inmetwrangler.Rcheck/00_pkg_src/inmetwrangler/R/import_txt_files_inmet.R
In lhmet/inmetwrangler: Functions to Wrangle Data Files from INMET Weather Stations
#' Read ASCII data file of INMET's automatic weather stations
#' @importFrom dplyr %>%
#' @importFrom stats setNames
#' @importFrom utils head
#' @param .file path to file
#' @param .verbose logical value, when it is set to TRUE show warnings
#' and messages
#' @param .only.problems logical value. Set TRUE to report problems,
#' FALSE to return meteorological data
#' @param .full.names a logical value. If TRUE, the directory path is prepended
#' to the file names to give a relative file path. If FALSE, the file names
#' (rather than paths) are returned.
#' @details When \code{only.problems} is TRUE a data frame with one row for
#' each problem found for every file. When the files do not have any problem the
#' data frame is returned empty (0 rows).
#' @return A data frame with one row for each problem and four columns:
#' \item{row,col}{Row and column of problem}
#' \item{expected}{What readr expected to find}
#' \item{actual}{What it actually got}
#' \item{file}{file name or the path to file (if \code{.full.names} is TRUE)}
#' @export
read_txt_file_inmet <- function(.file,
.verbose = TRUE,
.only.problems = FALSE,
.full.names = FALSE){
# .file <- "inst/extdata/A805.txt"; .verbose = TRUE; .only.problems = TRUE
# .file <- "inst/extdata/A838.txt"; .verbose = TRUE; .only.problems = TRUE
# .file <- "inst/extdata/A803.txt"; .verbose = TRUE; .only.problems = TRUE
# .file <- "inst/extdata/A852.txt"; .verbose = TRUE; .only.problems = TRUE
# .file = txt_files[3]; .verbose = FALSE; .only.problems = TRUE
stopifnot(is.character(.file),
is.logical(.verbose),
is.logical(.only.problems),
file.exists(.file))
# raw data
all_lines <- readr::read_lines(.file)
# station id used to extract the data from database
# with SQL command SELECT
# should match the id column values of dataset
aws_id_from_sql_cmd <- all_lines %>%
purrr::keep(., .p = ~stringr::str_detect(.x, "SELECT")) %>%
#keep(., .p = function(x) str_detect("SELECT"))
stringr::str_extract(., "[A-Za-z]{1}[0-9]{3,4}") %>%
stringr::str_to_upper(.)
if (.verbose) {
message("-------------------------------------------")
message(.file)
message('AWS ID from header: ', aws_id_from_sql_cmd)
}
stopifnot(aws_id_from_sql_cmd ==
stringr::str_extract(basename(.file), "[A-Za-z]{1}[0-9]{3,4}") )
# head(read_lines(.file))
# tail(read_lines(.file))
# rows limits to extract data
row_limits <- all_lines %>%
stringr::str_detect("pre>") %>%
#str_detect(., "[A-Za-z]{1}[0-9]{3,4}") %>%
which() # %>%range()
# set file_format (2 cases according to header files pattern)
if (length(row_limits) == 2) {
file_format <- 1
## header pattern
#"<html><head>"
#"<meta http-equiv=\"content-type\" content=\"text/html; charset=windows-1252\"></head><body>Sql"
#" - SELECT * FROM cadRema WHERE RemaEstacao='a807' and RemaData BETWEEN "
#"'2010-01-01' AND '2011-12-31' ORDER BY RemaEstacao,RemaData,RemaHora <br><pre>A807 2010 01 01 00 11.6 21 18.1 18.7 18.1 94 94 88 17.1 17.1 16.6 911.4 911.4 910.8 2.9 122 9.5 -2.240 0.0 / //// ///// ///// ="
} else {
file_format <- 2
# header pattern
#"Sql - SELECT * FROM cadRema WHERE RemaEstacao='A880' and RemaData BETWEEN '2010-01-01' AND '2011-12-31' ORDER BY RemaEstacao,RemaData,RemaHora "
#""
#"A880 2010 01 01 00 12.3 17 14.7 16.0 14.7 80 81 76 11.3 12.6 11.3 906.8 906.8 906.5 4.6 106 9.5 -3.538 0.0 / //// ///// ///// ="
}
var_names <- c("site", "year", "month", "day", "hour_utc",
"tens_bat", "temp_cpu",
"tair_inst", "tair_max", "tair_min",
"rh_inst", "rh_max", "rh_min",
"tdew_inst", "tdew_max", "tdew_min",
"press_inst", "press_max", "press_min",
"ws", "wd", "ws_max",
"rg", "prec", "cld_tot", "cld_cod", "cld_base",
