Hello all,
I am attempting to generate a basic Splom graph, however, rather than having a standard color by row, I want to color individual cells. Thus, the coloring will be specific per subgraph of the Splom. I am doing this specifically to look at imputed values to ensure that the imputed data matches what is expected.
colors = pd.DataFrame(np.zeros(df.shape), columns = df.columns)
for val in missing_values:
colors.loc[val] = 1
fig = go.Figure()
fig.add_trace(
go.Splom(
dimensions = [
dict(label = column, values = df[column]) for column in df.columns
],
marker = dict(
color = colors
)
)
)
fig.update_layout(
title = "test"
)
offline.plot(fig)
This seems to kinda work, in that it shows most values where the color category is 0 (but not all). However, it does not show category 1 values at all and if there are too many category 1 values the splom does not show anything.
Graph with color categories:
Graph without color categories: same data.
Any ideas?