[BUG]: px.sunburst / px.treemap / px.icicle with path give a different sector order on every run for Polars DataFrames

Description

When path= is used with a Polars DataFrame, px.sunburst, px.treemap and px.icicle build their ids / labels / parents / values arrays in a different order every time the script is run. The same data as a pandas DataFrame or a PyArrow table always gives the same order: the order in which the sectors first appear in the data.

The cause is in process_dataframe_hierarchy (plotly/express/_core.py). Each level of the hierarchy is built with df.group_by(path[i:]).agg(...). With pandas (narwhals uses sort=False) and PyArrow the groups come back in order of first appearance, but Polars' group_by does not guarantee any order, so the order of the output changes from run to run.

Consequences:

• fig.to_json() / fig.write_html() output is not reproducible with Polars input (snapshot tests, caching, diffs of generated HTML).
• With sort=False, or when sectors have equal values, the chart itself is laid out differently on each run.
• Polars results differ from pandas / PyArrow results for identical data.

Screenshots/Video

N/A: the difference is in the figure data; see the output below.

Steps to reproduce

import plotly
import plotly.express as px
import polars as pl

df = pl.DataFrame(
    {
        "region": ["South", "North", "South", "West", "North", "West"],
        "sector": ["Tech", "Finance", "Finance", "Tech", "Tech", "Finance"],
        "sales": [1, 2, 3, 4, 5, 6],
    }
)
fig = px.sunburst(df, path=["region", "sector"], values="sales")
print(plotly.__version__, pl.__version__, list(fig.data[0].ids))

Running the script three times (plotly 7.1.0, polars 1.44.2):

7.1.0 1.44.2 ['West/Tech', 'West/Finance', 'North/Finance', 'South/Finance', 'North/Tech', 'South/Tech', 'South', 'North', 'West']
7.1.0 1.44.2 ['South/Tech', 'West/Tech', 'North/Tech', 'South/Finance', 'North/Finance', 'West/Finance', 'West', 'North', 'South']
7.1.0 1.44.2 ['South/Tech', 'West/Tech', 'North/Tech', 'North/Finance', 'South/Finance', 'West/Finance', 'West', 'South', 'North']

With pd.DataFrame(...) instead, every run prints:

['South/Tech', 'North/Finance', 'South/Finance', 'West/Tech', 'North/Tech', 'West/Finance', 'South', 'North', 'West']

Notes

I have a small fix with a regression test and will open a PR for it.

Commencez dans plotly/express/_core.py, au niveau de process_dataframe_hierarchy, et suivez les appels à group_by utilisés pour les graphiques basés sur des chemins. Comparez l’ordre de la hiérarchie de Polars, pandas et PyArrow, puis examinez le test de régression inclus ou proposé par le rapporteur. Le travail est terminé lorsque des exécutions répétées de Polars produisent un ordre stable selon la première occurrence, cohérent avec les autres entrées prises en charge.