I am generating a correlation visual with some emphasis on sparsity, i.e. if n <=30. i.e. for those points where the answer to statistical significance is simply no, I am hoping to keep those out of the visual.
Is there a way to do this with heatmap2d, or density heatmaps, etc? Iām in python but hoping for something easy 
trace1 = go.Histogram2d(
x=edte_quant.age,
y=edte_quant.time_spent_on_website,
z=np.round(edte_quant.status, 2),
histfunc="avg",
autobiny=False,
ybins=dict(size=400),
texttemplate="%{z}",
colorscale=SCALE_3 )
f = layout_func(go.Figure(data=[trace1]).update_layout({"title": {"text": "Age by Time on Site, Color as Conversions"}}))
f
The ideal, as you know, is that those bright red "1"s at the top left are no longer in the plot,
Let me know if possible. thank you!
