plotly / plotly/plotly.py

Unify hovertemplate title cannot be edited.

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bug P3 sev-3
Dominant language
Python
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Description

Hello

It seems that we cannot modify the title of the hovertemplate when the chart uses a unify hovermode whenever the axis has not a date type.

Here a short example with 2 scatter plots, the first one with a date axis and the second is linear:

import numpy as np
import pandas as pd
from plotly.subplots import make_subplots

dates = pd.date_range("2022-01-01", "2022-03-01")
values = np.random.randint(0, 10, len(dates))

fig = make_subplots(cols=2) 
fig.add_scatter(x=dates, y=values, row=1, col=1)
fig.add_scatter(x=values, y=values, mode="markers", row=1, col=2)

fig.update_traces(hovertemplate="%{y}<extra></extra>")
fig.update_xaxes(row=1, col=1, hoverformat=" ")
fig.update_xaxes(row=1, col=2, type="linear", hoverformat=" ")
fig.update_layout(hovermode="x unified")

fig.show()

image

If you force the second scatter to be a date type, the hovertemplate title is removed with the workaround hoverformat=" ". However, it only works for date axis.

Here some references/related issues:
https://github.com/plotly/plotly.py/issues/4278
https://community.plotly.com/t/customizing-text-on-x-unified-hovering/39440/18
https://community.plotly.com/t/pass-nothing-or-disable-x-axis-hoverformat/67496

plotly version = 5.18.0

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Run the supplied Python reproduction with plotly 5.18.0 and compare the date-axis and linear-axis cases. Read related issue #4278 and the linked community discussions; done means unified hover on a linear axis permits the hovertemplate title to be removed or customized without forcing a date axis, with regression coverage.

Written by the indexing model from the issue text.

Assessment

Tech stack
numpy, pandas, python
Domain
data-visualization
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
38/100

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