Letting Anyone Explore Airbnb on the Fly

This example shows how to load, visualize, and interactively explore Airbnb listing data from San Francisco — roughly 7,000 points covering locations, property types, occupancy, reviews, and pricing — using a Fused Canvas with an AI-powered chat widget that lets anyone ask questions and reshape the visualization in real time.

Walkthrough: Exploring Airbnb data with a Fused AI widget. Try the Canvas

Airbnb publishes detailed listing data for cities around the world, but exploring it usually means downloading CSVs and writing one-off scripts. With Fused, you can load the dataset into a Canvas, visualize it on a map, and attach an AI chat widget so anyone — technical or not — can ask questions and get instant visual answers.

Building the canvas

1. Load the Airbnb dataset

The airbnb_data UDF reads a Parquet file containing ~7,000 San Francisco Airbnb listings from S3. Each row includes the listing's location, neighbourhood, property type, occupancy, review scores, and pricing. The data is cached so subsequent runs load instantly.

@fused.udf
def udf():
    import pandas as pd

    @fused.cache
    def load_data():
        return pd.read_parquet("s3://fused-sample/demo_data/airbnb_listings_sf.parquet")

    df = load_data()
    print(df.head())
    print(df.dtypes)
    print(df.shape)
    return df

2. Connect a render widget to visualize the data

The airbnb_data UDF returns a DataFrame. To visualize it, we connect it to a widget by drawing an edge from the UDF node to the widget node in the Canvas.

We use a render widget here because it wraps any chart type and layers on an AI panel — so users can modify the visualization with natural language without touching JSON. In this example we plot a bar chart of the top 15 neighbourhoods by average price:

{
  "type": "render",
  "props": {
    "defaultValue": {
      "type": "bar-chart",
      "props": {
        "sql": "SELECT neighbourhood_cleansed as label, ROUND(AVG(price_in_dollar), 2) as value FROM {{airbnb_data}} GROUP BY neighbourhood_cleansed ORDER BY value DESC LIMIT 15",
        "title": "Top 15 Neighbourhoods"
      }
    },
    "aiBuilderMode": "enabled",
    "aiPanel": "right"
  }
}

Notice the {{airbnb_data}} in the SQL — this is the widget template syntax. Because the widget is connected to the airbnb_data UDF via an edge, the name inside {{ }} resolves automatically to that UDF's output. You just reference the UDF by name and the widget handles the rest.

• aiBuilderMode: "enabled" — activates the built-in AI panel so users can describe changes in natural language.
• aiPanel: "right" — positions the AI chat on the right side of the widget.

What you can ask the AI widget

The AI panel rewrites the inner widget definition based on your prompt. Try things like:

• "Switch to a pie chart of property types"
• "Show a histogram of review scores"
• "Map the most expensive listings"
• "Show average price by room type as a horizontal bar chart"

See the AI-driven widget guide for all available props and widget types.

3. Explore the data interactively

With the AI panel enabled, anyone can reshape the visualization without writing code. Ask for ratings distributions, price comparisons across neighbourhoods, occupancy trends — the AI rewrites the widget definition on the fly, and the chart updates instantly. This turns a static dashboard into a conversational data exploration tool.

4. Share with anyone

The Canvas can be shared as a link or as a standalone widget. Share the full Canvas for the complete experience (map + widget + AI chat), or share just the widget for a focused, embeddable view that anyone can interact with — no Fused account required.

Try it out

Open the Fused Canvas to explore the live Airbnb dataset, or go straight to the interactive widget to ask questions directly.

Make it your own

Clone the Canvas to customize it. Swap the data source, change the default chart, or adjust the AI panel position. See the Widgets guide for the full list of render widget props.