Import Excel files created via Citavi Export

Import Excel files created via Citavi Export

read_Citavi_xlsx(
  path = NULL,
  keepMarksCols = TRUE,
  useYearDerived = TRUE,
  setSuggestedColOrder = TRUE,
  setSuggestedColTypes = TRUE,
  ...
)

Arguments

path	Path to the xls/xlsx file created with Citavi via export to Excel.
keepMarksCols	If TRUE (default) it will keep and rename the first three nameless columns of the imported excel file. These columns are automatically created by the Citavi export and contain information about the attachment/paper-clip marker, the red flag marker and the blue circle marker. If kept, the columns are renamed has_attachment, red_flag and blue_circle. If FALSE, these three columns are deleted.
useYearDerived	If TRUE (default) the special column "Year derived" (DE: "Jahr ermittelt") is renamed to "Year" and thus replaces the original basic column "Year" which may have also been created via the Citavi export.
setSuggestedColOrder	If TRUE (default) columns a reordered in a suggested order.
setSuggestedColTypes	If TRUE (default) the col_types = argument of readxl::read_excel() is used. Each column's col_types is automatically determined by matching its name via an internal dataset (data-raw/field_translations.xlsx). Especially when the first entries of any column are empty, this can prevent the issue that occurs when column guessing goes wrong.
...	Other arguments passed to the readxl::read_excel() function.

Value

A tibble containing the information of the xls/xlsx file that was created with Citavi via export to Excel.

Details

Currently this only works for files that were generated while Citavi was set to "English" so that column names are "Short title" etc.

Examples

example_path <- example_file("3dupsin5refs.xlsx") # use this package's example xlsx file
read_Citavi_xlsx(example_path)
#> # A tibble: 5 x 19
#>   ID     Title  Year  `Short title` Author Categories Groups Abstract `DOI name`
#>   <chr>  <chr>  <chr> <chr>         <chr>  <chr>      <chr>  <chr>    <chr>     
#> 1 7e04d~ Estim~ 2019  Schmidt, Har~ Schmi~ 1 catA     Googl~ Broad-s~ 10.2135/c~
#> 2 2481c~ Herit~ 2019  Schmidt, Har~ Schmi~ 1 catA     Googl~ In plan~ 10.1534/g~
#> 3 db3ab~ Herit~ 2019  Schmidt, Har~ Schmi~ 2 catB     PubMed In plan~ NA        
#> 4 ba575~ Hrita~ 2019  Schmidt, Har~ Schmi~ 1 catA     TypoDB In plan~ 10.1534/g~
#> 5 fa402~ More,~ 2018  Schmidt, Möh~ Schmi~ 2 catB     Googl~ Traditi~ 10.2135/c~
#> # ... with 10 more variables: PubMed ID <chr>, Online address <chr>,
#> #   Periodical <chr>, Volume <chr>, Number <chr>, Page range <chr>,
#> #   Locations <chr>, has_attachment <lgl>, red_flag <lgl>, blue_circle <lgl>

if (FALSE) {
CitDat <- read_Citavi_xlsx("data/yourCitaviExport.xlsx")
}