GT.fmt_markdown()

Format Markdown text.

Usage

GT.fmt_markdown(
    columns=None,
    rows=None,
)

Any Markdown-formatted text in the incoming cells will be transformed during render when using the fmt_markdown() method.

Parameters

columns: SelectExpr = None: The columns to target. Can either be a single column name or a series of column names provided in a list.
rows: int | list[int] | None = None: In conjunction with columns=, we can specify which of their rows should undergo formatting. The default is all rows, resulting in all rows in targeted columns being formatted. Alternatively, we can supply a list of row indices.

Returns

GT: The GT object is returned. This is the same object that the method is called on so that we can facilitate method chaining.

Examples

Let’s first create a DataFrame containing some text that is Markdown-formatted and then introduce that to GT(). We’ll then transform the md column with the fmt_markdown() method.

import pandas as pd
from great_tables import GT
from great_tables.data import towny

text_1 = """
### This is Markdown.

Markdown’s syntax is comprised entirely of
punctuation characters, which punctuation
characters have been carefully chosen so as
to look like what they mean... assuming
you’ve ever used email.
"""

text_2 = """
Info on Markdown syntax can be found
[here](https://daringfireball.net/projects/markdown/).
"""

df = pd.DataFrame({"md": [text_1, text_2]})

(GT(df).fmt_markdown("md"))

md
This is Markdown. Markdown’s syntax is comprised entirely of punctuation characters, which punctuation characters have been carefully chosen so as to look like what they mean... assuming you’ve ever used email.
Info on Markdown syntax can be found here.

This is Markdown.

Markdown’s syntax is comprised entirely of punctuation characters, which punctuation characters have been carefully chosen so as to look like what they mean... assuming you’ve ever used email.

Info on Markdown syntax can be found here.