R Observatory: Metrics for anomalize version 0.3.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

anomalize

0.3.0Package record

Tidy Anomaly Detection

0packages dependsuggested by 2

24.4Kdownloads / year

79.0%test coverage

13/13flavors OK

Overview

About

Maintained by Matt DanchoCRAN page ↗GitHub ↗Issues ↗

The 'anomalize' package enables a "tidy" workflow for detecting anomalies in data. The main functions are time_decompose(), anomalize(), and time_recompose(). When combined, it's quite simple to decompose time series, detect anomalies, and create bands separating the "normal" data from the anomalous data at scale (i.e. for multiple time series). Time series decomposition is used to remove trend and seasonal components via the time_decompose() function and methods include seasonal decomposition of time series by Loess ("stl") and seasonal decomposition by piecewise medians ("twitter"). The anomalize() function implements two methods for anomaly detection of residuals including using an inner quartile range ("iqr") and generalized extreme studentized deviation ("gesd"). These methods are based on those used in the 'forecast' package and the Twitter 'AnomalyDetection' package. Refer to the associated functions for specific references for these methods.

Changes in 0.3.0

Prepare for supercession by timetk. Note that anomalize R package will be maintained for backwards compatibility. Users may wish to add these 2 lines of code to existing codebases that use the legacy anomalize R package:

``` r

library(anomalize)

anomalize <- anomalize::anomalize

plot_anomalies <- anomalize::plot_anomalies

```

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("anomalize", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("business-science/anomalize")

Development version from business-science/anomalize. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-anomalize

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-anomalize

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-anomalize

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 3.9 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-09-08
ERROR12 OK, 1 ERROR2026-09-07
OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09

Show 2 earlier changesHide 2 earlier changes

ERROR12 OK, 1 ERROR2026-06-08
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.3.0

READMEYes · 461 wordsVignettesYes · 3 · dynamicNEWSYes · 100% structured · mentions 0.3.0Citation fileNo

Help pages: 14includes a package overview page
Examples that run: 75%9 run in a plain check · 3 never run
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 92%
Help pages citing references: 29%

Vignettes (3)

How these are measured

Downloads

24.4K

CRAN downloads in the past year

Rank #3,792 · ~67/day · ~2K/mo

Releases R versions

Daily download trend is not available in this view yet.

85830 days

2.5K90 days

24.4K1 year

Compare downloads with other packages →

Also on228 r2u52 autocran215 c2d4u

How downloads are counted

Repository

business-science/anomalize ↗Organization: business-science

337Stars

61Forks

35Open issues

3Open PRs

0Releases

125Commits

7Commit identities

detect-anomaliesdecompositioniqrtime-seriesanomaly-detectionanomalyr-package

125 commits · Last activity 2023-12-28 · 0% stars, 30d · Default branch at 0.3.0.9000, ahead of CRAN 0.3.0 (checked 2026-10-18)

Responsiveness

How these are sampled

PRs merged (all time): 90%
Median days to close, 50 most recently updated closed issues: 3
Median days to close, 50 most recently updated closed PRs: 0

Stars over time

2025-10-15 · 3382026-08-21 · 337

How these are measured

PracticesBeta

11 development-tooling and community-health practices detected across 6 families in the upstream repository

Checks run against github.com/business-science/anomalize on 2026-10-18.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Docs source (4)

README.Rmdpkgdown

GitHub Pages site last deployed 2023-12-28 · The repository has a site deploy workflow

Coverage (1)

Coverage reporting (Codecov)

Reproducibility and dev environment (1)

data-raw/

Show all practicesHide 2 practices

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

19 external dependencies (excludes base and recommended)

Installing anomalize adds 123 packages (66 with compiled code, 106 MB of source tarballs). Heaviest: BH 14 MB, stringi 11 MB, ggplot2 6.0 MB.

Depends (1)

R >= 3.0.0

Imports (10)

dplyr glue timetk sweep tibbletime purrr rlang tibble tidyr ggplot2

LinkingTo (0)

none

Suggests (9)

tidyverse tidyquant stringr testthat covr knitr rmarkdown devtools roxygen2

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Suggested by 2

Suggests, most downloaded first

pathviewr whippr

How these are counted

Code & Tests

Datasets

People & History

People (2)

Matt Dancho

Author, Maintainer since 0.1.0 (2018)

Davis Vaughan

Author

Releases (8)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
0.3.0Latest
record
2023-10-31 · current release · diff ↗
0.2.4
record
2023-09-26 · diff ↗
unarchivedReturned to CRAN
2023-09-25
R
R 4.3.0 released · 2023-04-21
archivedRemoved from CRAN
2023-03-23
requires archived package 'sweep'
0.2.3
record
2023-02-09 · diff ↗
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
0.2.2
record
2020-10-20 · diff ↗
unarchivedReturned to CRAN
2020-06-19
0.2.1
record
2020-06-19 · diff ↗
archivedRemoved from CRAN
2020-06-15
check problems were not corrected in time
R
R 4.0.0 released · 2020-04-24

Show 6 earlier eventsHide 6 earlier events

0.2.0
record
2019-09-21 · diff ↗ ·
added 1 export
clean_anomalies
R
R 3.6.0 released · 2019-04-26
R
R 3.5.0 released · 2018-04-23
0.1.1
record
2018-04-17 · diff ↗
0.1.0
record
2018-04-06
R
R 3.4.0 released · 2017-04-21

Package metadata

First published: 2018-04-06
Total releases: 8 / 8 yrs
License: GPL (>= 3) OSI
Minimum R: ≥ 3.0.0
Bundled data: 40 KB / 1 file
Download size: 2.9 MB

Appears in task views

Anomaly Detection

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("anomalize")

Format

Dancho, M., & Vaughan, D. (2023). anomalize: Tidy Anomaly Detection (Version 0.3.0) [Computer software]. https://doi.org/10.32614/CRAN.package.anomalize

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for anomalize version 0.3.0 [Data set]. HJJB, LLC. Data release v2026-10-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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