"visib", "trash")
#all_lines[row_limits]
# file format 1 ---------------------------------------------------------------
if (file_format == 1) {
# raw txt file
rows_inner <- row_limits + c(1,-1)
#all_lines[row_limits]
# continuous rows of data
data_rows <- all_lines[rows_inner[1]:rows_inner[2]]
# data collapsed to header
data_1st_row <- all_lines[rows_inner[1] - 1] %>%
stringr::str_split(., "<pre>") %>%
unlist() %>%
magrittr::extract(2)
#a <- fread(txt_files[1], nrows = row_limits[2]-1, skip = row_limits[1]-1)
data_rows <- c(data_1st_row, data_rows)
#head(data_rows);
#tail(data_rows)
if (.verbose) {
hdata <- data_rows %>%
paste0(., collapse = "\n") %>%
readr::read_delim(.,
delim = " ",
skip = 2,
col_names = FALSE,
na = c("//////","/////", "////",
"///", "//", "/", "="),
guess_max = 16000) %>%
setNames(var_names) %>%
dplyr::select(-trash)
} else {
hdata <- data_rows %>%
paste0(., collapse = "\n")
hdata <- suppressWarnings(
readr::read_delim(hdata,
delim = " ",
skip = 2,
col_names = FALSE,
na = c("//////","/////", "////",
"///", "//", "/", "="),
guess_max = 16000)
)
hdata <- hdata %>%
setNames(var_names) %>%
dplyr::select(-trash)
}# end if .verbose
probs <- readr::problems(hdata)
# because data were read with read_file
if (nrow(probs) > 0) {
probs <- dplyr::mutate(probs,
row = row + 2,
file = ifelse(.full.names,
.file,
basename(.file))
)
} else {
#probs <- NULL
probs <- tibble::tibble(
row = 0,
row_file = 0,
col = 0,
expected = paste(ncol(hdata), "columns"),
actual = paste(ncol(hdata), "columns"),
file = ifelse(.full.names,
.file,
basename(.file))
)
}
if (.only.problems) return(probs)
#extract_num <- function(x) as.numeric(gsub("[^0-9.-]+", "", as.character(x)))
#pn <- parse_number(hdata$tair_max); attr(pn, "problems")
#hdata$tair_max[is.na(parse_number(hdata$tair_max))]
hdata <- suppressWarnings(dplyr::mutate_at(hdata,
dplyr::vars(tens_bat:prec),
readr::parse_number))
hdata <- dplyr::mutate_at(hdata,
dplyr::vars(site, cld_tot:visib),
readr::parse_character)
hdata <- dplyr::mutate_at(hdata,
dplyr::vars(year:hour_utc),
readr::parse_integer)
# hdata
} else {
# file format 2 ---------------------------------------------------------------
## txt file cleaned manualy
# head(all_lines)
# tail(all_lines)
# .file <- "../data-raw/RAW-DATA-8o-DISME/data_piece_A803.txt"
#.file <- "~/rows_prob_a803.txt"
# read_delim ignore empty rows (the last) and report problems better than data.table
to_skip <- which(head(all_lines) == "")
# to discover cols type
# cols_specif <- spec_delim(.file,
# delim = " ",
# guess_max=14000,
# col_names = FALSE,
# skip = 2,
# #na = c("//////","/////", "////", "///", "//", "/", "=")
# )
if (.verbose) {
hdata <- readr::read_file(.file) %>%
#stringi::stri_enc_toutf8(.) %>%
#stringi::stri_conv(x, to = "UTF-8", from = "latin1")
#stringr::str_replace_all(., "[/]{1,6}", "NA") %>%
readr::read_delim(.,
delim = " ",
# because A804 was send after others
# and A803
skip = to_skip,
col_names = FALSE,
na = c("//////","/////", "////", "///", "//", "/", "="),
guess_max = 16000
) %>%
setNames(var_names) %>%
dplyr::select(-trash)
} else {
hdata <- readr::read_file(.file)
#stringi::stri_enc_toutf8(.) %>%
#stringi::stri_conv(x, to = "UTF-8", from = "latin1")
#stringr::str_replace_all(., "[/]{1,6}", "NA") %>%
hdata <- suppressWarnings(
readr::read_delim(hdata,
delim = " ",
# because A804 was send after others
# and A803
skip = to_skip,
col_names = FALSE,
na = c("//////","/////", "////", "///", "//", "/", "="),
guess_max = 16000)
)
hdata <- hdata %>%
setNames(var_names) %>%
dplyr::select(-trash)
} # end if .verbose
probs <- readr::problems(hdata)
# View(hdata[probs[["row"]], ])
# because data were read with read_file
if (nrow(probs) > 0) {
probs <- dplyr::mutate(probs,
