{
  "_id": "6a23e470530b9bc726be8679",
  "Package": "baizer",
  "Title": "Useful Functions for Data Processing",
  "Version": "0.8.1",
  "Authors@R": "person(\"William\", \"Song\", , \"william_swl@163.com\", role = c(\"aut\", \"cre\"))",
  "Description": "In ancient Chinese mythology, Bai Ze is a divine creature\nthat knows the needs of everything. 'baizer' provides data\nprocessing functions frequently used by the author. Hope this\npackage also knows what you want!",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.2.3",
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  "URL": "https://william-swl.github.io/baizer/,\nhttps://github.com/william-swl/baizer",
  "BugReports": "https://github.com/william-swl/baizer/issues",
  "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev libssl-dev\nlibx11-dev",
  "Repository": "https://william-swl.r-universe.dev",
  "Date/Publication": "2023-10-25 03:39:09 UTC",
  "RemoteUrl": "https://github.com/william-swl/baizer",
  "RemoteRef": "HEAD",
  "RemoteSha": "6a20b06b093659bf24dd8ec9cd07a8e65ade2cf0",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-06 09:08:57 UTC",
    "User": "root"
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  "Author": "William Song [aut, cre]",
  "Maintainer": "William Song <william_swl@163.com>",
  "MD5sum": "ba4c0c8616ea9d7e1161c726849c052c",
  "_user": "william-swl",
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  "_created": "2026-06-06T09:08:57.000Z",
  "_published": "2026-06-06T09:12:16.277Z",
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    "nearest_tick",
    "not.na",
    "not.null",
    "number_fun_wrapper",
    "ordered_slice",
    "percent_to_float",
    "pileup_logical",
    "pkginfo",
    "pkglib",
    "pkgver",
    "pos_int_split",
    "r2c",
    "read_excel",
    "read_excel_list",
    "read_fmmd",
    "ref_level",
    "reg_join",
    "reg_match",
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    "remove_nacol",
    "remove_narow",
    "remove_outliers",
    "replace_item",
    "rewrite_na",
    "rng2seq",
    "round_string",
    "roxygen_fmt",
    "same_index",
    "seriate_df",
    "sftp_connect",
    "sftp_download",
    "sftp_ls",
    "signif_ceiling",
    "signif_floor",
    "signif_round_string",
    "signif_string",
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    "sortf",
    "split_column",
    "split_path",
    "split_vector",
    "stat_fc",
    "stat_phi",
    "stat_test",
    "str_replace_loc",
    "swap_vecname",
    "tbflt",
    "tdf",
    "top_item",
    "uniq",
    "uniq_in_cols",
    "write_excel"
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  "_datasets": [
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      "name": "mini_diamond",
      "title": "Minimal tibble dataset adjusted from diamond",
      "object": "mini_diamond",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "id",
        "carat",
        "cut",
        "clarity",
        "price",
        "x",
        "y"
      ],
      "rows": 100,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
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      "page": "grapes-eq-grapes",
      "title": "equal calculation operator, support NA",
      "topics": [
        "%eq%"
      ]
    },
    {
      "page": "grapes-neq-grapes",
      "title": "not equal calculation operator, support NA",
      "topics": [
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      ]
    },
    {
      "page": "grapes-nin-grapes",
      "title": "not in calculation operator",
      "topics": [
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      ]
    },
    {
      "page": "adjacent_div",
      "title": "expand a number vector according to the adjacent two numbers",
      "topics": [
        "adjacent_div"
      ]
    },
    {
      "page": "alias_arg",
      "title": "use aliases for function arguments",
      "topics": [
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      ]
    },
    {
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      "title": "trans a tibble into markdown format table",
      "topics": [
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    },
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      "topics": [
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    {
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      "topics": [
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      ]
    },
    {
      "page": "broadcast_vector",
      "title": "broadcast the vector into length n",
      "topics": [
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      "topics": [
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      "page": "check_arg",
      "title": "check arguments by custom function",
      "topics": [
        "check_arg"
      ]
    },
    {
      "page": "cmdargs",
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      "topics": [
        "cmdargs"
      ]
    },
    {
      "page": "collapse_vector",
      "title": "dump a named vector into character",
      "topics": [
        "collapse_vector"
      ]
    },
    {
      "page": "combn_vector",
      "title": "combine multiple vectors into one",
      "topics": [
        "combn_vector"
      ]
    },
    {
      "page": "correct_ratio",
      "title": "correct the numbers to a target ratio",
      "topics": [
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      ]
    },
    {
      "page": "cross_count",
      "title": "count two columns as a cross-tabulation table",
      "topics": [
        "cross_count"
      ]
    },
    {
      "page": "detect_dup",
      "title": "detect possible duplication in a vector, ignore case, blank and special character",
      "topics": [
        "detect_dup"
      ]
    },
    {
      "page": "diff_index",
      "title": "the index of different character",
      "topics": [
        "diff_index"
      ]
    },
    {
      "page": "diff_tb",
      "title": "differences between two tibbles",
      "topics": [
        "diff_tb"
      ]
    },
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      "page": "dx_tb",
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      "topics": [
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      ]
    },
    {
      "page": "empty_dir",
      "title": "detect whether directory is empty recursively",
      "topics": [
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      ]
    },
    {
      "page": "empty_file",
      "title": "detect whether file is empty recursively",
      "topics": [
        "empty_file"
      ]
    },
    {
      "page": "exist_matrix",
      "title": "generate a matrix to show whether the item in each element of a list",
      "topics": [
        "exist_matrix"
