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.