row_file = row + to_skip,
file = ifelse(.full.names,
.file,
basename(.file))
)
} else {
#probs <- NULL
probs <- tibble::tibble(
row = 0,
row_file = 0,
col = 0,
expected = paste(ncol(hdata), "columns"),
actual = paste(ncol(hdata), "columns"),
file = ifelse(.full.names,
.file,
basename(.file))
)
}
if (.only.problems) return(probs)
# r <- probs[, "row"] %>% t() %>% c()
# slice(hdata, r) %>% select(-(tair_inst:tdew_min))
# hdata2 <- data.table::fread(.file,
# stringsAsFactors = FALSE,
# header = FALSE,
# skip = 2,
# #fill = TRUE,
# na.strings = c("//////","/////", "////", "///", "//", "/", "=")
# ) %>%
# as_tibble() %>%
#View(hdata2[probs[["row"]], ])
# setNames(var_names) %>%
# select(-trash)
hdata <- suppressWarnings(dplyr::mutate_at(hdata,
dplyr::vars(tens_bat:prec),
readr::parse_number))
hdata <- dplyr::mutate_at(hdata,
dplyr::vars(site, cld_tot:visib),
readr::parse_character)
hdata <- dplyr::mutate_at(hdata,
dplyr::vars(year:hour_utc),
readr::parse_integer)
}# end else file_format
# tail(hdata)
hdata <- hdata %>%
# because data.table::fread read empty
#filter(site != "")
dplyr::mutate(.,
date = paste0(year, "-", month, "-", day, " ", hour_utc, ":00:00"),
date = as.POSIXct(date, tz = "UTC")) %>%
dplyr::select(., site, date, tens_bat:visib) %>%
dplyr::arrange(date)
return(hdata)
}
#' Import raw data files of automatic stations
#'
#' @param files character vector with path to files
#' @param verbose logical scalar. If TRUE, print messages and warnings.
#' @param only.problems logical value. Set TRUE to return a tibble
#' with problems information on file and FALSE to return meteorological data.
#' @param full.names a logical value. If TRUE, the directory path is prepended
#' to the file names to give a relative file path. If FALSE, the file names
#' (rather than paths) are returned.
#' @return A data frame with one row for each problem and four columns:
#' \item{row,col}{Row and column of problem}
#' \item{expected}{What readr expected to find}
#' \item{actual}{What it actually got}
#' \item{file}{file name or the path to file (if \code{full.names} is TRUE)}
#' @export
#' @examples
#'
#' library(dplyr); library(purrr); library(stringr); library(readr)
#'# missing columns problem example
#'myfile <- system.file("extdata", "A838.txt", package = "inmetwrangler")
#'myfile
#' A838_problems <- import_txt_files_inmet(files = myfile,
#' verbose = TRUE,
#' only.problems = TRUE)
#' A838_data <- import_txt_files_inmet(files = myfile,
#' verbose = TRUE,
#' only.problems = FALSE)
#'#looking at rows
#'for(irow in A838_problems$row) read_lines(myfile, skip = irow-2, n_max = irow+2)
#'# View(slice(A838_data, A838_problems$row)) # columns filled with NAs
import_txt_files_inmet <- function(files,
verbose = TRUE,
only.problems = FALSE,
full.names = FALSE){
res_tbl <- purrr::map_df(files,
~read_txt_file_inmet(.x,
.only.problems = only.problems,
.verbose = verbose,
.full.names = full.names
))
if (only.problems) {
res_tbl <- dplyr::filter( res_tbl,
row > 0 #|
#(readr::parse_number(expected) != readr::parse_number(actual))
)
}# end if prob
return(res_tbl)
}
lhmet/inmetwrangler documentation built on May 15, 2019, 1:42 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
#' Read ASCII data file of INMET's automatic weather stations
#' @importFrom dplyr %>%
#' @importFrom stats setNames
#' @importFrom utils head
#' @param .file path to file
#' @param .verbose logical value, when it is set to TRUE show warnings
#' and messages
#' @param .only.problems logical value. Set TRUE to report problems,
#' FALSE to return meteorological data
#' @param .full.names a logical value. If TRUE, the directory path is prepended
#' to the file names to give a relative file path. If FALSE, the file names
#' (rather than paths) are returned.
