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🖍️ updating readme
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README.md

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<p align="center">
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<a href="#readme">
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<img alt="Plotly-Resampler logo" src="https://raw.githubusercontent.com/predict-idlab/plotly-resampler/main/docs/sphinx/_static/logo.svg" width=65%>
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<img alt="Plotly-Resampler logo" src="https://raw.githubusercontent.com/predict-idlab/plotly-resampler/main/mkdocs/static/logo.svg" width=65%>
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</a>
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[![codecov](https://img.shields.io/codecov/c/github/predict-idlab/plotly-resampler?logo=codecov)](https://codecov.io/gh/predict-idlab/plotly-resampler)
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[![Downloads](https://pepy.tech/badge/plotly-resampler)](https://pepy.tech/project/plotly-resampler)
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[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?)](http://makeapullrequest.com)
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[![Documentation](https://github.com/predict-idlab/plotly-resampler/actions/workflows/deploy-docs.yml/badge.svg)](https://github.com/predict-idlab/plotly-resampler/actions/workflows/deploy-docs.yml)
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[![Documentation](https://img.shields.io/badge/documentation-informational)](https://predict-idlab.github.io/plotly-resampler/latest)
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[![Testing](https://github.com/predict-idlab/plotly-resampler/actions/workflows/test.yml/badge.svg)](https://github.com/predict-idlab/plotly-resampler/actions/workflows/test.yml)
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[Plotly](https://github.com/plotly/plotly.py) is an awesome interactive visualization library, however it can get pretty slow when a lot of data points are visualized (100 000+ datapoints). This library solves this by downsampling (aggregating) the data respective to the view and then plotting the aggregated points. When you interact with the plot (panning, zooming, ...), callbacks are used to aggregate data and update the figure.
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![basic example gif](https://raw.githubusercontent.com/predict-idlab/plotly-resampler/main/docs/sphinx/_static/basic_example.gif)
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![basic example gif](https://raw.githubusercontent.com/predict-idlab/plotly-resampler/main/mkdocs/static/basic_example.gif)
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In [this Plotly-Resampler demo](https://github.com/predict-idlab/plotly-resampler/blob/main/examples/basic_example.ipynb) over `110,000,000` data points are visualized!
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