bigframes.pandas.DataFrame.to_html#

DataFrame.to_html(buf=None, columns: Sequence[str] | None = None, col_space=None, header: bool = True, index: bool = True, na_rep: str = 'NaN', formatters=None, float_format=None, sparsify: bool | None = None, index_names: bool = True, justify: str | None = None, max_rows: int | None = None, max_cols: int | None = None, show_dimensions: bool = False, decimal: str = '.', bold_rows: bool = True, classes: str | list | tuple | None = None, escape: bool = True, notebook: bool = False, border: int | None = None, table_id: str | None = None, render_links: bool = False, encoding: str | None = None, *, allow_large_results: bool | None = None) → str[source]#

Render a DataFrame as an HTML table.

Examples:

>>> df = bpd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
>>> print(df.to_html())
<table border="1" class="dataframe">
<thead>
    <tr style="text-align: right;">
    <th></th>
    <th>col1</th>
    <th>col2</th>
    </tr>
</thead>
<tbody>
    <tr>
    <th>0</th>
    <td>1</td>
    <td>3</td>
    </tr>
    <tr>
    <th>1</th>
    <td>2</td>
    <td>4</td>
    </tr>
</tbody>
</table>

Parameters:

buf (str, Path or StringIO-like, optional, default None) – Buffer to write to. If None, the output is returned as a string.
columns (sequence, optional, default None) – The subset of columns to write. Writes all columns by default.
col_space (str or int, list or dict of int or str, optional) – The minimum width of each column in CSS length units. An int is assumed to be px units.
header (bool, optional) – Whether to print column labels, default True.
index (bool, optional, default True) – Whether to print index (row) labels.
na_rep (str, optional, default 'NaN') – String representation of NAN to use.
formatters (list, tuple or dict of one-param. functions, optional) – Formatter functions to apply to columns’ elements by position or name. The result of each function must be a unicode string. List/tuple must be of length equal to the number of columns.
float_format (one-parameter function, optional, default None) – Formatter function to apply to columns’ elements if they are floats. This function must return a unicode string and will be applied only to the non-NaN elements, with NaN being handled by na_rep.
sparsify (bool, optional, default True) – Set to False for a DataFrame with a hierarchical index to print every multiindex key at each row.
index_names (bool, optional, default True) – Prints the names of the indexes.
justify (str, default None) – How to justify the column labels. If None uses the option from the print configuration (controlled by set_option), ‘right’ out of the box. Valid values are, ‘left’, ‘right’, ‘center’, ‘justify’, ‘justify-all’, ‘start’, ‘end’, ‘inherit’, ‘match-parent’, ‘initial’, ‘unset’.
max_rows (int, optional) – Maximum number of rows to display in the console.
max_cols (int, optional) – Maximum number of columns to display in the console.
show_dimensions (bool, default False) – Display DataFrame dimensions (number of rows by number of columns).
decimal (str, default '.') – Character recognized as decimal separator, e.g. ‘,’ in Europe.
bold_rows (bool, default True) – Make the row labels bold in the output.
classes (str or list or tuple, default None) – CSS class(es) to apply to the resulting html table.
escape (bool, default True) – Convert the characters <, >, and & to HTML-safe sequences.
notebook (bool, default False) – Whether the generated HTML is for IPython Notebook.
border (int) – A border=border attribute is included in the opening <table> tag. Default pd.options.display.html.border.
table_id (str, optional) – A css id is included in the opening <table> tag if specified.
render_links (bool, default False) – Convert URLs to HTML links.
encoding (str, default "utf-8") – Set character encoding.
allow_large_results (bool, default None) – If not None, overrides the global setting to allow or disallow large query results over the default size limit of 10 GB.

Returns:

If buf is None, returns the result as a string. Otherwise returns None.

Return type:

str or None

bigframes.pandas.DataFrame.to_html#

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