The DOI matches its Crossref record.
Altair: Interactive Statistical Visualizations for Python
Open accessAbstract
Altair is a declarative statistical visualization library for Python.Statistical visualization is a constrained subset of data visualization focused on the creation of visualizations that are helpful in statistical modeling.The constrained model of statistical visualization is usually expressed in terms of a visualization grammar (Wilkinson, 2005) that specifies how input data is transformed and mapped to visual properties (position, color, size, etc.).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Starr, T. N., Greaney, A. J., Hilton, S. K., Ellis, D., Crawford, K. H. D., Dingens, A. S., Navarro, M. J., Bowen, J. E., Tortorici, M. A., Walls, A. C., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.012 · Cited by 1,956
Shifting mutational constraints in the SARS-CoV-2 receptor-binding domain during viral evolution
Starr, T. N., Greaney, A. J., Hannon, W. W., Loes, A. N., Hauser, K., Dillen, J. R., Ferri, E., Farrell, A. G., Dadonaite, B., McCallum, M., et al. (2022) · Science · doi:10.1126/science.abo7896 · Cited by 303
An antibody-escape estimator for mutations to the SARS-CoV-2 receptor-binding domain
Greaney, A. J., Starr, T. N., & Bloom, J. D. (2022) · Virus Evolution · doi:10.1093/ve/veac021 · Cited by 147
Interactive Model Cards: A Human-Centered Approach to Model Documentation
Crisan, A., Drouhard, M., Vig, J., & Rajani, N. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3531146.3533108 · Cited by 101
Gerbin, K. A., Grancharova, T., Donovan-Maiye, R. M., Hendershott, M. C., Anderson, H. G., Brown, J. M., Chen, J., Dinh, S. Q., Gehring, J. L., Johnson, G. R., et al. (2021) · Cell Systems · doi:10.1016/j.cels.2021.05.001 · Cited by 59
Metadata
- Authors
- VanderPlas, J., Granger, B., Heer, J., Moritz, D., Wongsuphasawat, K., Satyanarayan, A., Lees, E., Timofeev, I., Welsh, B., & Sievert, S.
- Venue
- Journal of Open Source Software
- Publisher
- The Open Journal
- Published
- 2018-12-10
- Volume
- 3
- Issue
- 32
- Pages
- 1057
- ISSN
- 2475-9066 (ISSN-L)
- OpenAlex
- W2903675476
- Cited by
- 219
- References
- 0
- FWCI
- 8.35
- Type
- journal article
- Language
- en
- Open access
- diamond
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Altair: Interactive Statistical Visualizations for Python. https://app.cochat.ai/papers/10.21105/joss.01057
- The paper
- VanderPlas, J., Granger, B., Heer, J., Moritz, D., Wongsuphasawat, K., Satyanarayan, A., Lees, E., Timofeev, I., Welsh, B., & Sievert, S. (2018). Altair: Interactive Statistical Visualizations for Python. Journal of Open Source Software. https://doi.org/10.21105/joss.01057
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.