pyspark.pandas.DataFrame.to_latex

DataFrame.to_latex(buf: Optional[IO[str]] = None, columns: Optional[List[Union[Any, Tuple[Any, …]]]] = None, col_space: Optional[int] = None, header: bool = True, index: bool = True, na_rep: str = 'NaN', formatters: Union[List[Callable[[Any], str]], Dict[Union[Any, Tuple[Any, …]], Callable[[Any], str]], None] = None, float_format: Optional[Callable[[float], str]] = None, sparsify: Optional[bool] = None, index_names: bool = True, bold_rows: bool = False, column_format: Optional[str] = None, longtable: Optional[bool] = None, escape: Optional[bool] = None, encoding: Optional[str] = None, decimal: str = '.', multicolumn: Optional[bool] = None, multicolumn_format: Optional[str] = None, multirow: Optional[bool] = None) → Optional[str]

Render an object to a LaTeX tabular environment table.

Render an object to a tabular environment table. You can splice this into a LaTeX document. Requires usepackage{booktabs}.

Note

This method should only be used if the resulting pandas object is expected to be small, as all the data is loaded into the driver’s memory. If the input is large, consider alternative formats.

Parameters

buffile descriptor or None

Buffer to write to. If None, the output is returned as a string.

columnslist of label, optional

The subset of columns to write. Writes all columns by default.

col_spaceint, optional

The minimum width of each column.

Deprecated since version 3.4.0.

headerbool or list of str, default True

Write out the column names. If a list of strings is given, it is assumed to be aliases for the column names.

indexbool, default True

Write row names (index).

na_repstr, default ‘NaN’

Missing data representation.

formatterslist of functions or dict of {str: function}, optional

Formatter functions to apply to columns’ elements by position or name. The result of each function must be a Unicode string. List must be of length equal to the number of columns.

float_formatstr, optional

Format string for floating point numbers.

sparsifybool, optional

Set to False for a DataFrame with a hierarchical index to print every multiindex key at each row. By default the value will be read from the config module.

index_namesbool, default True

Prints the names of the indexes.

bold_rowsbool, default False

Make the row labels bold in the output.

column_formatstr, optional

The columns format as specified in LaTeX table format e.g. ‘rcl’ for 3 columns. By default, ‘l’ will be used for all columns except columns of numbers, which default to ‘r’.

longtablebool, optional

By default the value will be read from the pandas config module. Use a longtable environment instead of tabular. Requires adding a usepackage{longtable} to your LaTeX preamble.

escapebool, optional

By default the value will be read from the pandas config module. When set to False prevents from escaping latex special characters in column names.

encodingstr, optional

A string representing the encoding to use in the output file, defaults to ‘ascii’ on Python 2 and ‘utf-8’ on Python 3.

decimalstr, default ‘.’

Character recognized as decimal separator, e.g. ‘,’ in Europe.

multicolumnbool, default True

Use multicolumn to enhance MultiIndex columns. The default will be read from the config module.

multicolumn_formatstr, default ‘l’

The alignment for multicolumns, similar to column_format The default will be read from the config module.

multirowbool, default False

Use multirow to enhance MultiIndex rows. Requires adding a usepackage{multirow} to your LaTeX preamble. Will print centered labels (instead of top-aligned) across the contained rows, separating groups via clines. The default will be read from the pandas config module.

Returns

str or None

If buf is None, returns the resulting LateX format as a string. Otherwise returns None.

See also

DataFrame.to_string

Render a DataFrame to a console-friendly tabular output.

DataFrame.to_html

Render a DataFrame as an HTML table.

Examples

>>> df = ps.DataFrame({'name': ['Raphael', 'Donatello'],
...                    'mask': ['red', 'purple'],
...                    'weapon': ['sai', 'bo staff']},
...                   columns=['name', 'mask', 'weapon'])
>>> print(df.to_latex(index=False)) 
\begin{tabular}{lll}
\toprule
      name &    mask &    weapon \\
\midrule
   Raphael &     red &       sai \\
 Donatello &  purple &  bo staff \\
\bottomrule
\end{tabular}

pyspark.pandas.DataFrame.to_records pyspark.pandas.DataFrame.style