[BUG] go.Heatmap making values NaN? px.imshow is correct

Issue: For some reason, using go.Heatmap causes values to be dropped/excluded from the plot. I’m guessing they’re being made NaN and filtered out somehow? px.imshow correctly includes all values.

See here for the output from the code below: output

Versions: pandas: 1.40 plotly: 5.8.0

Reproducible code:

import pandas as pd
import plotly.express as px
import plotly.graph_objects as go

df = pd.DataFrame([[438, 160, 2, 3, 2]], index=["AB"], columns=["100015", "500015", "500030", "500039", "500078"])
print(df)
fig1 = go.Figure(
    data=go.Heatmap(z=df.values, x=df.index, y=df.columns, colorbar=dict(title="count"), hoverongaps=False)
)
fig1.show()
fig2 = px.imshow(
    df.values.T,
    labels=dict(color="count"),
    x=df.index,
    y=df.columns,
)
fig2.show()

[nicolaskruchten]

It would be very challenging to implement this kind of warning at the graph_objects level unfortunately… That said, px.imshow actually does provide this warning (try px.imshow(df.values, x=df.index, y=df.columns)) and this kind of thing is one of the reasons it’s generally recommended to use px wherever possible 😃

[kmcentush]

Oh, I finally get it, thank you so much. Setting the axis names with different dimensions than the raw data cuts things off.

Do you think it’s worth adding some sort of warning when this happens (i.e. axis dimensions not aligning with input data)? Happy to close the issue if not.