{
  "_id": "6a37ae623efcd9bda44255c8",
  "Package": "correlationfunnel",
  "Type": "Package",
  "Title": "Speed Up Exploratory Data Analysis (EDA) with the Correlation\nFunnel",
  "Version": "0.2.0",
  "Authors@R": "person(\"Matt\", \"Dancho\", email = \"mdancho@business-science.io\", role = c(\"aut\", \"cre\"))",
  "Description": "Speeds up exploratory data analysis (EDA) by providing a\nsuccinct workflow and interactive visualization tools for\nunderstanding which features have relationships to target\n(response). Uses binary correlation analysis to determine\nrelationship. Default correlation method is the Pearson method.\nLian Duan, W Nick Street, Yanchi Liu, Songhua Xu, and Brook Wu\n(2014) <doi:10.1145/2637484>.",
  "URL": "https://github.com/business-science/correlationfunnel,\nhttps://business-science.github.io/correlationfunnel/",
  "BugReports": "https://github.com/business-science/correlationfunnel/issues",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.1.0",
  "Roxygen": "list(markdown = TRUE)",
  "VignetteBuilder": "knitr",
  "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev libssl-dev",
  "Repository": "https://business-science.r-universe.dev",
  "Date/Publication": "2024-01-16 18:07:26 UTC",
  "RemoteUrl": "https://github.com/business-science/correlationfunnel",
  "RemoteRef": "HEAD",
  "RemoteSha": "e592ef37ff50f8cbdb2763681f6a0a03aad72611",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-21 09:22:51 UTC",
    "User": "root"
  },
  "Author": "Matt Dancho [aut, cre]",
  "Maintainer": "Matt Dancho <mdancho@business-science.io>",
  "MD5sum": "38b9df9316a63cf2c3d780603c4b15f3",
  "_user": "business-science",
  "_type": "src",
  "_file": "correlationfunnel_0.2.0.tar.gz",
  "_fileid": "bf1e020207a0f4c6fe4c70a82d6d8fe1a06799e065c4616de435b230c6d18e8c",
  "_filesize": 3216158,
  "_sha256": "bf1e020207a0f4c6fe4c70a82d6d8fe1a06799e065c4616de435b230c6d18e8c",
  "_created": "2026-06-21T09:22:51.000Z",
  "_published": "2026-06-21T09:26:58.956Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 82558373914,
      "time": 203,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "NOTE",
      "artifact": "7773925086"
    },
    {
      "job": 82558373917,
      "time": 175,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "NOTE",
      "artifact": "7773920960"
    },
    {
      "job": 82558373915,
      "time": 132,
      "config": "macos-oldrel-arm64",
      "r": "4.5.3",
      "check": "NOTE",
      "artifact": "7773915112"
    },
    {
      "job": 82558373923,
      "time": 105,
      "config": "macos-release-arm64",
      "r": "4.6.0",
      "check": "NOTE",
      "artifact": "7773911475"
    },
    {
      "job": 82558061408,
      "time": 288,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7773897370"
    },
    {
      "job": 82558373913,
      "time": 129,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7773914723"
    },
    {
      "job": 82558373903,
      "time": 151,
      "config": "windows-devel",
      "r": "4.7.0",
      "check": "NOTE",
      "artifact": "7773918101"
    },
    {
      "job": 82558373908,
      "time": 165,
      "config": "windows-oldrel",
      "r": "4.5.3",
      "check": "NOTE",
      "artifact": "7773919482"
    },
    {
      "job": 82558373922,
      "time": 138,
      "config": "windows-release",
      "r": "4.6.0",
      "check": "NOTE",
      "artifact": "7773915934"
    }
  ],
  "_buildurl": "https://github.com/r-universe/business-science/actions/runs/27899837014",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/business-science/correlationfunnel",
  "_commit": {
    "id": "e592ef37ff50f8cbdb2763681f6a0a03aad72611",
    "author": "Matt Dancho <mdancho84@users.noreply.github.com>",
    "committer": "GitHub <noreply@github.com>",
    "message": "Merge pull request #9 from olivroy/patch-1\n\n",
    "time": 1705428446
  },
  "_maintainer": {
    "name": "Matt Dancho",
    "email": "mdancho@business-science.io",
