Annotations varying by subplot with plotly-express?

Question

Suppose I want to make a subplot like this in which each facet has its own y scale:

import plotly.express as px

fig = px.scatter(px.data.iris(), x='sepal_length', y='sepal_width', facet_col='species')


def update(y):
    y.update(matches=None)
    y.showticklabels=True

fig.for_each_yaxis(update)

Now suppose I want to add some annotations, and the position is going to vary according to the faceted variable, and I have this in a dataframe:

If I was using plotnine/ggplot I could do it like this:

ggplot(df_iris, aes(x='sepal_length', y='sepal_width')) + geom_point() + facet_wrap("~species", scales="free_y") + geom_text(aes(x='x', y='y', label='label'), data=df_text) 

Is it possible to do this in plotly? I got pretty bogged down mucking around with subplots and annotations, I know you can add annotations to a subplot, but you have to know the row and column number in order to do that, and I'm not sure how I can map the facet variable (species) to the subplot row/column indexes.

Thanks :)

Answer 1

I'm not sure if this is the best way to do it but you can try the following

import plotly.express as px
import pandas as pd

df_text = pd.DataFrame({"species":["setosa", "versicolor", "virginica"],
                        "x": [7, 7, 5],
                        "y": [3, 2, 3.5],
                        "label":["label1", "label2", "label3"]})

fig = px.scatter(px.data.iris(),
                 x='sepal_length',
                 y='sepal_width',
                 facet_col='species')

# Here are your annotations
data = px.scatter(df_text,
                  x="x",
                  y="y",
                  text="label",
                  facet_col='species')\
          .update_traces(mode="text")["data"]

def update(y):
    y.update(matches=None)
    y.showticklabels=True
    
fig.for_each_yaxis(update)

for trace in data:
    fig.add_trace(trace)

fig.show()