Jupyter Scatter: Interactive Exploration of Large-Scale Datasets
Fuente:
arXiv
Salvato in:
| Autori principali: | , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2024
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866914843301249024 |
|---|---|
| author | Lekschas, Fritz Manz, Trevor |
| author_facet | Lekschas, Fritz Manz, Trevor |
| contents | Jupyter Scatter is a scalable, interactive, and interlinked scatterplot widget for exploring datasets in Jupyter Notebook/Lab, Colab, and VS Code. Its goal is to simplify the visual exploration, analysis, and comparison of large-scale bivariate datasets. Jupyter Scatter can render up to twenty million points, supports fast point selections, integrates with Pandas DataFrame and Matplotlib, uses perceptually-effective default settings, and offers a user-friendly API. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_14397 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Jupyter Scatter: Interactive Exploration of Large-Scale Datasets Lekschas, Fritz Manz, Trevor Human-Computer Interaction Jupyter Scatter is a scalable, interactive, and interlinked scatterplot widget for exploring datasets in Jupyter Notebook/Lab, Colab, and VS Code. Its goal is to simplify the visual exploration, analysis, and comparison of large-scale bivariate datasets. Jupyter Scatter can render up to twenty million points, supports fast point selections, integrates with Pandas DataFrame and Matplotlib, uses perceptually-effective default settings, and offers a user-friendly API. |
| title | Jupyter Scatter: Interactive Exploration of Large-Scale Datasets |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2406.14397 |