More efficient way of producing heatmap-like images grids

📊 Plotly Python
1

I’m making an heatmap-like figure that is basically a NxM grid of small icons

newplot
newplot1944×1050 230 KB

The code I’m using to produce this is sub-optimal, because it needs to iterate through every row and column to place the images.

for i, var in enumerate(rows): # these are the rows of the plots (members)
    for _, row in df.iterrows(): # These are the columns of the plot (time)
        fig.add_layout_image(
            dict(
                source=Image.open(row["icons"]),
                x=row["time"],
                y=y_positions[i],
                sizex=12 * 24 * 10 * 60 * 100,
                sizey=.5,
                xref="x",
                yref="y",
                xanchor="center",
                yanchor="middle",
            ),
        )

Note that I also have to fiddle around with sizex as the xaxis is in time units!

This code takes a while to finish, sometimes longer than a minute.

Isn’t there a better way to achieve this?