#' @details When \code{only.problems} is TRUE a data frame with one row for
#' each problem found for every file. When the files do not have any problem the
#' data frame is returned empty (0 rows).
#' @return A data frame with one row for each problem and four columns:
#' \item{row,col}{Row and column of problem}
#' \item{expected}{What readr expected to find}
#' \item{actual}{What it actually got}
#' \item{file}{file name or the path to file (if \code{.full.names} is TRUE)}
#' @export
read_txt_file_inmet <- function(.file,
.verbose = TRUE,
.only.problems = FALSE,
.full.names = FALSE){
# .file <- "inst/extdata/A805.txt"; .verbose = TRUE; .only.problems = TRUE
# .file <- "inst/extdata/A838.txt"; .verbose = TRUE; .only.problems = TRUE
# .file <- "inst/extdata/A803.txt"; .verbose = TRUE; .only.problems = TRUE
# .file <- "inst/extdata/A852.txt"; .verbose = TRUE; .only.problems = TRUE
# .file = txt_files[3]; .verbose = FALSE; .only.problems = TRUE
stopifnot(is.character(.file),
is.logical(.verbose),
is.logical(.only.problems),
file.exists(.file))
# raw data
all_lines <- readr::read_lines(.file)
# station id used to extract the data from database
# with SQL command SELECT
# should match the id column values of dataset
aws_id_from_sql_cmd <- all_lines %>%
purrr::keep(., .p = ~stringr::str_detect(.x, "SELECT")) %>%
#keep(., .p = function(x) str_detect("SELECT"))
stringr::str_extract(., "[A-Za-z]{1}[0-9]{3,4}") %>%
stringr::str_to_upper(.)
if (.verbose) {
message("-------------------------------------------")
message(.file)
message('AWS ID from header: ', aws_id_from_sql_cmd)
}
stopifnot(aws_id_from_sql_cmd ==
stringr::str_extract(basename(.file), "[A-Za-z]{1}[0-9]{3,4}") )
# head(read_lines(.file))
# tail(read_lines(.file))
# rows limits to extract data
row_limits <- all_lines %>%
stringr::str_detect("pre>") %>%
#str_detect(., "[A-Za-z]{1}[0-9]{3,4}") %>%
which() # %>%range()
# set file_format (2 cases according to header files pattern)
if (length(row_limits) == 2) {
file_format <- 1
## header pattern
#"<html><head>"
#"<meta http-equiv=\"content-type\" content=\"text/html; charset=windows-1252\"></head><body>Sql"
#" - SELECT * FROM cadRema WHERE RemaEstacao='a807' and RemaData BETWEEN "
#"'2010-01-01' AND '2011-12-31' ORDER BY RemaEstacao,RemaData,RemaHora <br><pre>A807 2010 01 01 00 11.6 21 18.1 18.7 18.1 94 94 88 17.1 17.1 16.6 911.4 911.4 910.8 2.9 122 9.5 -2.240 0.0 / //// ///// ///// ="
} else {
file_format <- 2
# header pattern
#"Sql - SELECT * FROM cadRema WHERE RemaEstacao='A880' and RemaData BETWEEN '2010-01-01' AND '2011-12-31' ORDER BY RemaEstacao,RemaData,RemaHora "
#""
#"A880 2010 01 01 00 12.3 17 14.7 16.0 14.7 80 81 76 11.3 12.6 11.3 906.8 906.8 906.5 4.6 106 9.5 -3.538 0.0 / //// ///// ///// ="
}
var_names <- c("site", "year", "month", "day", "hour_utc",
"tens_bat", "temp_cpu",
"tair_inst", "tair_max", "tair_min",
"rh_inst", "rh_max", "rh_min",
"tdew_inst", "tdew_max", "tdew_min",
"press_inst", "press_max", "press_min",
"ws", "wd", "ws_max",
"rg", "prec", "cld_tot", "cld_cod", "cld_base",
"visib", "trash")
#all_lines[row_limits]
# file format 1 ---------------------------------------------------------------
if (file_format == 1) {
# raw txt file
rows_inner <- row_limits + c(1,-1)
#all_lines[row_limits]
