{ "_id": "6a1ef452b401979e73415e41", "Package": "dataprep", "Type": "Package", "Title": "Efficient and Flexible Data Preprocessing Tools", "Version": "0.1.5", "Author": "Chun-Sheng Liang , Hao Wu, Hai-Yan\nLi, Qiang Zhang, Zhanqing Li, Ke-Bin He, Lanzhou University,\nTsinghua University", "Maintainer": "Chun-Sheng Liang ", "Description": "Efficiently and flexibly preprocess data using a set of\ndata filtering, deletion, and interpolation tools. These data\npreprocessing methods are developed based on the principles of\ncompleteness, accuracy, threshold method, and linear\ninterpolation and through the setting of constraint conditions,\ntime completion & recovery, and fast & efficient calculation\nand grouping. Key preprocessing steps include deletions of\nvariables and observations, outlier removal, and missing values\n(NA) interpolation, which are dependent on the incomplete and\ndispersed degrees of raw data. They clean data more accurately,\nkeep more samples, and add no outliers after interpolation,\ncompared with ordinary methods. Auto-identification of\nconsecutive NA via run-length based grouping is used in\nobservation deletion, outlier removal, and NA interpolation;\nthus, new outliers are not generated in interpolation.\nConditional extremum is proposed to realize point-by-point\nweighed outlier removal that saves non-outliers from being\nremoved. Plus, time series interpolation with values to refer\nto within short periods further ensures reliable interpolation.\nThese methods are based on and improved from the reference:\nLiang, C.-S., Wu, H., Li, H.-Y., Zhang, Q., Li, Z. & He, K.-B.\n(2020) .", "License": "GPL (>= 2)", "VignetteBuilder": "knitr, rmarkdown", "Encoding": "UTF-8", "RoxygenNote": "7.1.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-19 07:07:43 UTC", "User": "root" }, "Repository": "https://cran.r-universe.dev", "Date/Publication": "2022-01-15 12:32:42 UTC", "RemoteUrl": "https://github.com/cran/dataprep", "RemoteRef": "HEAD", "RemoteSha": "0ac37849478f43812beb06630d9e9ea4738c7ac5", "MD5sum": "2148aecfa4fca0e853df028b9e08df14", "_user": "cran", "_type": "src", "_file": "dataprep_0.1.5.tar.gz", "_fileid": "3cd78a47f00442adcadb6d09ea9655d5c411b87e1436570c02ccdd692deea458", "_filesize": 2485950, "_sha256": "3cd78a47f00442adcadb6d09ea9655d5c411b87e1436570c02ccdd692deea458", "_created": "2026-05-19T07:07:43.000Z", "_published": "2026-06-02T15:18:42.219Z", "_distro": "noble", "_jobs": [ { "job": 79105981361, "time": 121, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7077015439" }, { "job": 79105981285, "time": 139, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7077021150" }, { "job": 79105980035, "time": 173, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7076979092" }, { "job": 79105979886, "time": 107, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7361986897" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/26081813933", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/dataprep", "_commit": { "id": "0ac37849478f43812beb06630d9e9ea4738c7ac5", "author": "Chun-Sheng Liang ", "committer": "cran-robot ", "message": "version 0.1.5\n", "time": 1642249962 }, "_maintainer": { "name": "Chun-Sheng Liang", "email": "liangchunsheng@lzu.edu.cn" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "ggplot2", "role": "Imports" }, { "package": "scales", "role": "Imports" }, { "package": "foreach", "role": "Imports" }, { "package": "doParallel", "role": "Imports" }, { "package": "dplyr", "role": "Imports" }, { "package": "reshape2", "role": "Imports" }, { "package": "data.table", "role": "Imports" }, { "package": "zoo", "role": "Imports" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 0, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 269, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/dataprep" }, "_searchresults": 7, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/dataprep.html", "manual.pdf" ], "_realowner": "cran", "_cranurl": false, "_releases": [ { "version": "0.1.0", "date": "2021-01-11" }, { "version": "0.1.1", "date": "2021-04-04" }, { "version": "0.1.2", "date": "2021-05-25" }, { "version": "0.1.3", "date": "2021-05-28" }, { "version": "0.1.4", "date": "2021-07-04" }, { "version": "0.1.5", "date": "2022-01-15" } ], "_exports": [ "condextr", "data", "data1", "dataprep", "descdata", "descplot", "melt", "obsedele", "optisolu", "percdata", "percoutl", "percplot", "shorvalu", "varidele", "zerona" ], "_help": [ { "page": "condextr", "title": "Remove outliers using point-by-point weighed outlier removal by conditional extremum", "topics": [ "condextr" ] }, { "page": "data", "title": "Example data (particle number concentrations in SMEAR I Varrio forest)", "topics": [ "data" ] }, { "page": "data1", "title": "Example data (data1, particle number concentrations in SMEAR I Varrio forest)", "topics": [ "data1" ] }, { "page": "dataprep", "title": "Data preprocessing with multiple steps in one function", "topics": [ "dataprep" ] }, { "page": "descdata", "title": "Fast descriptive statistics", "topics": [ "descdata" ] }, { "page": "descplot", "title": "View the descriptive statistics via plot", "topics": [ "descplot" ] }, { "page": "melt", "title": "Turn variable names and values into two columns", "topics": [ "melt" ] }, { "page": "obsedele", "title": "Delete observations with variable(s) containing too many consecutive missing values (NA) in time series", "topics": [ "obsedele" ] }, { "page": "optisolu", "title": "Find an optimal combination of 'interval' and 'times' for 'condextr'", "topics": [ "optisolu" ] }, { "page": "percdata", "title": "Calculate the top and bottom percentiles of each selected variable", "topics": [ "percdata" ] }, { "page": "percoutl", "title": "Traditional percentile-based outlier removal", "topics": [ "percoutl" ] }, { "page": "percplot", "title": "Plot the top and bottom percentiles of each selected variable", "topics": [ "percplot" ] }, { "page": "shorvalu", "title": "Interpolation with values to refer to within short periods", "topics": [ "shorvalu" ] }, { "page": "varidele", "title": "Delete variables containing too many missing values (NA)", "topics": [ "varidele" ] }, { "page": "zerona", "title": "Turn zeros to missing values", "topics": [ "zerona" ] } ], "_rundeps": [ "cli", "codetools", "cpp11", "data.table", "doParallel", "dplyr", "farver", "foreach", "generics", "ggplot2", "glue", "gtable", "isoband", "iterators", "labeling", "lattice", "lifecycle", "magrittr", "pillar", "pkgconfig", "plyr", "R6", "RColorBrewer", "Rcpp", "reshape2", "rlang", "S7", "scales", "stringi", "stringr", "tibble", "tidyselect", "utf8", "vctrs", "viridisLite", "withr", "zoo" ], "_vignettes": [ { "source": "vignettes.Rmd", "filename": "vignettes.html", "title": "dataprep: data preprocessing and plots", "engine": "knitr::rmarkdown", "headings": [ "Figure 1. Line plots for variables with names that are essentially numeric and logarithmic", "Figure 2. Line plots for variables whose names are essentially numeric and logarithmic", "Figure 3. Bar charts for the type of variable names that is character", "Figure 4. Bar charts for the type of variable names that is character", "Figure 5. Particle number size distributions in logarithmic scales", "Figure 6. Particle number size distributions in logarithmic scales with only one part", "Figure 7. Particle number size distributions in logarithmic scales with only one part", "Figure 8. Percentiles of modes in linear scales", "Figure 9. Percentiles of modes in linear scales with only one part", "Figure 10. Percentiles of modes in linear scales with only one part" ], "created": "2021-01-11 09:00:02", "modified": "2021-01-11 09:00:02", "commits": 1 } ], "_score": 2, "_indexed": true, "_nocasepkg": "dataprep", "_universes": [ "cran" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.1.5", "date": "2026-05-19T07:09:38.000Z", "distro": "noble", "commit": "0ac37849478f43812beb06630d9e9ea4738c7ac5", "fileid": "426941ab7f66dad88c301bc8e3c2f94b14d834811925eba7ceee2dec020c928d", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26081813933" }, { "r": "4.6.0", "os": "linux", "version": "0.1.5", "date": "2026-05-19T07:09:55.000Z", "distro": "noble", "commit": "0ac37849478f43812beb06630d9e9ea4738c7ac5", "fileid": "234116df2dc21c37ecd9e5e3faf169d93b7033c72379a67c69596b72b57f933e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26081813933" }, { "r": "4.6.0", "os": "wasm", "version": "0.1.5", "date": "2026-06-02T15:18:23.000Z", "commit": "0ac37849478f43812beb06630d9e9ea4738c7ac5", "fileid": "8a6255d0f6c71e7d96544b2c25283bc7ccfcaafb0c4c00918ceb8b1b981314d7", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/26081813933" } ] }