# Share a ydata-profiling EDA Report — Link It, Don't Mail It

Canonical: https://commareports.com/share-eda-report
Published: 2026-08-18

> ydata-profiling, Sweetviz, and D-Tale write a big self-contained HTML file that email rejects. Publish it to Comma for one private link, anchored comments on individual columns, and a revision per refresh.

# Share an EDA / data-profiling report

The first honest thing anyone does with a new dataset is profile it —
`ydata-profiling`, Sweetviz, D-Tale, `skimpy`. One line of Python, and out
comes a genuinely excellent document: every column's distribution,
missingness, cardinality, correlations, the rows that look wrong.

Then comes the part nobody solved. The file is 15–40 MB of self-contained
HTML. Email bounces it. Slack mangles it. Committing it to the repo makes
the reviewer download a blob to open locally, and putting it on a static
host means publishing sample rows of production data to the internet. So
the profile — the artifact most likely to catch a data problem before it
reaches a model or a board deck — gets looked at by exactly one person.

## Publish it instead

```python
from ydata_profiling import ProfileReport

ProfileReport(df, title="Orders — 2026-08").to_file("profile.html")
```

Then drag `profile.html` into [Comma](https://commareports.com/), or push
it from a pipeline:

```bash
curl -fsS -X POST https://commareports.com/api/v1/reports \
  -H "Authorization: Bearer $COMMA_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d "$(jq -n --rawfile html profile.html \
        '{title: "Orders profile — 2026-08", html: $html}')"
```

You get a URL that opens like a document — no Python, no notebook server,
no repo access — behind the access level you pick. Reports are private by
default and can be opened to invited people, to any signed-in colleague,
or to the public. For an artifact containing real sample rows, that
choice is the whole point; see the [sharing model](/docs/sharing).

## The conversation belongs on the column

A profiling report is a list of things that might be wrong. Every one of
them deserves a sentence from someone who knows the domain, and every one
of those sentences currently gets typed into Slack, detached from the
column it's about.

With an [anchored comment layer](/comment-on-html) on the rendered report,
the analyst highlights `discount_pct — 12.4% missing` and pins a thread:
"missing means no promo applied, not unknown — don't impute." Someone
else marks the bimodal `session_length` histogram: "that's the bot
traffic we filtered out in July, it's back." The next person to open the
profile reads the domain knowledge next to the statistic instead of
rediscovering the same anomaly a month later.

That's the difference between a profile you generate and a profile your
team actually reviews.

## Re-profile without breaking the link

`PATCH` the same report id when the data refreshes:

```bash
curl -fsS -X PATCH "https://commareports.com/api/v1/reports/$REPORT_ID" \
  -H "Authorization: Bearer $COMMA_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d "$(jq -n --rawfile html profile.html '{html: $html}')"
```

Same URL, one revision per refresh, and any two revisions can be
[diffed](/docs/ci) — which is how a drifting distribution or a newly-null
column shows up as a *change* rather than as a fact you have to notice
twice. Open threads carry across revisions.

To take the human out of the loop entirely, a
[routine](/features/routines) regenerates and republishes on a schedule,
and a [webhook](/docs/api) on `revision.created` announces each refresh in
Slack.

## What renders, and what doesn't

- **Renders faithfully** — per-column statistics tables, histograms,
  correlation heatmaps, missing-value matrices, sample rows. These are
  HTML, CSS, and embedded images.
- **Inert** — the collapsible tab navigation and any interactive widget,
  because Comma strips `<script>` on write as defense-in-depth on an
  endpoint that accepts arbitrary HTML. Reports generated in the flat or
  long-form layout read best; Sweetviz and skimpy output land the same way.
- **Big files are fine** — a self-contained profile with inlined images is
  a single HTML document. If your generator writes a folder instead, drop
  the whole folder or a zip of it and the relative references are rewritten
  automatically.

Working in notebooks? [Share the notebook itself](/with/jupyter) the same
way — export with `nbconvert`, publish, and comment on the cells.

## Try it

Comma is free — unlimited reports, unlimited commenters, unlimited
revision history. Profile your next dataset, publish it, and let the
people who know the data write on it.

**[Create your first report →](https://commareports.com/)**