seaborn.objects.Plot color option cannot handle a list of a single value

[AyushmaanAggarwal]

When setting seaborn.objects.Plot(df,x="x", y="y",..., color="single_value"), where df["single_value"] is a list of size df["x"] with only a single value(say all ones), seaborn crashes with the error ValueError: 'alpha' must be between 0 and 1, inclusive

Ideally, this would just use a single color for the plot and label the single color if a legend is generated.

This dataframe fails

x = np.linspace(0, 10, 100)
df =  {"x":x, "y":np.sin(x), "ymin": np.sin(x)*.9, "ymax": np.sin(x)*1.1, "color" : np.ones_like(x)}

And this dataframe succeeds

x = np.linspace(0, 10, 100)
df =  {"x":x, "y":np.sin(x), "ymin": np.sin(x)*.9, "ymax": np.sin(x)*1.1, "color" : np.random.randint(0,3,size=np.shape(x))},

while running the following code

import numpy as np
import seaborn.objects as so
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(10, 5))
p = (
    so.Plot(
      df,
      x="x",
      y="y",
      ymin="ymin",
      ymax="ymax",
      color="color",
    )
        .add(so.Dots())
        .add(so.Line(alpha=1))
        .add(so.Range())
        .add(so.Band())
        .label(x="x", y="Leakage after 512 Circuit Depth")
        .on(ax)
        .show()
)

This is the link to the full error:
https://gist.github.com/AyushmaanAggarwal/33bf35fd0e4b6dc38b3de69bfc15d57a#file-full-error-seaborn-color

[kudos07]

Thanks for the detailed traceback. This error occurs when the color variable has only one unique value. In that case, seaborn.objects treats it as continuous, but the scale domain collapses (vmin == vmax). That yields invalid normalized values that eventually get passed to Matplotlib as alpha, triggering:

ValueError: 'alpha' must be between 0 and 1, inclusive

Minimal repro

import numpy as np, pandas as pd
import seaborn.objects as so

x = np.linspace(0, 10, 100)
df = pd.DataFrame({
    "x": x,
    "y": np.sin(x),
    "qubit": np.zeros_like(x),  # only one unique value
})

so.Plot(df, x="x", y="y", color="qubit").add(so.Dots()).show()

Why it happens

• With multiple unique values, continuous normalization works.
• With one value, the domain collapses and produces invalid RGBA values, which surface as the 'alpha' must be between 0 and 1' error.

Expected behavior

Use a single color for the plot (and optionally a single legend entry) rather than raising.

Workarounds

• Pass a fixed color instead of mapping:

  .add(so.Dots(color="C0"))

• Or coerce the column to categorical so it’s treated as nominal:

  df["qubit"] = "one"

Question for maintainers

I’m happy to open a PR to handle this edge case. Would you prefer seaborn to:

1. Automatically fall back to a nominal scale when there’s only one unique value, or
2. Skip normalization and assign a fixed color without a legend entry?