Plotly Rangebreaks Make Chart Mega-Slow, Mega Lag

📊 Plotly Python
1

Hello, using the implementation here for x-axis rangebreaks… If you use say 10+ years of data the plots get ultra laggy to the point where they are virtually unusable. I really like the implementation below because you can get rid of candlestick gaps but at this point based on how laggy the chart becomes I think the cost outweighs the benefit. Does anyone have an idea how I might implement the below without sacrificing the performance of the rendering and scrolling over the chart itself?

Thank you very much.

import plotly.express as px
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')

fig = px.scatter(df, x='Date', y='AAPL.High', range_x=['2015-12-01', '2016-01-15'],
                 title="Hide Weekend and Holiday Gaps with rangebreaks")
fig.update_xaxes(
    rangebreaks=[
        dict(bounds=["sat", "mon"]), #hide weekends
        dict(values=["2015-12-25", "2016-01-01"])  # hide Christmas and New Year's
    ]
)
fig.show()
1 Like
2

I will try to bring this issue from the dead… I face a similar problem and the time it takes for the plot to render when using the rangebreaks option is very long. Furthermore, navigating in the rendered image afterwards (e.g. zooming in a certain time range) is very slow as well.

FWIW, I use the plotly.graph_objects.Candlestick.

Is there maybe an option to disable the missing dates filling logic? In other words, ask plotly to only plot that available data.

Related: #5630