Make pandas pipelines interactive
## The Pain

Pandas is a powerful tool. If you are making a longer pipeline of chained operations there can be many arguments to provide. Often you want to try out different options. But that can take time to change the options and rerun the script.

#### Describe the solution you'd like

I would like to make the arguments interactive. With widgets. And eventually turn the pipeline into a small, interactive data app.

### The solution is already here

[hvplot](https://hvplot.holoviz.org/) now provides the `.interactive` method to make dataframe pipelines interactive. [Panel](https://panel.holoviz.org/) makes it easy to turn the pipeline into a small, interactive data app.

Basically what you can now make for example the `seattle_bikes` dataframe pipeline below interactive with widgets

```python
# Widgets
resample = pn.widgets.Select(value="D", options=["D", "W", "M"], name="Sampling Frequency")
window = pn.widgets.IntSlider(value=50, start=10, end=100, name="Rolling Window Length")
center = pn.widgets.Checkbox(value=True, name="Center")
win_type = pn.widgets.Select(value="gaussian", options=[None, "gaussian"], name="Window Type")
std = pn.widgets.IntSlider(value=10, start=5, end=20, name="std")
line_width = pn.widgets.IntSlider(value=6, start=1, end=20, name="Line Width")

# A Pandas Dataframe made .interactive with hvPlot
pipeline = (
    seattle_bikes.interactive()
    .resample(resample)
    .sum()
    .rolling(window, center=center, win_type=win_type)
    .sum(std=10)
    .dropna()
)

# Interactive Plot
plot = pn.panel(
    pipeline.hvplot( # pandas .plot drop in replacement to render to Matplotlib, Bokeh or Plotly
        responsive=True,
        height=600,
        color=PALETTE,
        line_width=line_width,
        yformatter="%.0f",
    ).holoviews(),
    sizing_mode="stretch_both",
    name="Plot",
)

# Interactive Table
table = pipeline.pipe(
    pn.widgets.Tabulator,
    pagination="remote",
    page_size=20,
    theme="fast",
    sizing_mode="stretch_both",
).panel(name="Table")
```

https://user-images.githubusercontent.com/42288570/139597169-a60db679-ecbe-438b-b5f1-987f1ce0ef03.mp4

You can find the full code in this gist https://gist.github.com/MarcSkovMadsen/ffb273636dced88705c8c88d5ee28f23

You can use it in a notebook, colab, vs code, pycharm or where ever you explore and code.

### Additional Resources

[![image](https://user-images.githubusercontent.com/42288570/139597274-4ea43cde-a1ee-4dc6-a743-8aa48fb5bc7e.png)](https://discourse.holoviz.org/t/pydata-2021-build-polished-data-driven-applications-directly-from-your-pandas-or-xarray-pipelines/3017)

- [hvplot .interactive reference guide](https://hvplot.holoviz.org/)

### You may close this issue

I think this api is truly revolutionary and would like the world to know. Thus I shared the example here as I don't know where else this information can be shared in the Pandas community. You may close this issue.