{
  "_id": "6a1573bdacfb0bcc41d65804",
  "Package": "brolgar",
  "Title": "Browse Over Longitudinal Data Graphically and Analytically in R",
  "Version": "1.0.2",
  "Authors@R": "c(person(given = \"Nicholas\",\nfamily = \"Tierney\",\nrole = c(\"aut\", \"cre\"),\nemail = \"nicholas.tierney@gmail.com\",\ncomment = c(ORCID = \"https://orcid.org/0000-0003-1460-8722\")),\nperson(given = \"Di\",\nfamily = \"Cook\",\nrole = \"aut\",\nemail = \"dicook@monash.edu\",\ncomment = c(ORCID = \"https://orcid.org/0000-0002-3813-7155\")),\nperson(given = \"Tania\",\nfamily = \"Prvan\",\nrole = \"aut\",\nemail = \"tania.prvan@mq.edu.au\"),\nperson(given = \"Stuart\",\nfamily = \"Lee\",\nrole = \"ctb\"),\nperson(given = \"Earo\",\nfamily = \"Wang\",\nrole = \"ctb\"))",
  "Description": "Provides a framework of tools to summarise, visualise, and\nexplore longitudinal data. It builds upon the tidy time series\ndata frames used in the 'tsibble' package, and is designed to\nintegrate within the 'tidyverse', and 'tidyverts' (for time\nseries) ecosystems. The methods implemented include calculating\nfeatures for understanding longitudinal data, including\ncalculating summary statistics such as quantiles, medians, and\nnumeric ranges, sampling individual series, identifying\nindividual series representative of a group, and extending the\nfacet system in 'ggplot2' to facilitate exploration of samples\nof data. These methods are fully described in the paper\n\"brolgar: An R package to Browse Over Longitudinal Data\nGraphically and Analytically in R\", Nicholas Tierney, Dianne\nCook, Tania Prvan (2020) <doi:10.32614/RJ-2022-023>.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/njtierney/brolgar,\nhttps://brolgar.njtierney.com/, http://brolgar.njtierney.com/",
  "BugReports": "https://github.com/njtierney/brolgar/issues",
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  "Repository": "https://njtierney.r-universe.dev",
  "Date/Publication": "2025-07-29 23:52:08 UTC",
  "RemoteUrl": "https://github.com/njtierney/brolgar",
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  "Packaged": {
    "Date": "2026-05-26 10:15:35 UTC",
    "User": "root"
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  "Author": "Nicholas Tierney [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-1460-8722>),\nDi Cook [aut] (ORCID: <https://orcid.org/0000-0002-3813-7155>),\nTania Prvan [aut],\nStuart Lee [ctb],\nEaro Wang [ctb]",
  "Maintainer": "Nicholas Tierney <nicholas.tierney@gmail.com>",
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  "_created": "2026-05-26T10:15:35.000Z",
  "_published": "2026-05-26T10:19:41.547Z",
  "_distro": "noble",
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  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.cff",
    "extra/citation.html",
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    "extra/citation.txt",
    "extra/contents.json",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
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  "_homeurl": "https://github.com/njtierney/brolgar",
  "_realowner": "njtierney",
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  "_releases": [
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      "date": "2020-12-16"
    },
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      "version": "0.1.1",
      "date": "2021-05-27"
    },
    {
      "version": "0.1.2",
      "date": "2021-08-25"
    },
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      "version": "1.0.0",
      "date": "2023-02-07"
    },
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      "date": "2024-05-10"
    },
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      "version": "1.0.2",
      "date": "2025-09-03"
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  ],
  "_exports": [
    "%>%",
    "add_key_slope",
    "add_key_slope.default",
    "add_n_obs",
    "as_tsibble",
    "b_diff_iqr",
    "b_diff_max",
    "b_diff_mean",
    "b_diff_median",
    "b_diff_min",
    "b_diff_q25",
    "b_diff_q75",
    "b_diff_sd",
    "b_diff_var",
    "b_iqr",
    "b_mad",
    "b_max",
    "b_mean",
    "b_median",
    "b_min",
    "b_q25",
    "b_q75",
    "b_range",
    "b_range_diff",
    "b_sd",
    "b_var",
    "decreasing",
    "facet_sample",
    "facet_strata",
    "feat_brolgar",
    "feat_diff_summary",
    "feat_five_num",
    "feat_monotonic",
    "feat_ranges",
    "feat_spread",
    "feat_three_num",
    "features",
    "features_all",
    "features_at",
    "features_if",
    "increasing",
    "index_regular",
    "index_summary",
    "key_slope",
    "keys_near",
    "l_five_num",
    "l_three_num",
    "monotonic",
    "n_keys",
    "n_obs",
    "near_between",
    "near_middle",
    "near_quantile",
    "nearest_lgl",
    "nearest_qt_lgl",
    "sample_frac_keys",
    "sample_n_keys",
