Set different colors based on categories when box plotting in Plotly

Question

Assume having the data:

import pandas as pd
df = pd.DataFrame(
    {
        "val": np.random.normal(0, 1, size=100),
        "cat": np.random.choice(["a", "b"], size=100),
    }
)

Next, visualize a box plot:

from plotly import graph_objects as go
fig = go.Figure()
fig.add_trace(go.Box(y=df["val"], x=df["cat"], boxmean="sd",))

I'm using go.Box since I want to visualize the STD. This yields:

How can I set different colors of for the left and right box plots depending on the category?

FWIW, here's another question I had related to the same bigger challenge I have: stackoverflow.com/q/72110370/671013 — Dror
– Dror, Commented May 4, 2022 at 9:20

r-beginners · Accepted Answer · 2022-05-04 10:10:37Z

1

You can change the color by looping through each category variable.

for c in df['cat'].unique():
    dff = df[df['cat'] == c]
    fig.add_trace(go.Box(y=dff["val"], x=dff["cat"], boxmean="sd", name=c))

answered May 4, 2022 at 10:10

r-beginners

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1 Comment

Dror Over a year ago

That worked nicely! It is a little counter intuitive for me that calling fig.add_trace twice behaves this way. I was expecting some sort of overwrite. But it is actually appending (adding as the name suggest) to the figure. It seems that the order a, b is kept regardless of their order in the loop. Interesting. Now I'm left with this.

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