> ## Documentation Index
> Fetch the complete documentation index at: https://anaconda.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Visualizations and dashboards

Anaconda Enterprise makes it easy for you to create and share interactive data visualizations, live notebooks or machine learning models built using popular libraries such as Bokeh and HoloViews.

To get you started quickly, Anaconda Enterprise provides sample projects of Bokeh applications for clustering and cross filtering data. There are also several [examples of AE5 projects that use PyViz here](https://examples.pyviz.org/).

***

Follow these steps to create an interactive plot:

1. From the **Projects** view, select **Create + > New Project** and create a project from the `Anaconda 3.6 (v5.0.1)` template:

   <Frame>
     <img src="https://mintcdn.com/anaconda-29683c67/GAawxvWy-HUVSCqf/images/project_templates.png?fit=max&auto=format&n=GAawxvWy-HUVSCqf&q=85&s=ecb6fb3371c6fedd1b1b4d3efa79dbec" alt="" width="1642" height="996" data-path="images/project_templates.png" />
   </Frame>

2. Open the project in a session <Icon icon="code" iconType="light" />, select **New > Terminal** to open a terminal, and run the following command to install packages for `hvplot`, `panel`, `pyct`, and `bokeh`:

   ```
   anaconda-project add-packages hvplot panel
   ```

   <Frame>
     <img src="https://mintcdn.com/anaconda-29683c67/u4MsRLDCM8Pedgc_/images/terminal_pkgs.png?fit=max&auto=format&n=u4MsRLDCM8Pedgc_&q=85&s=79bf7ec18ba6460a39145f72d41d5c6f" alt="" width="2476" height="1526" data-path="images/terminal_pkgs.png" />
   </Frame>

3. Select **New > Python 3** to create a new notebook, rename it `tips.ipynb`, and add the following code to create an interactive plot:

   ```
   import pandas as pd
   import hvplot.pandas
   import panel

   panel.extension()

   df = pd.read_csv('http://bit.ly/tips-csv')
   p = df.hvplot.scatter(x='total_bill', y='tip', hover_cols=['sex','day','size'])
   pn.Pane(p).servable()
   ```

   <Note>
     In this example, the data is being read from the Internet. Alternatively, you
     could
     [download](https://raw.githubusercontent.com/mwaskom/seaborn-data/master/tips.csv)
     the `.csv` and upload it to the project.
   </Note>

4. Open the project’s `anaconda-project.yml` file, and add the following lines after
   the `description`. This is the deployment command that Anaconda Enterprise will use
   when you deploy the notebook. `commands: scatter-plot: unix: panel serve tips.ipynb
   supports_http_options: True`

5. [Save and commit your changes](./projects/commit-changes).

   <Frame>
     <img src="https://mintcdn.com/anaconda-29683c67/6fJRxAwYs9izUc34/images/commit_tips.png?fit=max&auto=format&n=6fJRxAwYs9izUc34&q=85&s=aa782b4165e3c81be9e77ad1449b4726" alt="" width="2564" height="1328" data-path="images/commit_tips.png" />
   </Frame>

   <Frame>
     <img src="https://mintcdn.com/anaconda-29683c67/6fJRxAwYs9izUc34/images/commit-tips2.png?fit=max&auto=format&n=6fJRxAwYs9izUc34&q=85&s=9d71fa17d3c3879efd0c3e2ff1a32f5c" alt="" width="994" height="1414" data-path="images/commit-tips2.png" />
   </Frame>

6. Now you’re ready to [deploy the project](./deployments/project).

<Frame>
  <img src="https://mintcdn.com/anaconda-29683c67/atV1FF4bOzhiwIx6/images/deploy_tips.png?fit=max&auto=format&n=atV1FF4bOzhiwIx6&q=85&s=de2ed3c8b875f5b0cfd3402f12559ba5" alt="" width="2486" height="1528" data-path="images/deploy_tips.png" />
</Frame>

<Frame>
  <img src="https://mintcdn.com/anaconda-29683c67/atV1FF4bOzhiwIx6/images/deploy_tips2.png?fit=max&auto=format&n=atV1FF4bOzhiwIx6&q=85&s=b1cc86a3cad42b63a99b307842e24e94" alt="" width="2790" height="1216" data-path="images/deploy_tips2.png" />
</Frame>

To interact with the notebook—executing its cells without making changes to it—click the deployment’s name.

<Frame>
  <img src="https://mintcdn.com/anaconda-29683c67/kBuj3mPdZoBk8YoG/images/view_deploy_new.png?fit=max&auto=format&n=kBuj3mPdZoBk8YoG&q=85&s=c07f58799b47b66f1a4befb53a448c50" alt="" width="2488" height="1264" data-path="images/view_deploy_new.png" />
</Frame>

<Tip>
  To dive deeper into the world of data visualization, follow [this HoloViz
  tutorial](https://holoviz.org/tutorial/index.html).
</Tip>

To view and monitor the logs for the deployment while it’s running, click **Logs** in the left menu. The **app** section records the initialization steps and any messages printed to standard output by the command used in your project.

<Frame>
  <img src="https://mintcdn.com/anaconda-29683c67/u4MsRLDCM8Pedgc_/images/tips_logs.png?fit=max&auto=format&n=u4MsRLDCM8Pedgc_&q=85&s=e6336dc7ebf6d60bb9b9c3f4c141c978" alt="" width="2650" height="1126" data-path="images/tips_logs.png" />
</Frame>

You can also [share the deployment](./deployments/share) with others.