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Description
Two situations where layout images referenced to data can disappear:
- When one of the size parameters is far, far larger than necessary. Normally (with the default
sizing: 'contain'
) the aspect ratio of the image is preserved, so in the rectangle described bysizex
andsizey
, one of those is limiting and the non-limiting size can be increased indefinitely with no visible effect. This has a limit though: if you make it something like a million times too big, the image abruptly disappears. (this one is from an example by @celia-plotly) - On a date axis, in data arrays integer numbers and integer strings are both treated as years, but in layout images only integer strings are treated as years; integer numbers are treated as milliseconds since 1970 (and with the local UTC offset no less 🤦)
Here's a working example:
import dash
from dash import dcc
import plotly.graph_objects as go
import pandas as pd
# Create a Dash app
app = dash.Dash(__name__)
df = pd.DataFrame.from_records([
{"Year": 2008, "Tickets Sold": 8000000},
{"Year": 2009, "Tickets Sold": 9000000},
{"Year": 2010, "Tickets Sold": 5000000},
{"Year": 2011, "Tickets Sold": 5000000},
{"Year": 2012, "Tickets Sold": 7000000},
{"Year": 2013, "Tickets Sold": 5000000},
{"Year": 2014, "Tickets Sold": 7000000},
])
fig = go.Figure()
fig.add_trace(go.Scatter(x=df["Year"], y=df["Tickets Sold"]))
for j, row in df.iterrows():
fig.add_layout_image(
dict(
source="https://upload.wikimedia.org/wikipedia/commons/8/8a/Plotly-logo.png",
xref="x",
yref="y",
x=row["Year"],
y=row["Tickets Sold"],
sizex=1,
sizey=1000000,
xanchor="center",
yanchor="middle",
)
)
# Define the app layout
app.layout = dcc.Graph(figure=fig, style={"height": "50vh"})
if __name__ == "__main__":
app.run(debug=True)
And if you make sizex
bigger, even as high as 10000
, nothing changes. But go up to 100000
and the images disappear.
For the date flavor: add fig.update_xaxes(type="date")
and sizex=1000*3600*24*365
(one year in msec), the images disappear. You can find them if you zoom out and back in around year 1970. But if you stringify, ie x=str(row["Year"])
, they reappear atop the data points again.