How to not show repeated values in a heatmap in plotly express (px.imshow)?

📊 Plotly Python
1

Hello guys,

I’m trying to plot a matrix using a heatmap chart but I would like to avoid repeated values;

When using seaborn we can set a “mask” to avoid showing all values, but I can’t find the equivalent on Plotly / Plotly Express;

I would like to see something like:
enter image description here

But at this moment, it is the below format:

enter image description here

Below is an MWE example of my data structure… Any reference or help to do this will be very welcome

import pandas as pd
import plotly.express as px

heatmap_data=pd.DataFrame(
    {'user1': {'user1': 1,
               'user2': 0.5267109866774764,
               'user3': 0.905914413030722},
    'user2': {'user1': 0.5267109866774764,
              'user2': 1,
              'user3': 0.5160264783692895},
    'user3': {'user1': 0.905914413030722,
              'user2': 0.5160264783692895,
              'user3': 1}
    })
fig = px.imshow(heatmap_data,  zmin=0, zmax=1, 
                text_auto=True, 
                color_continuous_scale="Plasma")
fig

Thank you in advantage

2

Hi @kabure,

The forum search finds some similar topics, this one for example:

3

Hello @kabure,

The initial version https://chart-studio.plotly.com/~empet/3265/correlation-matrix-with-asymmetric-diverging-colorscale/#/} of this kind of heatmap is 7 years old, but I recognized the heatmap due to sns_colormap.
Here is a version using px.imshow:

mport plotly.express as px
import numpy as np

sns_colormap = [[0.0, '#3f7f93'],
 [0.1, '#6397a7'],
 [0.2, '#88b1bd'],
 [0.3, '#acc9d2'],
 [0.4, '#d1e2e7'],
 [0.5, '#f2f2f2'],
 [0.6, '#f6cdd0'],
 [0.7, '#efa8ad'],
 [0.8, '#e8848b'],
 [0.9, '#e15e68'],
 [1.0, '#da3b46']]

z = np.array(np.random.randint(-7, 7, size=(15, 15)), dtype=float)
ids = np.array([[i,j] for i in range(15) for j in range(i, 15)])
I, J = ids.T
z[I, J] = np.nan
fig=px.imshow(z, color_continuous_scale=sns_colormap, origin="upper")
fig.update_layout(width=500, height=500, plot_bgcolor="rgba(0,0,0,0)")
fig.update_traces(xgap=1, ygap=1,   hoverongaps=False)

triangular-heatmap

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