# continuous rows of data
data_rows <- all_lines[rows_inner[1]:rows_inner[2]]
# data collapsed to header
data_1st_row <- all_lines[rows_inner[1] - 1] %>%
stringr::str_split(., "<pre>") %>%
unlist() %>%
magrittr::extract(2)
#a <- fread(txt_files[1], nrows = row_limits[2]-1, skip = row_limits[1]-1)
data_rows <- c(data_1st_row, data_rows)
#head(data_rows);
#tail(data_rows)
if (.verbose) {
hdata <- data_rows %>%
paste0(., collapse = "\n") %>%
readr::read_delim(.,
delim = " ",
skip = 2,
col_names = FALSE,
na = c("//////","/////", "////",
"///", "//", "/", "="),
guess_max = 16000) %>%
setNames(var_names) %>%
dplyr::select(-trash)
} else {
hdata <- data_rows %>%
paste0(., collapse = "\n")
hdata <- suppressWarnings(
readr::read_delim(hdata,
delim = " ",
skip = 2,
col_names = FALSE,
na = c("//////","/////", "////",
"///", "//", "/", "="),
guess_max = 16000)
)
hdata <- hdata %>%
setNames(var_names) %>%
dplyr::select(-trash)
}# end if .verbose
probs <- readr::problems(hdata)
# because data were read with read_file
if (nrow(probs) > 0) {
probs <- dplyr::mutate(probs,
row = row + 2,
file = ifelse(.full.names,
.file,
basename(.file))
)
} else {
#probs <- NULL
probs <- tibble::tibble(
row = 0,
row_file = 0,
col = 0,
expected = paste(ncol(hdata), "columns"),
actual = paste(ncol(hdata), "columns"),
file = ifelse(.full.names,
.file,
basename(.file))
)
}
if (.only.problems) return(probs)
#extract_num <- function(x) as.numeric(gsub("[^0-9.-]+", "", as.character(x)))
#pn <- parse_number(hdata$tair_max); attr(pn, "problems")
#hdata$tair_max[is.na(parse_number(hdata$tair_max))]
hdata <- suppressWarnings(dplyr::mutate_at(hdata,
dplyr::vars(tens_bat:prec),
readr::parse_number))
hdata <- dplyr::mutate_at(hdata,
dplyr::vars(site, cld_tot:visib),
readr::parse_character)
hdata <- dplyr::mutate_at(hdata,
dplyr::vars(year:hour_utc),
readr::parse_integer)
# hdata
} else {
# file format 2 ---------------------------------------------------------------
## txt file cleaned manualy
# head(all_lines)
# tail(all_lines)
# .file <- "../data-raw/RAW-DATA-8o-DISME/data_piece_A803.txt"
#.file <- "~/rows_prob_a803.txt"
# read_delim ignore empty rows (the last) and report problems better than data.table
to_skip <- which(head(all_lines) == "")
# to discover cols type
# cols_specif <- spec_delim(.file,
# delim = " ",
# guess_max=14000,
# col_names = FALSE,
# skip = 2,
# #na = c("//////","/////", "////", "///", "//", "/", "=")
# )
if (.verbose) {
hdata <- readr::read_file(.file) %>%
#stringi::stri_enc_toutf8(.) %>%
#stringi::stri_conv(x, to = "UTF-8", from = "latin1")
#stringr::str_replace_all(., "[/]{1,6}", "NA") %>%
readr::read_delim(.,
delim = " ",
# because A804 was send after others
# and A803
skip = to_skip,
col_names = FALSE,
na = c("//////","/////", "////", "///", "//", "/", "="),
guess_max = 16000
) %>%
setNames(var_names) %>%
dplyr::select(-trash)
} else {
hdata <- readr::read_file(.file)
#stringi::stri_enc_toutf8(.) %>%
#stringi::stri_conv(x, to = "UTF-8", from = "latin1")
#stringr::str_replace_all(., "[/]{1,6}", "NA") %>%
hdata <- suppressWarnings(
readr::read_delim(hdata,
delim = " ",
# because A804 was send after others
# and A803
skip = to_skip,
col_names = FALSE,
na = c("//////","/////", "////", "///", "//", "/", "="),
guess_max = 16000)
)
hdata <- hdata %>%
setNames(var_names) %>%
dplyr::select(-trash)
} # end if .verbose
