Axis labels are not shown for all subplots when using plotly express, facets and string labels
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Description
Problem summary
Whenever I have the following combination:
- plotly express
- facet plots
- labels used for axis are strings
The first subplot shows the axis labels properly, but all following subplots don't show labels at all:

If the axis labels are numbers, there is no problem.
From a comment of the initial issue I opened I now know that fig.update_traces(bingroup='x2', row=1, col=2) can work around the issue, but that's not a permanent solution.
Reproducible example
I originally created these plots in Python (plotly 5.18.0) and then used the .to_json(pretty=True) method to obtain the Javascript for the codepens.
- Manually building up the figure using
graph_objectsandmake_subplotsI get the following working visualization: https://codepen.io/sl1970/pen/BaMvNbp - If I use the convenient
plotly.expresslibrary and thefacetargument I get this broken visualization (no axis labels on the right plot): https://codepen.io/sl1970/pen/jOdXPoa
Original Python code
If necessary, this is the original Python code I used
import pandas as pd
import plotly.express as px
from plotly.subplots import make_subplots
import plotly.graph_objects as go
df = pd.DataFrame(
{
"age": { "0": "Adult", "1": "Adult", "2": "Adult", "3": "Adult", "4": "Adult", "5": "Kid", "6": "Kid", "7": "Kid", "8": "Kid", "9": "Kid", },
"favourite_food": { "0": "Pizza", "1": "Noodles", "2": "Pizza", "3": "Pizza", "4": "Pizza", "5": "Burger", "6": "Pancake", "7": "Noodles", "8": "Pizza", "9": "Pancake", },
"favourite_drink": { "0": "Beer", "1": "Tea", "2": "Beer", "3": "Wine", "4": "Coffee", "5": "Coffee", "6": "Water", "7": "Beer", "8": "Tea", "9": "Wine", },
"max_running_speed": { "0": 4.7362803248, "1": 16.7084927714, "2": 8.1135697835, "3": 1.0704264989, "4": 4.6330187561, "5": 6.331593807, "6": 16.5221040135, "7": 3.2256763127, "8": 4.3084468631, "9": 6.3677742299, },
"number_of_bicycles": { "0": 4, "1": 2, "2": 1, "3": 3, "4": 4, "5": 3, "6": 3, "7": 3, "8": 4, "9": 2, },
}
)
df.set_index("age", inplace=True)
working = make_subplots(rows=1, cols=2, subplot_titles=["Food", "Drink"])
working.add_trace( go.Histogram( histfunc="count", histnorm="percent", x=df.loc["Adult"].favourite_food, name="Adult", legendgroup="Adult", ), row=1, col=1, )
working.add_trace( go.Histogram( histfunc="count", histnorm="percent", x=df.loc["Kid"].favourite_food, name="Kid", legendgroup="Kid" ), row=1, col=1, )
working.add_trace( go.Histogram( histfunc="count", histnorm="percent", x=df.loc["Adult"].favourite_drink, name="Adult", legendgroup="Adult", ), row=1, col=2, )
working.add_trace( go.Histogram( histfunc="count", histnorm="percent", x=df.loc["Kid"].favourite_drink, name="Kid", legendgroup="Kid" ), row=1, col=2, )
working.show()
broken = px.histogram(
df,
x=["favourite_food", "favourite_drink"],
facet_col="variable",
color=df.index,
barmode="group",
histnorm="percent",
text_auto=".2r",
).update_xaxes(matches=None, showticklabels=True).update_yaxes(matches=None, showticklabels=True)
broken.show()
Related
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the plotly.express histogram and facet handling described in the reproducible Python example, then compare its generated figure with the working make_subplots example and linked CodePens. Done means categorical string axis labels render on every facet without requiring a bingroup workaround, with a regression test covering the case.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pandas, python
- Domain
- data-visualization
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100