    "stratify_keys",
    "unvarying"
  ],
  "_datasets": [
    {
      "name": "heights",
      "title": "World Height Data",
      "object": "heights",
      "class": [
        "tbl_ts",
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "country",
        "continent",
        "year",
        "height_cm"
      ],
      "rows": 1490,
      "table": true,
      "tojson": true
    },
    {
      "name": "pisa",
      "title": "Student data from 2000-2018 PISA OECD data",
      "object": "pisa",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "country",
        "year",
        "math_mean",
        "math_min",
        "math_max",
        "read_mean",
        "read_min",
        "read_max",
        "science_mean",
        "science_min",
        "science_max"
      ],
      "rows": 433,
      "table": true,
      "tojson": true
    },
    {
      "name": "wages",
      "title": "Wages data from National Longitudinal Survey of Youth (NLSY)",
      "object": "wages",
      "class": [
        "tbl_ts",
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "id",
        "ln_wages",
        "xp",
        "ged",
        "xp_since_ged",
        "black",
        "hispanic",
        "high_grade",
        "unemploy_rate"
      ],
      "rows": 6402,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "add_n_obs",
      "title": "Add the number of observations for each key in a 'tsibble'",
      "topics": [
        "add_n_obs"
      ]
    },
    {
      "page": "b_summaries",
      "title": "Brolgar summaries (b_summaries)",
      "topics": [
        "b_diff_iqr",
        "b_diff_max",
        "b_diff_mean",
        "b_diff_median",
        "b_diff_min",
        "b_diff_q25",
        "b_diff_q75",
        "b_diff_sd",
        "b_diff_var",
        "b_iqr",
        "b_mad",
        "b_max",
        "b_mean",
        "b_median",
        "b_min",
        "b_q25",
        "b_q75",
        "b_range",
        "b_range_diff",
        "b_sd",
        "b_summaries",
        "b_var"
      ]
    },
    {
      "page": "brolgar-features",
      "title": "Calculate features of a 'tsibble' object in conjunction with 'features()'",
      "topics": [
        "brolgar-features",
        "feat_brolgar",
        "feat_diff_summary",
        "feat_five_num",
        "feat_monotonic",
        "feat_ranges",
        "feat_spread",
        "feat_three_num"
      ]
    },
    {
      "page": "facet_sample",
      "title": "Facet data into groups to facilitate exploration",
      "topics": [
        "facet_sample"
      ]
    },
    {
      "page": "facet_strata",
      "title": "Facet data into groups to facilitate exploration",
      "topics": [
        "facet_strata"
      ]
    },
    {
      "page": "heights",
      "title": "World Height Data",
      "topics": [
        "heights"
      ]
    },
    {
      "page": "index_summary",
      "title": "Index summaries",
      "topics": [
        "index_regular",
        "index_regular.data.frame",
        "index_regular.tbl_ts",
        "index_summary",
        "index_summary.data.frame",
        "index_summary.tbl_ts"
      ]
    },
    {
      "page": "key_slope",
      "title": "Fit linear model for each key",
      "topics": [
        "add_key_slope",
        "add_key_slope.default",
        "key_slope"
      ]
    },
    {
      "page": "keys_near",
      "title": "Return keys nearest to a given statistics or summary.",
      "topics": [
        "keys_near",
        "keys_near.default"
      ]
    },
    {
      "page": "keys_near.data.frame",
      "title": "Return keys nearest to a given statistics or summary.",
      "topics": [
        "keys_near.data.frame"
      ]
    },
    {
      "page": "keys_near.tbl_ts",
      "title": "Return keys nearest to a given statistics or summary.",
      "topics": [
        "keys_near.tbl_ts"
      ]
    },
    {
      "page": "l_funs",
      "title": "A named list of the five number summary",
      "topics": [
        "l_five_num",
        "l_funs",
        "l_three_num"
      ]
    },
    {
      "page": "monotonic",
      "title": "Are values monotonic? Always increasing, decreasing, or unvarying?",
      "topics": [
        "decreasing",
        "increasing",
        "monotonic",
        "unvarying"
      ]
    },
    {
      "page": "n_obs",
      "title": "Return the number of observations",
      "topics": [
        "n_obs"
      ]
    },
    {
      "page": "near_between",
      "title": "Return x percent to y percent of values",
      "topics": [
        "near_between"
      ]
    },
    {
      "page": "near_middle",
      "title": "Return the middle x percent of values",
      "topics": [
        "near_middle"
      ]
    },
    {
      "page": "near_quantile",
      "title": "Which values are nearest to any given quantiles",
      "topics": [
        "near_quantile"
      ]
    },
    {
      "page": "nearests",
