Automatic reading in data from a meta-table of external data sets.

Usage

read_data(x, ...)

# S3 method for class 'data.frame'
read_data(x, name_variable = "name", file_variable = "file", ...)

# S3 method for class 'character'
read_data(
  x,
  data_table,
  fun = NULL,
  frame = parent.frame(),
  name_variable = "name",
  file_variable = "file",
  clean_names_option = FALSE,
  remove_blank_rows_cols_option = FALSE,
  ...
)

Arguments

x: character string or data.frame. If it is a character then it is the name of the object to be created, and referenced within the data to find the file path. If it is a dataframe then read_data is repeated across all the rows of the data.frame.
...: other arguments to supply to fun.
name_variable: character string giving the variable name within data that has the object names to be referenced. Defaults to "name".
file_variable: character string giving the variable name within data that has the file names to be referenced. Defaults to "file".
data_table: data frame containing the meta-table of file paths of the external data files, and their desired R object names.
fun: the function to be used to read in the data file. If unspecified it picks up file extensions ".xsl" and ".xslx" to use readxl::read_xls and readxl::read_xlsx, otherwise uses read.csv. This could actually be any function applied to the file path character string that is extracted from data_table, but a warning is issued if the function name does not contain "read".
frame: Environment in which an object with name given by x is created. Default is parent.frame(). Or if NULL the data read in is returned with no assignment.
clean_names_option: logical to apply the clean_names function internally. Defaults to FALSE for compatibility with apply_macro_dict.
remove_blank_rows_cols_option: logical to apply the remove_blank_rows_cols function internally. Defaults to FALSE for compatibility with apply_macro_dict.

Value

read_data assigns or returns a data frame reading in data from an external file

Details

The idea is to improve the tracibility of reading in external data. This should be used in two steps: create a meta-table in R that has a minimum of 2 columns, one with the name of the R data.frame to be created, and the other giving the file path to the external data; use read_data as a wrapper to read in the data as specified. This ends up with less code, and allows an table of extenral data and associated meta-data to be easily produced using data_table_summary. If options("verbose") is TRUE then read_data will display messages describing what objects have been created.

This is a generic method with methods defined for a character string, and a data.frame. The former just reads in one data.frame, the latter reads in all the data.frames specified.

Methods (by class)

read_data(data.frame): data.frame method for read_data generic
read_data(character): character method for read_data generic

Examples

data_table <- data.frame(
  name = c("dirtydata", "meta"),
  file = c("dirtydata.csv", "meta_table.xlsx"),
  folder = system.file("extdata", package = "cctu"),
  stringsAsFactors = FALSE
)
data_table_summary(data_table)
#>        name            file                                       folder
#> 1 dirtydata   dirtydata.csv /home/runner/work/_temp/Library/cctu/extdata
#> 2      meta meta_table.xlsx /home/runner/work/_temp/Library/cctu/extdata
#>              mod_time
#> 1 2026-06-04 09:21:16
#> 2 2026-06-04 09:21:16
#>                                                 full_file_path
#> 1   /home/runner/work/_temp/Library/cctu/extdata/dirtydata.csv
#> 2 /home/runner/work/_temp/Library/cctu/extdata/meta_table.xlsx
options("verbose" = TRUE)
read_data(data_table)
#> object created in : dirtydata
#> now dyn.load("/home/runner/work/_temp/Library/readxl/libs/readxl.so") ...
#> object created in : meta
summary(dirtydata)
#>    Subject_Id        age              gender    Treatment       start_date
#>  Min.   :1.00   Min.   :19.00   Length   :8   Min.   :1.0   Length   : 8  
#>  1st Qu.:2.25   1st Qu.:24.50   N.unique :3   1st Qu.:1.0   N.unique : 7  
#>  Median :3.50   Median :40.00   N.blank  :2   Median :1.5   N.blank  : 2  
#>  Mean   :3.50   Mean   :38.33   Min.nchar:0   Mean   :1.5   Min.nchar: 0  
#>  3rd Qu.:4.75   3rd Qu.:51.75   Max.nchar:6   3rd Qu.:2.0   Max.nchar:10  
#>  Max.   :6.00   Max.   :56.00                 Max.   :2.0                 
#>  NAs    :2      NAs    :2                     NAs    :2                   
#>     outcome    missing        comments      
#>  Min.   :0.0   Mode:logical   Mode:logical  
#>  1st Qu.:0.0   NAs :8         NAs :8        
#>  Median :0.5                                
#>  Mean   :0.5                                
#>  3rd Qu.:1.0                                
#>  Max.   :1.0                                
#>  NAs    :2                                  
summary(meta)
#>      Completed Checked             Section        Title         Subtitle
#>  Length   :4   Mode:logical   Length   :4   Length   : 4   Length   :4  
#>  N.unique :1   NAs :4         N.unique :2   N.unique : 3   N.unique :2  
#>  N.blank  :0                  N.blank  :0   N.blank  : 0   N.blank  :0  
#>  Min.nchar:2                  Min.nchar:6   Min.nchar: 6   Min.nchar:6  
#>  Max.nchar:2                  Max.nchar:8   Max.nchar:14   Max.nchar:6  
#>  NAs      :1                                               NAs      :1  
#>                                                                         
#>        Number      Population    Orientation Program               Item  
#>  Length   :4   Length   :4    Length   :4    Mode:logical   Length   :4  
#>  N.unique :4   N.unique :2    N.unique :2    NAs :4         N.unique :3  
#>  N.blank  :0   N.blank  :0    N.blank  :0                   N.blank  :0  
#>  Min.nchar:3   Min.nchar:4    Min.nchar:8                   Min.nchar:4  
#>  Max.nchar:5   Max.nchar:6    Max.nchar:9                   Max.nchar:6  
#>                                                                          
#>                                                                          
#>    Junk         Endpoint       Time Points or how to conglomerate
#>  Mode:logical   Mode:logical   Length   : 4                      
#>  NAs :4         NAs :4         N.unique : 1                      
#>                                N.blank  : 0                      
#>                                Min.nchar:15                      
#>                                Max.nchar:15                      
#>                                NAs      : 1                      
#>                                                                  
#>  Covariates or Subgroups Summary Statistics Formal Analysis     Footnote1 
#>  Length   :4             Length   :4        Mode:logical    Length   : 4  
#>  N.unique :1             N.unique :1        NAs :4          N.unique : 1  
#>  N.blank  :0             N.blank  :0                        N.blank  : 0  
#>  Min.nchar:4             Min.nchar:4                        Min.nchar:15  
#>  Max.nchar:4             Max.nchar:4                        Max.nchar:15  
#>  NAs      :3             NAs      :3                        NAs      : 2  
#>                                                                           
#>  Footnote2         fontsize 
#>  Mode:logical   Min.   :16  
#>  NAs :4         1st Qu.:17  
#>                 Median :18  
#>                 Mean   :18  
#>                 3rd Qu.:19  
#>                 Max.   :20  
#>                 NAs    :1