Generates the code for loading a dataset and returns both the code and the contents
Usage
UD_ds_read(
state,
data_file_ext = NULL,
data_file_local = NULL,
data_file = NULL,
sheets = NULL,
sheet = NULL
)Arguments
- state
UD state from
UD_fetch_state()- data_file_ext
File extension of the uploaded file (e.g. "xlsx", "csv", etc).
- data_file_local
Full path to the data file on the server.
- data_file
Dataset file name without the path.
- sheets
If the uploaded file is an excel file, this is a character vector of the sheets present in that file.
- sheet
If the uploaded file is an excel file, this is the currently selected sheet.
Examples
# We need a module state object to use this function:
id="UD"
sess_res = UD_test_mksession(session=list())
#> → UD: including file
#> → UD: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → UD: dest: file.path("config","report.docx")
#> → UD: including file
#> → UD: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → UD: dest: file.path("config","report.pptx")
#> → UD: including file
#> → UD: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → UD: dest: file.path("config","report.yaml")
#> → UD: State initialized
#> → UD: module checksum updated:897d952fecbc804999396a96f9df4b20
state = sess_res$state
# This is the full path to a test data file:
data_file_local = system.file(package="formods", "test_data", "TEST_DATA.xlsx")
# Excel file extension
data_file_ext = "xlsx"
# Base file name
data_file = "TEST_DATA.xlsx"
# Excel files need a sheet specification:
sheet = "DATA"
# We will also attach the sheets along with it
sheets = readxl::excel_sheets(data_file_local)
ds_read_res = UD_ds_read(state,
data_file_ext = data_file_ext,
data_file_local = data_file_local,
data_file = data_file,
sheets = sheets,
sheet = sheet)
ds_read_res
#> $contents
#> # A tibble: 10,680 × 33
#> ID TIME_DY TIME_HR NTIME_DY NTIME_HR TIME AMT DV RECDESC DOSE
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl>
#> 1 1 0 0 0 0 0 3000000 0 dose 3000000
#> 2 1 0 0 0 0 0 0 1250 BM_ng_ml 3000000
#> 3 1 0 0 0 0 0 0 0 C_ng_ml 3000000
#> 4 1 1 24 1 24 24 0 1647 BM_ng_ml 3000000
#> 5 1 1 24 1 24 24 0 690. C_ng_ml 3000000
#> 6 1 2 48 2 48 48 0 1947 BM_ng_ml 3000000
#> 7 1 2 48 2 48 48 0 588. C_ng_ml 3000000
#> 8 1 3 72 3 72 72 0 2170 BM_ng_ml 3000000
#> 9 1 3 72 3 72 72 0 506. C_ng_ml 3000000
#> 10 1 4 96 4 96 96 0 2332 BM_ng_ml 3000000
#> # ℹ 10,670 more rows
#> # ℹ 23 more variables: DOSE_STR <chr>, Cohort <chr>, ROUTE <chr>, WT <dbl>,
#> # SUBTYPE <chr>, SEX <chr>, F1 <dbl>, ka <dbl>, CL <dbl>, Vc <dbl>, Vp <dbl>,
#> # Q <dbl>, BM_IC <dbl>, kdeg_BM <dbl>, Emax <dbl>, EC50 <dbl>, CMT <chr>,
#> # DUR <dbl>, EVID <dbl>, NDose <chr>, DOSE_NUM <dbl>, SUBTYPE_ID <dbl>,
#> # SEX_ID <dbl>
#>
#> $object_name
#> [1] "myDS"
#>
#> $isgood
#> [1] TRUE
#>
#> $code
#> [1] "myDS = readxl::read_excel(path=\"TEST_DATA.xlsx\", sheet=\"DATA\")\nmyDS = janitor::clean_names(myDS, case=\"none\")"
#>