      ]
    },
    {
      "page": "expr_pileup",
      "title": "pileup the subexpressions which is atomic",
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      ]
    },
    {
      "page": "extract_kv",
      "title": "extract key and values for a character vector",
      "topics": [
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    },
    {
      "page": "fancy_count",
      "title": "fancy count to show an extended column",
      "topics": [
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      ]
    },
    {
      "page": "fetch_char",
      "title": "fetch character from strings",
      "topics": [
        "fetch_char"
      ]
    },
    {
      "page": "filterC",
      "title": "apply tbflt on dplyr filter",
      "topics": [
        "filterC"
      ]
    },
    {
      "page": "fix_to_regex",
      "title": "trans fixed string into regular expression string",
      "topics": [
        "fix_to_regex"
      ]
    },
    {
      "page": "float_to_percent",
      "title": "from float number to percent number",
      "topics": [
        "float_to_percent"
      ]
    },
    {
      "page": "fps_vector",
      "title": "farthest point sampling (FPS) for a vector",
      "topics": [
        "fps_vector"
      ]
    },
    {
      "page": "full_expand",
      "title": "like 'dplyr::full_join' while ignore the same columns in right tibble",
      "topics": [
        "full_expand"
      ]
    },
    {
      "page": "gen_char",
      "title": "generate characters",
      "topics": [
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      ]
    },
    {
      "page": "gen_combn",
      "title": "generate all combinations",
      "topics": [
        "gen_combn"
      ]
    },
    {
      "page": "gen_outlier",
      "title": "generate outliers from a series of number",
      "topics": [
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      ]
    },
    {
      "page": "gen_str",
      "title": "generate strings",
      "topics": [
        "gen_str"
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    },
    {
      "page": "gen_tb",
      "title": "generate tibbles",
      "topics": [
        "gen_tb"
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    },
    {
      "page": "generate_ticks",
      "title": "generate ticks for a number vector",
      "topics": [
        "generate_ticks"
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    },
    {
      "page": "geom_mean",
      "title": "geometric mean",
      "topics": [
        "geom_mean"
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    },
    {
      "page": "group_vector",
      "title": "group character vector by a regex pattern",
      "topics": [
        "group_vector"
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    },
    {
      "page": "hist_bins",
      "title": "separate numeric x into bins",
      "topics": [
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      ]
    },
    {
      "page": "inner_expand",
      "title": "like 'dplyr::inner_join' while ignore the same columns in right tibble",
      "topics": [
        "inner_expand"
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    },
    {
      "page": "int_digits",
      "title": "trans numbers to a fixed integer digit length",
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        "int_digits"
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    },
    {
      "page": "is.zero",
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      "page": "left_expand",
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      "topics": [
        "left_expand"
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      "page": "list2df",
      "title": "trans list into data.frame",
      "topics": [
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      "page": "max_depth",
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    {
      "page": "mini_diamond",
      "title": "Minimal tibble dataset adjusted from diamond",
      "topics": [
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    },
    {
      "page": "mm_norm",
      "title": "max-min normalization",
      "topics": [
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      ]
    },
    {
      "page": "move_row",
      "title": "move selected rows to target location",
      "topics": [
        "move_row"
      ]
    },
    {
      "page": "near_ticks",
      "title": "the ticks near a number",
      "topics": [
        "near_ticks"
      ]
    },
    {
      "page": "nearest_tick",
      "title": "the nearest ticks around a number",
      "topics": [
        "nearest_tick"
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    },
    {
      "page": "not.na",
      "title": "not NA",
      "topics": [
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    },
    {
      "page": "not.null",
      "title": "not NULL",
      "topics": [
        "not.null"
      ]
    },
    {
      "page": "number_fun_wrapper",
      "title": "wrapper of the functions to process number string with prefix and suffix",
      "topics": [
        "number_fun_wrapper"
      ]
    },
    {
      "page": "ordered_slice",
      "title": "slice a tibble by an ordered vector",
      "topics": [
        "ordered_slice"
      ]
    },
    {
      "page": "percent_to_float",
      "title": "from percent number to float number",
      "topics": [
        "percent_to_float"
      ]
    },
    {
      "page": "pileup_logical",
      "title": "pileup another logical vector on the TRUE values of first vector",
      "topics": [
        "pileup_logical"
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    },
    {
      "page": "pkginfo",
      "title": "information of packages",
      "topics": [
        "pkginfo"
      ]
    },
    {
      "page": "pkglib",
      "title": "load packages as a batch",
      "topics": [
        "pkglib"
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    },
    {
      "page": "pkgver",
      "title": "versions of packages",
      "topics": [
        "pkgver"
      ]
    },
    {
      "page": "pos_int_split",
      "title": "split a positive integer number as a number vector",
      "topics": [
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    },
    {
      "page": "r2c",
      "title": "wrapper of tibble::rownames_to_column",
      "topics": [
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    },
    {
      "page": "read_excel",
      "title": "read excel file",
      "topics": [
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    },
    {
      "page": "read_excel_list",
      "title": "read multi-sheet excel file as a list of tibbles",
      "topics": [
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