Data source in Jupyter needs full URL

In Jupyter Lab I have seattle-weather.csv, bar.vl.json and a notebook all in the same folder. The data is from the example data sets, as is the Vega Lite:

{
  "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
  "data": {"url": "seattle-weather.csv"},
  "mark": "bar",
  "encoding": {
    "x": {"timeUnit": "month", "field": "date", "type": "ordinal"},
    "y": {"aggregate": "count", "type": "quantitative"},
    "color": {"field": "weather", "type": "nominal"}
  }
}

Opening the Vega Lite file directly creates a tab with the bar chart rendered as expected. In the notebook I need to pass the full URL to Altair to create the same visualisation:

alt.Chart('http://localhost:8888/files/seattle-weather.csv').mark_bar().encode(
    x='month(date):O',
    y='count():Q',
    color='weather:N'
)

Why does alt.Chart('seattle-weather.csv')..... not work in the notebook? Can the docs be updated to include guidance around this use case scenario?

[joelostblom]

I just discovered that it works as expected with /files instead of just files.

[jakevdp]

I don’t think the full URL is actually required. For example, I ran this in a local JupyterLab instance and it produced a correctly rendered chart:

import altair as alt
from vega_datasets import data
!curl -O {data.seattle_weather.url}

alt.Chart('files/seattle-weather.csv').mark_bar().encode(
    x='month(date):O',
    y='count():Q',
    color='weather:N'
)

(This will only work if you have not used the %cd magic command to change the working directory from the JupyterLab root. I believe there are also caveats about different ways to start kernels and different jupyter configuration settings that will make this fail, because the location in which the curl command is run can diverge from the JupyterLab root directory)