Pandas: DataFrame could have a to_markdown method.

[petebachant]

Similar to to_latex and to_html.

[TomAugspurger]

Is there a widely agreed upon format for markdown tables? It's not in Gruber's original version, and IIRC CommonMark even punted on them.

[petebachant]

Good point. I'm not sure. Maybe the method could specify a flavor, e.g., GitHub or Pandoc?

[TomAugspurger]

I suspect that anything too complicated won't find much support here (maintaining stuff is no fun). Especially now that we have pipe. df.pipe(to_markdown) isn't much worse than df.to_markdown.

Is your usecase here to present / read the mardown, or convert it to something else? Since markdown is a superset of HTML, you may be able to get away with to_html before converting.

[hayd]

One issue is what should the row headers be for MI columns/index. It seems that GH registers only the first (unless there is some syntactical trick).

For _most_ flavors you can include html.

[jankatins]

As the new styler uses jinja (https://github.com/pydata/pandas/pull/10250), this shouldn't be too hard? I would also love this feature for knitpy, which is a markdown based format which is converted into all kind of formats (docx...pdf...html).

Up to now (and as workarounds...), I recommended tabulate to convert a DataFrame to markdown. There is also pandoc (e.g. via pypandoc), which can take the output of df.to_html() and convert that to markdown.

[jreback]

@JanSchulz yes, I could see .to_markdown() method in Styler (as better API than to put it directly in DataFrame (though could have that as well).

[jankatins]

IMO, on .styler it doesn't make sense, markdown unfortunately do not provide styles :-( I only mentioned .styler as it already (soft) requires jinja and that should make it easy to build a markdown representation...

IMO it should be DataFrame.to_markdown() and DataFrame._repr_markdown_()

[ghost]

I'd love DataFrame.to_markdown() too. I was surprised when it didn't work already.

[pstjohn]

Would pandas be open to adding a dependency? tabulate does exactly this and is pip installable.

from tabulate import tabulate
print(tabulate(df, headers='keys', tablefmt='pipe'))

|    |   test1 | test2   |   test3 |   test4 |    test5 |
|---:|--------:|:--------|--------:|--------:|---------:|
|  0 |     385 | apple   |     288 |     745 |  64.9352 |
|  1 |     627 | banana  |       3 |     792 | 226.955  |
|  2 |     486 | pear    |     446 |     503 | 110.454  |
|  3 |     368 | orange  |     887 |     808 | 297.62   |
|  4 |     550 | grape   |     235 |      96 | 240.324  |
|  5 |     749 | peach   |      22 |     598 | 240.642  |

| | test1 | test2 | test3 | test4 | test5 |
|---:|--------:|:--------|--------:|--------:|---------:|
| 0 | 385 | apple | 288 | 745 | 64.9352 |
| 1 | 627 | banana | 3 | 792 | 226.955 |
| 2 | 486 | pear | 446 | 503 | 110.454 |
| 3 | 368 | orange | 887 | 808 | 297.62 |
| 4 | 550 | grape | 235 | 96 | 240.324 |
| 5 | 749 | peach | 22 | 598 | 240.642 |

[TomAugspurger]

I'm +0 to adding it as an optional dependency, and adding a to_markdown
method.

In the meantime, df.pipe(tabulate, header='keys', tablefmt='pipe') is a
workaround. I suppose it would be nice to avoid typing those keyword
arguments every time :)

On Wed, Oct 11, 2017 at 4:53 PM, Peter St. John [e-mail]
wrote:

Would pandas be open to adding a dependency? tabulate
https://pypi.python.org/pypi/tabulate does exactly this and is pip
installable.

from tabulate import tabulateprint(tabulate(df, headers='keys', tablefmt='pipe'))

  test1  test2      test3    test4    test5

---

0 356 apple 876 510 904
1 90 banana 590 24 988
2 150 pear 652 731 792
3 399 orange 603 76 420
4 864 grape 322 703 324
5 281 peach 731 192 192

test1 test2 test3 test4 test5
0 356 apple 876 510 904
1 90 banana 590 24 988
2 150 pear 652 731 792
3 399 orange 603 76 420
4 864 grape 322 703 324
5 281 peach 731 192 192

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[jreback]

i think adding a to_markdown method which calls tabulate as a dependency would be ok

[aflaxman]

print(tabulate(df, headers='keys', tablefmt='pipe')) is not as pretty as pandas for multi-index, would be cool if whatever pandas lands on is.

[kangwonlee]

FYI : Google found this discussion for me: https://stackoverflow.com/questions/33181846/programmatically-convert-pandas-dataframe-to-markdown-table

[MarcoGorelli]

I'm +0 to adding it as an optional dependency, and adding a to_markdown method. In the meantime, df.pipe(tabulate, header='keys', tablefmt='pipe') is a workaround. I suppose it would be nice to avoid typing those keyword arguments every time :)

@TomAugspurger Is this all the method would have to do? If so, I'd be happy to work on a PR

[jreback]

i think we would likely accept a PR for something like the above

[MarcoGorelli]

Sure, I've submitted a simple PR.

What should this method return if there's a wide DataFrame? (or is this an enhancement that would get taken care of at a later stage?)