Thanks for providing such a powerful tool!
I have a data frame of size 7486 rows x 960 columns. I am plotting the data with facet rows of 8 and columns of 2. Each plot has 3 categories and each category a group of 20 time series. Thus, each of the 16 contains 60 time series. I am plotting the data frame with plotly express lines, see snippet below. As renderer, I am using WebGL.
My impression is that plotly express line is rather slow. It uses a couple of minutes. Is this to be expected for this amount of data? Once it is rendered, the figures are responsive, though.
Thanks for any advice.
fig = px.line(error_per_type, facet_col=“eval_type”, facet_row=“data_set”, color=“est_type”, line_group=“run”, hover_name=“est_type”, render_mode=fig_renderer)
fig.update_traces(mode=“lines+markers”, line=dict(width=1), marker=dict(size=3), connectgaps=True)