probs <- readr::problems(hdata)
# View(hdata[probs[["row"]], ])
# because data were read with read_file
if (nrow(probs) > 0) {
probs <- dplyr::mutate(probs,
row_file = row + to_skip,
file = ifelse(.full.names,
.file,
basename(.file))
)
} else {
#probs <- NULL
probs <- tibble::tibble(
row = 0,
row_file = 0,
col = 0,
expected = paste(ncol(hdata), "columns"),
actual = paste(ncol(hdata), "columns"),
file = ifelse(.full.names,
.file,
basename(.file))
)
}
if (.only.problems) return(probs)
# r <- probs[, "row"] %>% t() %>% c()
# slice(hdata, r) %>% select(-(tair_inst:tdew_min))
# hdata2 <- data.table::fread(.file,
# stringsAsFactors = FALSE,
# header = FALSE,
# skip = 2,
# #fill = TRUE,
# na.strings = c("//////","/////", "////", "///", "//", "/", "=")
# ) %>%
# as_tibble() %>%
#View(hdata2[probs[["row"]], ])
# setNames(var_names) %>%
# select(-trash)
hdata <- suppressWarnings(dplyr::mutate_at(hdata,
dplyr::vars(tens_bat:prec),
readr::parse_number))
hdata <- dplyr::mutate_at(hdata,
dplyr::vars(site, cld_tot:visib),
readr::parse_character)
hdata <- dplyr::mutate_at(hdata,
dplyr::vars(year:hour_utc),
readr::parse_integer)
}# end else file_format
# tail(hdata)
hdata <- hdata %>%
# because data.table::fread read empty
#filter(site != "")
dplyr::mutate(.,
date = paste0(year, "-", month, "-", day, " ", hour_utc, ":00:00"),
date = as.POSIXct(date, tz = "UTC")) %>%
dplyr::select(., site, date, tens_bat:visib) %>%
dplyr::arrange(date)
return(hdata)
}
#' Import raw data files of automatic stations
#'
#' @param files character vector with path to files
#' @param verbose logical scalar. If TRUE, print messages and warnings.
#' @param only.problems logical value. Set TRUE to return a tibble
#' with problems information on file and FALSE to return meteorological data.
#' @param full.names a logical value. If TRUE, the directory path is prepended
#' to the file names to give a relative file path. If FALSE, the file names
#' (rather than paths) are returned.
#' @return A data frame with one row for each problem and four columns:
#' \item{row,col}{Row and column of problem}
#' \item{expected}{What readr expected to find}
#' \item{actual}{What it actually got}
#' \item{file}{file name or the path to file (if \code{full.names} is TRUE)}
#' @export
#' @examples
#'
#' library(dplyr); library(purrr); library(stringr); library(readr)
#'# missing columns problem example
#'myfile <- system.file("extdata", "A838.txt", package = "inmetwrangler")
#'myfile
#' A838_problems <- import_txt_files_inmet(files = myfile,
#' verbose = TRUE,
#' only.problems = TRUE)
#' A838_data <- import_txt_files_inmet(files = myfile,
#' verbose = TRUE,
#' only.problems = FALSE)
#'#looking at rows
#'for(irow in A838_problems$row) read_lines(myfile, skip = irow-2, n_max = irow+2)
#'# View(slice(A838_data, A838_problems$row)) # columns filled with NAs
import_txt_files_inmet <- function(files,
verbose = TRUE,
only.problems = FALSE,
full.names = FALSE){
res_tbl <- purrr::map_df(files,
~read_txt_file_inmet(.x,
.only.problems = only.problems,
.verbose = verbose,
.full.names = full.names
))
if (only.problems) {
res_tbl <- dplyr::filter( res_tbl,
row > 0 #|
#(readr::parse_number(expected) != readr::parse_number(actual))
)
}# end if prob
return(res_tbl)
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.