(porting across from other repo#7670)

Description

I would like to request the ability to specify a dash style (e.g., "dash", "dot", "dashdot") for the border line of markers in scatter plots.

Currently, themarker.line object only supports properties likecolor andwidth. It does not supportdash, unlikeline traces orshapes.

Attempting to setmarker=dict(line=dict(dash="dash")) currently raises aValueError.

Why should this feature be added?

This feature is essential for creating clear visual distinctions in scatter plots without relying solely on color or marker symbols.

Use Case:

In data imputation or time-series analysis, it is common to visualize "missing" or "inferred" data points alongside original data.

• Original Data: Solid markers.
• Imputed/Inferred Data: Markers with a dashed outline (often hollow or lighter fill).

Current Limitations:

1. Shapes: Usinglayout.shapes (circles) allows for dashed borders, but shapes are defined in data coordinates. This causes circles to distort into ellipses when the x and y axes have different scales (common in time series).
2. Markers: Markers maintain their aspect ratio (perfect circles) and fixed pixel size regardless of zoom, which is desired, but they cannot (currently) have dashed borders.

Addingdash support tomarker.line would bridge this gap, allowing for perfect, fixed-size circles with dashed outlines.

Mocks/Designs

Proposed API usage:

importplotly.graph_objectsasgofig=go.Figure(go.Scatter(mode="markers",x=[1,2,3],y=[1,2,3],marker=dict(size=20,color="white",line=dict(color="red",width=2,dash="dash"# <--- Proposed Feature            )        )    ))

Example of what I am trying to achieve:

And this is as close as I can get with the current marker options (solid line):

importplotly.expressaspximportpandasaspdimportnumpyasnpdat=pd.DataFrame(    {"time": [1,2,3,4,5,6],"all": [1,7.5,5.5,4.8,5.5,7],"missing": [False,False,True,True,False,False],    },).assign(value=lambdadf:np.where(df["missing"],np.nan,df["all"]),missing=lambdadf:np.where(df["missing"],df["all"],np.nan),)(px.line()    .add_scatter(x=dat["time"],y=dat["all"],mode="lines",name="all",line=dict(shape="spline",smoothing=1.3,color="teal",width=3,dash="dash"),    )    .add_scatter(x=dat["time"],y=dat["value"],mode="markers",name="value",marker=dict(color="teal",size=30),    )    .add_scatter(x=dat["time"],y=dat["missing"],mode="markers",name="missing",marker=dict(symbol="circle",color="lightgrey",size=30,line=dict(color="teal",width=2,# dash="dash",  # <-- Proposed feature to be added here            ),        ),    )    .update_layout(showlegend=False,xaxis=dict(showgrid=False,showticklabels=False,showline=False,ticks=""),yaxis=dict(showgrid=False,showticklabels=False,showline=False,ticks=""),    )    .show())