    "login": "mdancho84",
    "twitter": "@mdancho84",
    "description": "Hello. I'm Matt. I'm the founder of @business-science where we train business professionals how to become 6-figure data scientists and grow their careers. ",
    "uuid": 13734662
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.1",
      "role": "Depends"
    },
    {
      "package": "ggplot2",
      "role": "Imports"
    },
    {
      "package": "rlang",
      "role": "Imports"
    },
    {
      "package": "recipes",
      "role": "Imports"
    },
    {
      "package": "magrittr",
      "role": "Imports"
    },
    {
      "package": "plotly",
      "role": "Imports"
    },
    {
      "package": "tibble",
      "role": "Imports"
    },
    {
      "package": "dplyr",
      "version": ">= 1.0.0",
      "role": "Imports"
    },
    {
      "package": "tidyr",
      "version": ">= 1.0.0",
      "role": "Imports"
    },
    {
      "package": "stats",
      "role": "Imports"
    },
    {
      "package": "utils",
      "role": "Imports"
    },
    {
      "package": "ggrepel",
      "role": "Imports"
    },
    {
      "package": "stringr",
      "role": "Imports"
    },
    {
      "package": "forcats",
      "role": "Imports"
    },
    {
      "package": "purrr",
      "role": "Imports"
    },
    {
      "package": "cli",
      "role": "Imports"
    },
    {
      "package": "crayon",
      "role": "Imports"
    },
    {
      "package": "rstudioapi",
      "role": "Imports"
    },
    {
      "package": "scales",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "covr",
      "role": "Suggests"
    },
    {
      "package": "lubridate",
      "role": "Suggests"
    },
    {
      "package": "testthat",
      "version": ">= 2.1.0",
      "role": "Suggests"
    }
  ],
  "_owner": "business-science",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_topics": [
    "correlation",
    "exploratory-analysis",
    "exploratory-data-analysis",
    "exploratory-data-visualizations",
    "tidyverse"
  ],
  "_stars": 140,
  "_contributors": [
    {
      "user": "mdancho84",
      "count": 53,
      "uuid": 13734662
    },
    {
      "user": "olivroy",
      "count": 1,
      "uuid": 52606734
    }
  ],
  "_userbio": {
    "uuid": 26503379,
    "type": "organization",
    "name": "Business Science",
    "followers": 1260,
    "description": "Applying data science to business & financial analysis, tw: @bizScienc"
  },
  "_downloads": {
    "count": 516,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/correlationfunnel"
  },
  "_devurl": "https://github.com/business-science/correlationfunnel",
  "_pkgdown": "https://business-science.github.io/correlationfunnel/",
  "_searchresults": 148,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/correlationfunnel.html",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "LICENSE",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/business-science/correlationfunnel",
  "_realowner": "business-science",
  "_cranurl": true,
  "_releases": [
    {
      "version": "0.1.0",
      "date": "2019-08-06"
    },
    {
      "version": "0.2.0",
      "date": "2020-06-09"
    }
  ],
  "_exports": [
    "%>%",
    "binarize",
    "correlate",
    "plot_correlation_funnel"
  ],
  "_datasets": [
    {
      "name": "customer_churn_tbl",
      "title": "Customer Churn Data Set for a Telecommunications Company",
      "object": "customer_churn_tbl",
      "class": [
        "spec_tbl_df",
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "customerID",
        "gender",
        "SeniorCitizen",
        "Partner",
        "Dependents",
        "tenure",
        "PhoneService",
        "MultipleLines",
        "InternetService",
        "OnlineSecurity",
        "OnlineBackup",
        "DeviceProtection",
        "TechSupport",
        "StreamingTV",
        "StreamingMovies",
        "Contract",
        "PaperlessBilling",
        "PaymentMethod",
