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seaborn: statistical data visualization
Open accessAbstract
seaborn is a library for making statistical graphics in Python.It provides a high-level interface to matplotlib and integrates closely with pandas data structures.Functions in the seaborn library expose a declarative, dataset-oriented API that makes it easy to translate questions about data into graphics that can answer them.When given a dataset and a specification of the plot to make, seaborn automatically maps the data values to visual attributes such as color, size, or style, internally computes statistical transformations, and decorates the plot with informative axis labels and a legend.Many seaborn functions can generate figures with multiple panels that elicit comparisons between conditional subsets of data or across different pairings of variables in a dataset.seaborn is designed to be useful throughout the lifecycle of a scientific project.By producing complete graphics from a single function call with minimal arguments, seaborn facilitates rapid prototyping and exploratory data analysis.And by offering extensive options for customization, along with exposing the underlying matplotlib objects, it can be used to create polished, publication-quality figures.
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“All graphs of our experimental results plot the mean and standard deviation over 3 runs as computed by Seaborn (Waskom, 2021).”
From The Power of Scale for Parameter-Efficient Prompt Tuning (2021) · cites this paper as Waskom, 2021
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Research works printed but not linked: 1
- Wickham, Hadley, ggplot2: Elegant Graphics for Data Analysis, New York, Springer-Verlag, 2016, 978-3-319-24277-4, https://ggplot2.tidyverse.org
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Lovell, C. C., Wilkins, S. M., Thomas, P. A., Schaller, M., Baugh, C. M., Fabbian, G., & Bahé, Y. M. (2021) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stab3221 · Cited by 46
Thürlemann, M., Böselt, L., & Riniker, S. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c01021 · Cited by 46
The mass and size of Herbig disks as seen by ALMA
Stapper, L. M., Hogerheijde, M. R., van Dishoeck, E. F., & Mentel, R. (2021) · Astronomy and Astrophysics · doi:10.1051/0004-6361/202142164 · Cited by 45
Estimation of biological heart age using cardiovascular magnetic resonance radiomics
Raisi‐Estabragh, Z., Salih, A. M., Gkontra, P., Atehortúa, A., Radeva, P. I., Galazzo, I. B., Menegaz, G., Harvey, N. C., Lekadir, K., & Petersen, S. E. (2022) · Scientific Reports · doi:10.1038/s41598-022-16639-9 · Cited by 44
Wu, M.-S., Bodt, T. A., & Tresoldi, T. (2022) · Linguistics of the Tibeto-Burman Area · doi:10.1075/ltba.21019.wu · Cited by 46
Pejkowski, Ł., Seyda, J., Nowicki, K., & Mrozik, D. (2022) · Polymer Testing · doi:10.1016/j.polymertesting.2022.107891 · Cited by 46
How to approach machine learning-based prediction of drug/compound–target interactions
Ataş, H., & Doğan, T. (2023) · Journal of Cheminformatics · doi:10.1186/s13321-023-00689-w · Cited by 48
Cabezudo, A. C., Athanasiou, C., Tsengenes, A., & Wade, R. C. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00950 · Cited by 46
Moore, P. K., Anderson, K. C., McManus, S. A., Tu, T.-H. C., King, E. M., Mould, K. J., Redente, E. F., Henson, P. M., Janssen, W. J., & McCubbrey, A. L. (2023) · American Journal of Physiology-Lung Cellular and Molecular Physiology · doi:10.1152/ajplung.00223.2022 · Cited by 49
Antigen discrimination by T cells relies on size-constrained microvillar contact
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Using [Ne v]/[Ne iii] to Understand the Nature of Extreme-ionization Galaxies
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Clonally heritable gene expression imparts a layer of diversity within cell types
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A statistical–parametric model of tropical cyclones for hazard assessment
Arthur, W. C. (2021) · Natural hazards and earth system sciences · doi:10.5194/nhess-21-893-2021 · Cited by 45
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Chu, L., Qu, Y.-X., An, Y., Hou, L., Li, J., Li, W., Fan, G., Song, B., Li, E., Zhang, L., et al. (2022) · Cell Death and Disease · doi:10.1038/s41419-022-04601-6 · Cited by 47
The OPS-SAT benchmark for detecting anomalies in satellite telemetry
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Chemparathy, A., Le Guen, Y., Chen, S., Lee, E.-G., Leong, L., Gorzynski, J. E., Jensen, T. D., Ferrasse, A., Xu, G., Xiang, H., et al. (2024) · Neuron · doi:10.1016/j.neuron.2024.01.008 · Cited by 43
High [O iii ]/[C ii ] surface brightness ratios trace early starburst galaxies
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Metadata
- Authors
- Waskom, M.
- Affiliations
- New York University (US)
- Corresponding author
- Waskom, Michael
- ORCID
- Waskom, Michael
- Venue
- Journal of Open Source Software
- Publisher
- The Open Journal
- Published
- 2021-04-06
- Volume
- 6
- Issue
- 60
- Pages
- 3021
- ISSN
- 2475-9066 (ISSN-L)
- OpenAlex
- W3128261063
- Cited by
- 7,310
- References
- 6
- Citations by year
- 2026: 1498 · 2025: 1881 · 2024: 1517 · 2023: 1172 · 2022: 805 · 2021: 380
- FWCI
- 349.32
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- The Journal of Open Source Software (publishedVersion, cc-by)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, other-oa)
- Astrophysics Source Code Library
- Zenodo (CERN European Organization for Nuclear Research) (other-oa)
- Funders
- National Science Foundation (0801700)
- Simons Foundation (527794)
- Simons Society of Fellows
- Topics
- Physical Sciences › Computer Science › Software › Computational Physics and Python Applications
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Data Visualization and Analytics
- Physical Sciences › Mathematics › Statistics and Probability › Data Analysis with R
- Keywords
- seaborn, statistical graphics, Python library, exploratory data analysis, data visualization, publication-quality figures
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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