# How to plot ~10 billion datapoint time series efficiently?

**URL:** <https://discourse.julialang.org/t/how-to-plot-10-billion-datapoint-time-series-efficiently/81228>\
**Category:** Visualization\
**Tags:** question, plotting, diffeq\
**Created:** [May 18, 2022, 1:09am UTC](https://discourse.julialang.org/t/how-to-plot-10-billion-datapoint-time-series-efficiently/81228 "2022-05-18T01:09:30Z")\
**Posts on this page:** 1\
**Showing post:** 13

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**Author:** ![stevengj](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/stevengj/32/71_2.png) [@stevengj](https://discourse.julialang.org/u/stevengj)\
**Post date:** [May 18, 2022, 1:50pm UTC](https://discourse.julialang.org/t/how-to-plot-10-billion-datapoint-time-series-efficiently/81228/13 "2022-05-18T13:50:03Z")

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> [@joa-quim](#):
>
> It makes no sense to plot that many points.

There are a lot of different algorithms for downsampling huge timeseries datasets for visualization. See [this post](https://discourse.julialang.org/t/plotting-image-data-in-julia-is-much-slower-than-matlab/79660/18), for example (including some code).

If the downsampling algorithm is local (as is the case in the linked example above), you can process the dataset in chunks if the whole thing doesn’t fit into memory at once.

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