      "title": "Is x nearest to y?",
      "topics": [
        "nearests",
        "nearest_lgl",
        "nearest_qt_lgl"
      ]
    },
    {
      "page": "pisa",
      "title": "Student data from 2000-2018 PISA OECD data",
      "topics": [
        "pisa"
      ]
    },
    {
      "page": "sample-n-frac-keys",
      "title": "Sample a number or fraction of keys to explore",
      "topics": [
        "sample-n-frac-keys",
        "sample_frac_keys",
        "sample_n_keys"
      ]
    },
    {
      "page": "stratify_keys",
      "title": "Stratify the keys into groups to facilitate exploration",
      "topics": [
        "stratify_keys"
      ]
    },
    {
      "page": "wages",
      "title": "Wages data from National Longitudinal Survey of Youth (NLSY)",
      "topics": [
        "wages"
      ]
    }
  ],
  "_readme": "https://github.com/njtierney/brolgar/raw/HEAD/README.md",
  "_rundeps": [
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    "cli",
    "cpp11",
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    "distributional",
    "dplyr",
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    "magrittr",
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    "pillar",
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    "R6",
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    "stringi",
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    "tidyselect",
    "timechange",
    "tsibble",
    "utf8",
    "vctrs",
    "viridisLite",
    "withr"
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  "_vignettes": [
    {
      "source": "exploratory-modelling.Rmd",
      "filename": "exploratory-modelling.html",
      "title": "Exploratory Modelling",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Find keys near other summaries with keys_near()"
      ],
      "created": "2019-08-13 08:38:10",
      "modified": "2023-02-06 00:08:30",
      "commits": 6
    },
    {
      "source": "finding-features.Rmd",
      "filename": "finding-features.html",
      "title": "Finding Features in Data",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Calculating features",
        "Creating your own Features",
        "Accessing sets of features",
        "Registering a feature in a package"
      ],
      "created": "2019-08-13 08:38:10",
      "modified": "2023-02-06 00:24:49",
      "commits": 8
    },
    {
      "source": "getting-started.Rmd",
      "filename": "getting-started.html",
      "title": "Getting Started",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Setting up your data",
        "Basic summaries of the data",
        "How many observations are there?",
        "add_n_obs()",
        "Efficiently exploring longitudinal data",
        "sample_n_keys()",
        "Filtering observations",
        "Clever facets: facet_strata",
        "Clever facets: facet_sample",
        "Exploratory modelling",
        "Find keys near other summaries with keys_near",
        "Finding features in longitudinal data",
        "Linking individuals back to the data"
      ],
      "created": "2019-07-19 06:26:40",
      "modified": "2020-12-15 03:42:50",
      "commits": 15
    },
    {
      "source": "id-interesting-obs.Rmd",
      "filename": "id-interesting-obs.html",
      "title": "Identify Interesting Observations",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Specify your own summaries for keys_near",
        "Implementation of keys_near"
      ],
      "created": "2019-08-13 08:38:10",
      "modified": "2023-02-06 00:24:49",
      "commits": 7
    },
    {
      "source": "longitudinal-data-structures.Rmd",
      "filename": "longitudinal-data-structures.html",
      "title": "Longitudinal Data Structures",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Defining longitudinal data as a tsibble",
        "Converting your longitudinal data to a time series",
        "example data: wages",
        "example: heights data",
        "example: gapminder",
        "example: PISA data",
        "Conclusion"
      ],
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      "title": "Visualisation Gallery",
      "engine": "knitr::rmarkdown",
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        "Exploring raw data",
        "Select a sample of individuals",
        "Filter only those with certain number of observations",
        "Clever facets: facet_strata",
        "Clever facets: facet_sample",
        "Clever facets with number of observations",
        "Exploring data using features",
        "Plot monotonic individual series",
        "Plot individuals with negative slope",
        "Move along features with facet_strata",
        "Visualise along slope"
      ],
      "created": "2019-04-29 03:25:53",
      "modified": "2023-02-06 00:24:49",
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