(gallery_ppc_interval)=

# Interval plot
Plot posterior predictive point estimate and intervals at each observation.


::::::{tab-set}
:class: full-width
:sync-group: backend

:::::{tab-item} Matplotlib
:sync: matplotlib

![Matplotlib version of plot_ppc_interval](_images/plot_ppc_interval.png)

:::::

:::::{tab-item} Bokeh
:sync: bokeh

```{bokeh-plot}
:source-position: none

from bokeh.plotting import show

from arviz_base import load_arviz_data

import arviz_plots as azp

azp.style.use("arviz-variat")

data = load_arviz_data("radon")

data_subset = data.isel(obs_id=range(50))

pc = azp.plot_ppc_interval(
data_subset,
backend="bokeh",
)



# for some reason the bokeh plot extension needs explicit use of show
show(pc.viz["figure"].item() if pc.viz["figure"].item() is not None else pc.viz["plot"].item())
```

Link to this page with the [bokeh tab selected](https://arviz-plots.readthedocs.io/en/latest//gallery/plot_ppc_interval.html?backend=bokeh#synchronised-tabs)
:::::

:::::{tab-item} Plotly
:sync: plotly

```{jupyter-execute}
:hide-code:

from arviz_base import load_arviz_data

import arviz_plots as azp

azp.style.use("arviz-variat")

data = load_arviz_data("radon")

data_subset = data.isel(obs_id=range(50))

pc = azp.plot_ppc_interval(
data_subset,
backend="plotly",
)

pc.show()
```

Link to this page with the [plotly tab selected](https://arviz-plots.readthedocs.io/en/latest//gallery/plot_ppc_interval.html?backend=plotly#synchronised-tabs)
:::::
::::::

```{literalinclude} _scripts/plot_ppc_interval.py
:emphasize-lines: 13
```


:::{seealso}
API Documentation: {func}`~arviz_plots.plot_ppc_interval`
:::



## Other examples with `plot_ppc_interval`

```{eval-rst}
.. minigallery:: plot_ppc_interval
```


:::{div} example-plot-download
{download}`Download Python Source Code: plot_ppc_interval.py<_scripts/plot_ppc_interval.py>`
:::