df_to_html - ShopRunner's open-sourced helper function to convert Pandas DataFrame's to HTML.

df_to_html.py

import pandas as pd


def df_to_html(df: pd.DataFrame,
               image_cols: List[str] = [],
               hyperlink_cols: List[str] = [],
               html_tags: Dict[str, Union[str, List[str]]] = dict(),
               transpose: bool = False,
               image_width: Optional[int] = None,
               max_num_rows: int = 200,
               **kwargs) -> str:
    """
    Convert a Pandas DataFrame to HTML.

    Parameters
    -------------
    df: DataFrame
        DataFrame to convert to HTML
    image_cols: str or list
        Column names that contain image urls or file paths. Columns specified as images will make
        all other transformations to those columns be ignored. Local files will display correctly in
        Jupyter if specified using relative paths but not if specified using absolute paths (see
        https://github.com/jupyter/notebook/issues/3810).
    hyperlink_cols: str or list
        Column names that contain hyperlinks to open in a new tab
    html_tags: dictionary
        A transformation to be inserted directly into the HTML tag.

        Ex: ``{'col_name_1': 'strong'}`` becomes ``<strong>col_name_1</strong>``

        Ex: ``{'col_name_2': 'mark'}`` becomes ``<mark>col_name_2</mark>``

        Ex: ``{'col_name_3': 'h2'}`` becomes ``<h2>col_name_3</h2>``

        Ex: ``{'col_name_4': ['em', 'strong']}`` becomes ``<em><strong>col_name_4</strong></em>``

    transpose: bool
        Transpose the DataFrame before converting to HTML
    image_width: int
        Set image width for each image generated
    max_num_rows: int
        Maximum number of rows to display
    **kwargs: keyword arguments
        Additional arguments sent to ``pandas.DataFrame.to_html``, as listed in:
        https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_html.html

    Returns
    -------------
    df_html: HTML
        DataFrame converted to a HTML string, ready for displaying

    Examples
    -------------
    In a Jupyter notebook:

    .. code-block:: python

        from IPython.core.display import display, HTML
        import pandas as pd


        df = pd.DataFrame({
            'item': ['Beefy Fritos® Burrito'],
            'price': ['1.00'],
            'image_url': ['https://www.tacobell.com/images/22480_beefy_fritos_burrito_269x269.jpg'],
        })
        display(
            HTML(
                df_to_html(
                    df,
                    image_cols='image_url',
                    html_tags={'item': 'strong', 'price': 'em'},
                    image_width=200,
                )
            )
        )

    Notes
    -------------
    Converted table will have CSS class 'dataframe', unless otherwise specified.

    """
    def _wrap_cols_if_needed(cols: [str, List[str]]) -> List[str]:
        """Necessary for columns named with integers."""
        try:
            iter(cols)
        except TypeError:
            cols = [cols]
        if isinstance(cols, str):
            cols = [cols]

        return cols

    if max_num_rows is None or len(df) <= max_num_rows:
        df = df.copy()  # copy the dataframe so we don't edit the original!
    else:
        # explicit copy eliminates a warning we don't need
        df = df.head(max_num_rows).copy()

    image_cols = _wrap_cols_if_needed(image_cols)
    for image_col in image_cols:
        if image_col not in df.columns:
            raise ValueError('{} not a column in df!'.format(image_col))
        if not image_width:
            df[image_col] = df[image_col].map(lambda x: f'<img src="{x}">')
        else:
            df[image_col] = df[image_col].map(lambda x: f'<img src="{x}" width={image_width}>')

    hyperlink_cols = _wrap_cols_if_needed(hyperlink_cols)
    for hyperlink_col in hyperlink_cols:
        if hyperlink_col not in df.columns:
            raise ValueError('{} not a column in df!'.format(hyperlink_col))
        if hyperlink_col in image_cols:
            continue
        df[hyperlink_col] = (
            df[hyperlink_col].map(lambda x: f'<a target="_blank" href="{x}">{x}</a>')
        )

    for col, transformations in html_tags.items():
        if col not in df.columns:
            raise ValueError(f'{col} not a column in df!')
        if col in image_cols:
            continue

        if isinstance(transformations, str):
            transformations = [transformations]

        opening_tag = ''
        for extra in transformations:
            opening_tag += f'<{extra}>'

        closing_tag = ''
        for extra in transformations[::-1]:
            closing_tag += f'</{extra}>'

        df[col] = df[col].map(lambda x: f'{opening_tag}{x}{closing_tag}')

    max_colwidth = pd.get_option('display.max_colwidth')
    if pd.__version__ != '0':
        # this option is not backwards compatible with Pandas v1.0.0
        pd.set_option('display.max_colwidth', None)
    else:
        pd.set_option('display.max_colwidth', -1)

    if transpose:
        df = df.T
    df_html = df.to_html(escape=False, **kwargs)

    pd.set_option('display.max_colwidth', max_colwidth)

    return df_html