Skip to contents

Read delimited data for optimal use with daiquiri

Source: R/main.R
read_data.Rd

Popular file readers such as readr::read_delim() perform datatype conversion by default, which can interfere with daiquiri's ability to detect non-conformant values. Use this function instead to ensure optimal compatibility with daiquiri's features.

Usage

read_data(
  file,
  delim = NULL,
  col_names = TRUE,
  quote = "\"",
  trim_ws = TRUE,
  comment = "",
  skip = 0,
  n_max = Inf,
  show_progress = TRUE
)

Arguments

file

A string containing path of file containing data to load, or a URL starting http://, file://, etc. Compressed files with extension .gz, .bz2, .xz and .zip are supported.

delim

Single character used to separate fields within a record. E.g. "," or "\t"

col_names

Either TRUE, FALSE or a character vector of column names. If TRUE, the first row of the input will be used as the column names, and will not be included in the data frame. If FALSE, column names will be generated automatically. Default = TRUE

quote

Single character used to quote strings.

trim_ws

Should leading and trailing whitespace be trimmed from each field?

comment

A string used to identify comments. Any text after the comment characters will be silently ignored

skip

Number of lines to skip before reading data. If comment is supplied any commented lines are ignored after skipping

n_max

Maximum number of lines to read.

show_progress

Display a progress bar? Default = TRUE

Value

A data frame

Details

This function is aimed at non-expert users of R, and operates as a restricted implementation of readr::read_delim(). If you prefer to use read_delim() directly, ensure you set the following parameters: col_types = readr::cols(.default = "c") and na = character()

See also

field_types(), field_types_available(), aggregate_data(), report_data(), daiquiri_report()

Examples

raw_data <- read_data(
  system.file("extdata", "example_prescriptions.csv", package = "daiquiri"),
  delim = ",",
  col_names = TRUE
)

head(raw_data)
#> # A tibble: 6 × 8
#>   PrescriptionID PrescriptionDate    Admis…¹ Drug  Dose  DoseU…² Patie…³ Locat…⁴
#>   <chr>          <chr>               <chr>   <chr> <chr> <chr>   <chr>   <chr>  
#> 1 6000           2021-01-01 00:00:00 2020-1… Ceft… 500   mg      4993679 SITE1  
#> 2 6001           NULL                2020-1… Fluc… 1000  mg      819452  SITE1  
#> 3 6002           NULL                2020-1… Teic… 400   mg      275597  SITE1  
#> 4 6003           2021-01-01 01:00:00 2020-1… Fluc… 1000  NULL    819452  SITE1  
#> 5 6004           2021-01-01 02:00:00 2020-1… Fluc… 1000  NULL    528071  SITE1  
#> 6 6005           2021-01-01 03:00:00 2020-1… Co-a… 1.2   g       1001434 SITE1  
#> # … with abbreviated variable names ¹​AdmissionDate, ²​DoseUnit, ³​PatientID,
#> #   ⁴​Location