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predict-idlab/plotly-resampler

Visualize large time series data with plotly.py observed · 2026-08-28

github.com/predict-idlab/plotly-resampler · homepage · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

69/100

  • Activity 99
  • Release rhythm 13
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1747
  • days_rel: 369
  • days_push: 7
  • n_releases_24m: 1

Full methodology

Adoption not part of the score

1209 stars · 75 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library that adds dynamic resampling to Plotly figures so large time series datasets remain interactive when panning and zooming. It aggregates data relative to the current graph view via callbacks, keeping rendering fast.

Use cases

  • visualize millions of time series points in plotly without browser lag
  • make plotly dash charts responsive when zooming and panning large datasets
  • downsample time series data dynamically for interactive plotting
  • plot sensor or log data with many points in python
  • speed up plotly line charts with large sequential data

When to choose

  • you use plotly or plotly dash and need to plot very large time series interactively
  • your plotly figures are slow or freeze due to too many data points

When to avoid

  • you need a full dashboard with cross-filtering and many trace types - consider the successor FlexViz
  • your datasets are small enough that plain plotly is already fast

Facets

library · maturity maintenance

data-visualization charts data-visualization data-science time-series python plotly time-series resampling dash interactive-visualization

3 sources

Member repositories

RepositoryRoleHealth v2
predict-idlab/plotly-resamplermain69

For agents

markdown · JSON · MCP: product_card(name="predict-idlab/plotly-resampler")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem