", "Equity", "Equity", "Equity"],
        ...     ["Energy", "Energy", "Consumer", "Consumer"],
        ...     ["BP", "Shell", "H&M", "Unilever"]
        ... ])
        >>> styler = pd.DataFrame([
        ...     [1, 0.8, 0.66, 0.72, 32.1678, 32.1678**2, 335.12, 240.89, "Buy"],
        ...     [0.8, 1.0, 0.69, 0.79, 1.876, 1.876**2, 14.12, 19.78, "Hold"],
        ...     [0.66, 0.69, 1.0, 0.86, 7, 7**2, 210.9, 140.6, "Buy"],
        ...     [0.72, 0.79, 0.86, 1.0, 213.76, 213.76**2, 2807, 3678, "Sell"],
        ... ], columns=cidx, index=iidx).style

        Second we will format the display and, since our table is quite wide, will
        hide the repeated level-0 of the index:

        >>> (styler.format(subset="Equity", precision=2)
        ...       .format(subset="Stats", precision=1, thousands=",")
        ...       .format(subset="Rating", formatter=str.upper)
        ...       .format_index(escape="latex", axis=1)
        ...       .format_index(escape="latex", axis=0)
        ...       .hide(level=0, axis=0))  # doctest: +SKIP

        Note that one of the string entries of the index and column headers is "H&M".
        Without applying the `escape="latex"` option to the `format_index` method the
        resultant LaTeX will fail to render, and the error returned is quite
        difficult to debug. Using the appropriate escape the "&" is converted to "\\&".

        Thirdly we will apply some (CSS-HTML) styles to our object. We will use a
        builtin method and also define our own method to highlight the stock
        recommendation:

        >>> def rating_color(v):
        ...     if v == "Buy": color = "#33ff85"
        ...     elif v == "Sell": color = "#ff5933"
        ...     else: color = "#ffdd33"
        ...     return f"color: {color}; font-weight: bold;"
        >>> (styler.background_gradient(cmap="inferno", subset="Equity", vmin=0, vmax=1)
        ...       .map(rating_color, subset="Rating"))  # doctest: +SKIP

        All the above styles will work with HTML (see below) and LaTeX upon conversion:

        .. figure:: ../../_static/style/latex_stocks_html.png

        However, we finally want to add one LaTeX only style
        (from the {graphicx} package), that is not easy to convert from CSS and
        pandas does not support it. Notice the `--latex` flag used here,
        as well as `--rwrap` to ensure this is formatted correctly and
        not ignored upon conversion.

        >>> styler.map_index(
        ...     lambda v: "rotatebox:{45}--rwrap--latex;", level=2, axis=1
        ... )  # doctest: +SKIP

        Finally we render our LaTeX adding in other options as required:

        >>> styler.to_latex(
        ...     caption="Selected stock correlation and simple statistics.",
        ...     clines="skip-last;data",
        ...     convert_css=True,
        ...     position_float="centering",
        ...     multicol_align="|c|",
        ...     hrules=True,
        ... )  # doctest: +SKIP
        \begin{table}
        \centering
        \caption{Selected stock correlation and simple statistics.}
        \begin{tabular}{llrrrrrrrrl}
        \toprule
         &  & \multicolumn{4}{|c|}{Equity} & \multicolumn{4}{|c|}{Stats} & Rating \\
         &  & \multicolumn{2}{|c|}{Energy} & \multicolumn{2}{|c|}{Consumer} &
        \multicolumn{4}{|c|}{} &  \\
         &  & \rotatebox{45}{BP} & \rotatebox{45}{Shell} & \rotatebox{45}{H\&M} &
        \rotatebox{45}{Unilever} & \rotatebox{45}{Std Dev} & \rotatebox{45}{Variance} &
        \rotatebox{45}{52w High} & \rotatebox{45}{52w Low} & \rotatebox{45}{} \\
        \midrule
        \multirow[c]{2}{*}{Energy} & BP & {\cellcolor[HTML]{FCFFA4}}
        \color[HTML]{000000} 1.00 & {\cellcolor[HTML]{FCA50A}} \color[HTML]{000000}
        0.80 & {\cellcolor[HTML]{EB6628}} \color[HTML]{F1F1F1} 0.66 &
        {\cellcolor[HTML]{F68013}} \color[HTML]{F1F1F1} 0.72 & 32.2 & 1,034.8 & 335.1
        & 240.9 & \color[HTML]{33FF85} \bfseries BUY \\
         & Shell & {\cellcolor[HTML]{FCA50A}} \color[HTML]{000000} 0.80 &
        {\cellcolor[HTML]{FCFFA4}} \color[HTML]{000000} 1.00 &
        {\cellcolor[HTML]{F1731D}} \color[HTML]{F1F1F1} 0.69 &
        {\cellcolor[HTML]{FCA108}} \color[HTML]{000000} 0.79 & 1.9 & 3.5 & 14.1 &
        19.8 & \color[HTML]{FFDD33} \bfseries HOLD \\
        \cline{1-11}
        \multirow[c]{2}{*}{Consumer} & H\&M & {\cellcolor[HTML]{EB6628}}
        \color[HTML]{F1F1F1} 0.66 & {\cellcolor[HTML]{F1731D}} \color[HTML]{F1F1F1}
        0.69 & {\cellcolor[HTML]{FCFFA4}} \color[HTML]{000000} 1.00 &
        {\cellcolor[HTML]{FAC42A}} \color[HTML]{000000} 0.86 & 7.0 & 49.0 & 210.9 &
        140.6 & \color[HTML]{33FF85} \bfseries BUY \\
         & Unilever & {\cellcolor[HTML]{F68013}} \color[HTML]{F1F1F1} 0.72 &
        {\cellcolor[HTML]{FCA108}} \color[HTML]{000000} 0.79 &
        {\cellcolor[HTML]{FAC42A}} \color[HTML]{000000} 0.86 &
        {\cellcolor[HTML]{FCFFA4}} \color[HTML]{000000} 1.00 & 213.8 & 45,693.3 &
        2,807.0 & 3,678.0 & \color[HTML]{FF5933} \bfseries SELL \\
        \cline{1-11}
        \bottomrule
        \end{tabular}
        \end{table}

        .. figure:: ../../_static/style/latex_stocks.png
        T