how to automate annotations on 3d scatter plotly plot

Question

here , they show that to add annotations to a 3d scatter plot one can use the following code:

fig.update_layout(
    scene=dict(
        xaxis=dict(type="date"),
        yaxis=dict(type="category"),
        zaxis=dict(type="log"),
        annotations=[
        dict(
            showarrow=False,
            x="2017-01-01",
            y="A",
            z=0,
            text="Point 1",
            xanchor="left",
            xshift=10,
            opacity=0.7),
        dict(
            x="2017-02-10",
            y="B",
            z=4,
            text="Point 2",
            textangle=0,
            ax=0,
            ay=-75,
            font=dict(
                color="black",
                size=12
            ),
            arrowcolor="black",
            arrowsize=3,
            arrowwidth=1,
            arrowhead=1),
        dict(
            x="2017-03-20",
            y="C",
            z=5,
            ax=50,
            ay=0,
            text="Point 3",
            arrowhead=1,
            xanchor="left",
            yanchor="bottom"
        )]
    ),
)

That works fine, but it's too manual. I'd like to automate that process because I have too many annotations to write them manually.

This is my attempt:

for i in range(annotations):
    fig.update_layout(
        scene=dict(
            xaxis=dict(type='linear'),
            yaxis=dict(type='linear'),
            zaxis=dict(type='linear'),
            annotations=[
            dict(
                x=anx[i],
                y=any[i],
                z=anz[i],
                text='F')]))

However, when plotted, it only shows the last annotation, so it's rewriting the annotations, instead of writing a new one every iteration. Does anyone know how to automate the annotation process? In my case, every annotation has the same text, but the coordinates are different. Also, I am not including annotations for every point on the plot, just some.

Answer 1

fig.update_layout() does not work like list.append , where every time it's called it adds something to the already existing collection. It will update the configuration of the layout based on the arguments provided and doing so in a loop will only show you whatever you set it to in the last iteration.

The annotations arguments takes a list of dicts, one for each annotation. You can automate it like this

ann = [dict(x=x, y=y, z=z, text='F') for x, y, z in zip(anx, any, anz)]
fig.update_layout(
    scene=dict(
        xaxis=dict(type="date"),
        yaxis=dict(type="category"),
        zaxis=dict(type="log"),
        annotations=ann
    )
)

---

I also suggest you find a different name for the y coordinates of the annotated points, because any already has a function in Python and by reassigning it you take that away.