        "MonthlyCharges",
        "TotalCharges",
        "Churn"
      ],
      "rows": 7043,
      "table": true,
      "tojson": true
    },
    {
      "name": "marketing_campaign_tbl",
      "title": "Marketing Data for a Bank",
      "object": "marketing_campaign_tbl",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "ID",
        "AGE",
        "JOB",
        "MARITAL",
        "EDUCATION",
        "DEFAULT",
        "BALANCE",
        "HOUSING",
        "LOAN",
        "CONTACT",
        "DAY",
        "MONTH",
        "DURATION",
        "CAMPAIGN",
        "PDAYS",
        "PREVIOUS",
        "POUTCOME",
        "TERM_DEPOSIT"
      ],
      "rows": 45211,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "binarize",
      "title": "Turn data with numeric, categorical features into binary data.",
      "topics": [
        "binarize"
      ]
    },
    {
      "page": "correlate",
      "title": "Correlate a response (target) to features in a data set.",
      "topics": [
        "correlate"
      ]
    },
    {
      "page": "customer_churn_tbl",
      "title": "Customer Churn Data Set for a Telecommunications Company",
      "topics": [
        "customer_churn_tbl"
      ]
    },
    {
      "page": "marketing_campaign_tbl",
      "title": "Marketing Data for a Bank",
      "topics": [
        "marketing_campaign_tbl"
      ]
    },
    {
      "page": "plot_correlation_funnel",
      "title": "Plot a Correlation Funnel",
      "topics": [
        "plot_correlation_funnel"
      ]
    }
  ],
  "_readme": "https://github.com/business-science/correlationfunnel/raw/HEAD/README.md",
  "_rundeps": [
    "askpass",
    "base64enc",
    "bslib",
    "cachem",
    "class",
    "cli",
    "clock",
    "codetools",
    "cpp11",
    "crayon",
    "crosstalk",
    "curl",
    "data.table",
    "diagram",
    "digest",
    "dplyr",
    "evaluate",
    "farver",
    "fastmap",
    "fontawesome",
    "forcats",
    "fs",
    "future",
    "future.apply",
    "generics",
    "ggplot2",
    "ggrepel",
    "globals",
    "glue",
    "gower",
    "gtable",
    "hardhat",
    "highr",
    "htmltools",
    "htmlwidgets",
    "httr",
    "ipred",
    "isoband",
    "jquerylib",
    "jsonlite",
    "KernSmooth",
    "knitr",
    "labeling",
    "later",
    "lattice",
    "lava",
    "lazyeval",
    "lifecycle",
    "listenv",
    "lubridate",
    "magrittr",
    "MASS",
    "Matrix",
    "memoise",
    "mime",
    "nnet",
    "numDeriv",
    "openssl",
    "otel",
    "parallelly",
    "pillar",
    "pkgconfig",
    "plotly",
    "prodlim",
    "progressr",
    "promises",
    "purrr",
    "R6",
    "rappdirs",
    "RColorBrewer",
    "Rcpp",
    "recipes",
    "rlang",
    "rmarkdown",
    "rpart",
    "rstudioapi",
    "S7",
    "sass",
    "scales",
    "shape",
    "sparsevctrs",
    "SQUAREM",
    "stringi",
    "stringr",
    "survival",
    "sys",
    "tibble",
    "tidyr",
    "tidyselect",
    "timechange",
    "timeDate",
    "tinytex",
    "tzdb",
    "utf8",
    "vctrs",
    "viridisLite",
    "withr",
    "xfun",
    "yaml"
  ],
  "_vignettes": [
    {
      "source": "introducing_correlation_funnel.Rmd",
      "filename": "introducing_correlation_funnel.html",
      "title": "Introducing Correlation Funnel - Customer Churn Example",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Problem",
        "Solution",
        "Main Benefits",
        "Correlation Funnel Process",
        "Example - Customer Churn",
        "Step 1 - Prepare Data as Binary Features",
        "Step 2 - Correlate to the Target",
        "Step 3 - Plot the Correlation Funnel",
        "Business Insights",
        "Conclusion",
        "More Information"
      ],
      "created": "2019-07-16 00:03:09",
      "modified": "2020-06-09 00:32:54",
      "commits": 3
    },
    {
      "source": "key_considerations.Rmd",
      "filename": "key_considerations.html",
