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PreprintarXiv licencearXiv

Snapshot plots: displaying summary tables as parallel univariate plots with consistent color highlighting

  • Matthias Schonlau
  • Sandra Huang
  • Tiancheng Yang
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Abstract

For empirical studies, social and health scientists give background characteristics of their sample and summarize them in the famous "Table 1". When treatment/ control groups are present, this table gives summary statistics by group to see whether the background characteristics differ by group. We propose snapshot plots --- parallel univariate plots with consistent highlighting --- to visualize such tables. Compared to "Table 1", such plots are designed to facilitate comparisons of background characteristics --- in particular among groups --- and give more detail on numerical variables. We provide a web app as well as a python implementation of snapshot plots. Snapshot plots arise as edge cases of hammock plots (parallel coordinate plots for mixed categorical/ numerical data). We demonstrate the usefulness of snapshot plots for two "Table 1"s.

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Cite

BibTeXRIS
BibTeX
@misc{schonlau2026snapshot,
  title = {{Snapshot plots: displaying summary tables as parallel univariate plots with consistent color highlighting}},
  author = {Matthias Schonlau and Sandra Huang and Tiancheng Yang},
  howpublished = {arXiv},
  year = {2026},
  month = jul,
  doi = {10.48550/arxiv.2607.28302},
  eprint = {2607.28302},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.28302},
}
RIS
TY  - UNPB
TI  - Snapshot plots: displaying summary tables as parallel univariate plots with consistent color highlighting
AU  - Matthias Schonlau
AU  - Sandra Huang
AU  - Tiancheng Yang
PY  - 2026
DA  - 2026/07/30
PB  - arXiv
DO  - 10.48550/arxiv.2607.28302
UR  - https://arxiv.org/abs/2607.28302
AB  - For empirical studies, social and health scientists give background characteristics of their sample and summarize them in the famous "Table 1". When treatment/ control groups are present, this table gives summary statistics by group to see whether the background characteristics differ by group. We propose snapshot plots --- parallel univariate plots with consistent highlighting --- to visualize such tables. Compared to "Table 1", such plots are designed to facilitate comparisons of background characteristics --- in particular among groups --- and give more detail on numerical variables. We provide a web app as well as a python implementation of snapshot plots. Snapshot plots arise as edge cases of hammock plots (parallel coordinate plots for mixed categorical/ numerical data). We demonstrate the usefulness of snapshot plots for two "Table 1"s.
ER  -