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https://github.com/CamDavidsonPilon/tdigest

distributed-computing estimate mapreduce percentile pyspark python quantile

Score: 21.34255023867491

Last synced: about 16 hours ago
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Repository metadata:

t-Digest data structure in Python. Useful for percentiles and quantiles, including distributed enviroments like PySpark


Owner metadata:


GitHub Events

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Committers metadata

Last synced: 7 days ago

Total Commits: 95
Total Committers: 18
Avg Commits per committer: 5.278
Development Distribution Score (DDS): 0.379

Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0

Name Email Commits
Cameron Davidson-Pilon c****n@g****m 59
AJ West a****t@g****m 6
Guilherme Kunigami k****i@f****m 4
JonathanZailer 5****r 4
Paul Jimenez p****j@p****g 4
Mats Julian Olsen m****s@p****t 3
Peter Cotton p****r@P****l 2
Yang Wang y****g@a****m 2
Peter Cotton 5****n 2
Bradford Toney b****y@g****m 1
DataAI d****w@t****m 1
Dave Matthews d****s@g****m 1
Olivier Grisel o****l@e****g 1
Vivien Maisonneuve v****n@s****o 1
Mats Julian Olsen (****) 1
Dave Matthews d****s@s****t 1
Vladimir Mihailenco v****v@g****m 1
Víctor Zabalza v****a@g****m 1

Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 36
Total pull requests: 31
Average time to close issues: 3 months
Average time to close pull requests: about 1 month
Total issue authors: 26
Total pull request authors: 16
Average comments per issue: 2.06
Average comments per pull request: 2.55
Merged pull request: 27
Bot issues: 0
Bot pull requests: 0

Past year issues: 0
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 0
Past year pull request authors: 0
Past year average comments per issue: 0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/CamDavidsonPilon/tdigest

Top Issue Authors

  • CamDavidsonPilon (7)
  • microprediction (4)
  • crepererum (2)
  • MaxHalford (1)
  • kat-grayson (1)
  • vmihailenco (1)
  • IntegersOfK (1)
  • pjz (1)
  • Jackmrzhou (1)
  • MatufA (1)
  • DataAI (1)
  • CreekLou (1)
  • ovanes (1)
  • kakila (1)
  • asottile (1)

Top Pull Request Authors

  • CamDavidsonPilon (9)
  • pjz (4)
  • mewwts (2)
  • JonathanZailer (2)
  • d18s (2)
  • kunigami (2)
  • DataAI (1)
  • IntegersOfK (1)
  • vmihailenco (1)
  • zblz (1)
  • vivienm (1)
  • tkluck-booking (1)
  • microprediction (1)
  • bluemoon (1)
  • wangyangcharles (1)

Top Issue Labels

Top Pull Request Labels


Package metadata

pypi.org: tdigest

T-Digest data structure

  • Homepage: https://github.com/CamDavidsonPilon/tdigest
  • Documentation: https://tdigest.readthedocs.io/
  • Licenses: MIT
  • Latest release: 0.4.0 (published about 11 years ago)
  • Last Synced: 2026-08-24T13:32:49.259Z (1 day ago)
  • Versions: 14
  • Dependent Packages: 13
  • Dependent Repositories: 41
  • Downloads: 243,306 Last month
  • Docker Downloads: 34
  • Rankings:
    • Downloads: 0.716%
    • Dependent packages count: 0.794%
    • Dependent repos count: 2.285%
    • Average: 2.882%
    • Stargazers count: 3.371%
    • Docker downloads count: 4.319%
    • Forks count: 5.805%
  • Maintainers (1)
proxy.golang.org: github.com/CamDavidsonPilon/tdigest

proxy.golang.org: github.com/camdavidsonpilon/tdigest

guix: python-tdigest

Python implementation of the t-digest data structure

  • Homepage: https://github.com/CamDavidsonPilon/tdigest
  • Documentation: https://git.savannah.gnu.org/cgit/guix.git/tree/gnu/packages/digest.scm#n40
  • Licenses: expat
  • Latest release: 0.6.0.1 (published 5 months ago)
  • Last Synced: 2026-05-01T13:41:47.722Z (4 months ago)
  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Rankings:
    • Dependent repos count: 0.0%
    • Dependent packages count: 0.0%
    • Average: 100%

Dependencies

requirements.txt pypi
  • accumulation_tree >=0.5.0
  • pyudorandom >=1.0.0
setup.py pypi
  • accumulation_tree *
  • pyudorandom *