      "title": "Methodology, Key Considerations, and FAQs",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Methodology",
        "Key Considerations",
        "Prior to Binarization Step",
        "During Binarization",
        "Prior to Correlation Step",
        "After Plotting the Correlation Funnel",
        "FAQs",
        "1. How does the Correlation Funnel Find Relationships in Numeric Data?",
        "1.1 Linear Relationships",
        "1.2 Non-Linear Relationships",
        "2. What About Skewed Numeric Data?",
        "2.1 Skewed Data",
        "2.2. Highly Skewed Data",
        "3. How does the Correlation Funnel Work With Categorical Data?",
        "3.1 One-Hot Encoding vs Dummy Encoding",
        "3.2 Reducing Dimensionality (Preventing Irrelevant Factor Levels)",
        "3.3 Assessing Correlations With Categorical Data",
        "References"
      ],
      "created": "2019-07-16 14:17:35",
      "modified": "2020-06-09 00:32:54",
      "commits": 3
    }
  ],
  "_score": 7.316389751073196,
  "_indexed": true,
  "_nocasepkg": "correlationfunnel",
  "_universes": [
    "business-science",
    "mdancho84"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "0.2.0",
      "date": "2026-06-21T09:25:29.000Z",
      "distro": "noble",
      "commit": "e592ef37ff50f8cbdb2763681f6a0a03aad72611",
      "fileid": "344d5dfc46505dbd85bf83bfc79b3fd01b8ab620436f4dd947179da2bb1ce283",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/business-science/actions/runs/27899837014"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "0.2.0",
      "date": "2026-06-21T09:25:14.000Z",
      "distro": "noble",
      "commit": "e592ef37ff50f8cbdb2763681f6a0a03aad72611",
      "fileid": "ca87a7dc582a13f3e5601c274cf9eb27d416403261b5b1c2eb4ea367f5a6cc19",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/business-science/actions/runs/27899837014"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "0.2.0",
      "date": "2026-06-21T09:24:41.000Z",
      "commit": "e592ef37ff50f8cbdb2763681f6a0a03aad72611",
      "fileid": "97f0e898ab3fa31ab191d1e3a565896710389fe54a4be9cabccb984493aa24a2",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/business-science/actions/runs/27899837014"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "0.2.0",
      "date": "2026-06-21T09:24:23.000Z",
      "commit": "e592ef37ff50f8cbdb2763681f6a0a03aad72611",
      "fileid": "b1550665578bf8e1871095a0e2f2e126583f3f38d59597b7e3087a2915e760fb",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/business-science/actions/runs/27899837014"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "0.2.0",
      "date": "2026-06-21T09:25:24.000Z",
      "commit": "e592ef37ff50f8cbdb2763681f6a0a03aad72611",
      "fileid": "651218bb86c83c95ce9f4fd6d944517609598c122d4100fdf92cc8caaa8324e8",
      "status": "success",
      "buildurl": "https://github.com/r-universe/business-science/actions/runs/27899837014"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "0.2.0",
      "date": "2026-06-21T09:24:54.000Z",
      "commit": "e592ef37ff50f8cbdb2763681f6a0a03aad72611",
      "fileid": "ea78bcaac309a37e891b834582a7f1e01045d378a89aad402e94db46e2d17b6f",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/business-science/actions/runs/27899837014"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "0.2.0",
      "date": "2026-06-21T09:24:41.000Z",
      "commit": "e592ef37ff50f8cbdb2763681f6a0a03aad72611",
      "fileid": "dc9672997c36c960c8d24bfa0bdd9f5c69d5f75a33c3b784e3050febf3b0aa54",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/business-science/actions/runs/27899837014"
    },
    {
      "r": "4.6.0",
      "os": "win",
      "version": "0.2.0",
      "date": "2026-06-21T09:24:16.000Z",
      "commit": "e592ef37ff50f8cbdb2763681f6a0a03aad72611",
      "fileid": "a451969da6a517884c6b06983d261989e33834ef386c45dc7221b336d336d16b",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/business-science/actions/runs/27899837014"
    }
  ]
}