Align the use of `y=` argument with `error_y` in `plotly.express`

At the moment, I can plot multiple y series with an API that looks like this:

import pandas as pd
import plotly.express as px

data = {
    'X_Values': pd.date_range(start='2023-01-01', periods=10, freq='D'),
    'Y1_Values': [3, 5, 7, 9, 11, 13, 15, 17, 19, 21],
    'Y2_Values': [2, 4, 6, 8, 10, 12, 14, 16, 18, 20],
    'Y3_Values': [1, 3, 5, 7, 9, 11, 13, 15, 17, 19],
}
df = pd.DataFrame(data)

px.scatter(df, x='X_Values', y=['Y1_Values', 'Y2_Values', 'Y3_Values'])

I would expect to be able to provide an array of error bars for each of the y's but that doesn't seem to be the case:

import pandas as pd
import plotly.express as px

data = {
    'X_Values': pd.date_range(start='2023-01-01', periods=10, freq='D'),
    'Y1_Values': [3, 5, 7, 9, 11, 13, 15, 17, 19, 21],
    'Y1_Errors': [0.5, 0.6, 0.7, 0.5, 0.8, 0.5, 0.7, 0.6, 0.5, 0.7],
    'Y2_Values': [2, 4, 6, 8, 10, 12, 14, 16, 18, 20],
    'Y2_Errors': [0.3, 0.5, 0.4, 0.6, 0.7, 0.5, 0.6, 0.4, 0.5, 0.6],
    'Y3_Values': [1, 3, 5, 7, 9, 11, 13, 15, 17, 19],
    'Y3_Errors': [0.4, 0.3, 0.6, 0.5, 0.7, 0.4, 0.5, 0.3, 0.6, 0.5],
}
df = pd.DataFrame(data)

px.scatter(df, x='X_Values', y=['Y1_Values', 'Y2_Values', 'Y3_Values'], error_y=['Y1_Errors', 'Y2_Errors', 'Y3_Errors'])

but this fails with

ValueError: All arguments should have the same length. The length of argument `error_y` is 3, whereas the length of  previously-processed arguments ['X_Values'] is 10

Can this get similar semantics to an array-like object in the y= argument?

Reproduce the examples with plotly.express.scatter, beginning with the handling of the y and error_y arguments. Compare how array-like y values are expanded with how error_y is validated. Done means matching error arrays can be supplied for each y series without the reported length error, with relevant behavior covered by tests.