scda TealDatasetConnector
scda_dataset_connector.Rd![[Stable]](figures/lifecycle-stable.svg)
Usage
scda_dataset_connector(
dataname,
scda_dataname = tolower(dataname),
scda_name = "latest",
keys = character(0),
label = character(0),
code = character(0),
script = character(0),
metadata = list(type = "scda", version = scda_name)
)
scda_cdisc_dataset_connector(
dataname,
scda_dataname = tolower(dataname),
scda_name = "latest",
keys = get_cdisc_keys(dataname),
parent = if (identical(dataname, "ADSL")) character(0L) else "ADSL",
label = character(0),
code = character(0),
script = character(0),
metadata = list(type = "scda", version = scda_name)
)Arguments
- dataname
(
character)
A given name for the dataset it may not contain spaces- scda_dataname
(
character) whichscdadataset to use (e.g.adsl).- scda_name
(
character) which version ofscdadata to take, default "latest".- keys
optional, (
character)
vector of dataset primary keys column names- label
(
character)
Label to describe the dataset.- code
(
character)
A character string defining code to modifyraw_datafrom this dataset. To modify current dataset code should contain at least one assignment to object defined indatanameargument. For example ifdataname = ADSLexample code should containADSL <- <some R code>. Can't be used simultaneously withscript- script
(
character)
Alternatively tocode- location of the file containing modification code. Can't be used simultaneously withscript.- metadata
(named
list,NULLorCallableFunction)
Field containing either the metadata about the dataset (each element of the list should be atomic and length one) or aCallableFuntionto pull the metadata from a connection. This should return alistor an object which can be converted to a list withas.list.- parent
(
character, optional) parent dataset name
Details
Create a TealDatasetConnector for dataset in scda
Create a CDISCTealDatasetConnector from scda data
Examples
library(scda)
x <- scda_dataset_connector(
dataname = "ADSL", scda_dataname = "adsl",
)
x$get_code()
#> [1] "ADSL <- scda::synthetic_cdisc_dataset(dataset_name = \"adsl\", name = \"latest\")"
load_dataset(x)
get_dataset(x)
#> A TealDataset object containing the following data.frame (400 rows and 44 columns):
#> STUDYID USUBJID SUBJID SITEID AGE AGEU SEX
#> 1 AB12345 AB12345-CHN-3-id-128 id-128 CHN-3 32 YEARS M
#> 2 AB12345 AB12345-CHN-15-id-262 id-262 CHN-15 35 YEARS M
#> 3 AB12345 AB12345-RUS-3-id-378 id-378 RUS-3 30 YEARS F
#> 4 AB12345 AB12345-CHN-11-id-220 id-220 CHN-11 26 YEARS F
#> 5 AB12345 AB12345-CHN-7-id-267 id-267 CHN-7 40 YEARS M
#> 6 AB12345 AB12345-CHN-15-id-201 id-201 CHN-15 49 YEARS M
#> RACE ETHNIC COUNTRY DTHFL INVID
#> 1 ASIAN NOT HISPANIC OR LATINO CHN N INV ID CHN-3
#> 2 BLACK OR AFRICAN AMERICAN NOT HISPANIC OR LATINO CHN N INV ID CHN-15
#> 3 ASIAN NOT HISPANIC OR LATINO RUS N INV ID RUS-3
#> 4 ASIAN NOT HISPANIC OR LATINO CHN N INV ID CHN-11
#> 5 ASIAN UNKNOWN CHN N INV ID CHN-7
#> 6 ASIAN NOT HISPANIC OR LATINO CHN N INV ID CHN-15
#> INVNAM ARM ARMCD ACTARM ACTARMCD TRT01P
#> 1 Dr. CHN-3 Doe A: Drug X ARM A A: Drug X ARM A A: Drug X
#> 2 Dr. CHN-15 Doe C: Combination ARM C C: Combination ARM C C: Combination
#> 3 Dr. RUS-3 Doe C: Combination ARM C C: Combination ARM C C: Combination
#> 4 Dr. CHN-11 Doe B: Placebo ARM B B: Placebo ARM B B: Placebo
#> 5 Dr. CHN-7 Doe B: Placebo ARM B B: Placebo ARM B B: Placebo
#> 6 Dr. CHN-15 Doe C: Combination ARM C C: Combination ARM C C: Combination
#> TRT01A REGION1 STRATA1 STRATA2 BMRKR1 BMRKR2 ITTFL SAFFL BMEASIFL
#> 1 A: Drug X Asia C S2 14.424934 MEDIUM Y Y Y
#> 2 C: Combination Asia C S1 4.055463 LOW Y Y N
#> 3 C: Combination Eurasia A S1 2.803240 HIGH Y Y Y
#> 4 B: Placebo Asia B S2 10.262734 MEDIUM Y Y Y
#> 5 B: Placebo Asia C S1 6.206763 LOW Y Y N
#> 6 C: Combination Asia C S2 6.906799 MEDIUM Y Y Y
#> BEP01FL RANDDT TRTSDTM TRTEDTM EOSSTT
#> 1 Y 2019-02-22 2019-02-24 11:09:18 2021-02-23 22:47:42 COMPLETED
#> 2 N 2019-02-26 2019-02-26 09:05:00 2021-02-25 20:43:24 COMPLETED
#> 3 N 2019-02-24 2019-02-28 03:19:08 2021-02-27 14:57:32 COMPLETED
#> 4 Y 2019-02-27 2019-03-01 13:33:03 2021-03-01 01:11:27 COMPLETED
#> 5 N 2019-03-01 2019-03-02 00:09:16 2021-03-01 11:47:40 COMPLETED
#> 6 N 2019-03-05 2019-03-05 15:23:44 2021-02-17 20:24:57 DISCONTINUED
#> EOTSTT EOSDT EOSDY DCSREAS DTHDT DTHCAUS DTHCAT LDDTHELD
#> 1 COMPLETED 2021-02-23 731 <NA> <NA> <NA> <NA> NA
#> 2 COMPLETED 2021-02-25 731 <NA> <NA> <NA> <NA> NA
#> 3 COMPLETED 2021-02-27 731 <NA> <NA> <NA> <NA> NA
#> 4 COMPLETED 2021-03-01 731 <NA> <NA> <NA> <NA> NA
#> 5 COMPLETED 2021-03-01 731 <NA> <NA> <NA> <NA> NA
#> 6 DISCONTINUED 2021-02-17 716 LACK OF EFFICACY <NA> <NA> <NA> NA
#> LDDTHGR1 LSTALVDT DTHADY study_duration_secs
#> 1 <NA> 2021-03-05 NA 63113904
#> 2 <NA> 2021-03-15 NA 63113904
#> 3 <NA> 2021-03-15 NA 63113904
#> 4 <NA> 2021-03-17 NA 63113904
#> 5 <NA> 2021-03-25 NA 63113904
#> 6 <NA> 2021-03-01 NA 63113904
#>
#> ...
#> # A tibble: 6 × 44
#> STUDYID USUBJID SUBJID SITEID AGE AGEU SEX RACE ETHNIC COUNTRY DTHFL
#> <chr> <chr> <chr> <chr> <int> <fct> <fct> <fct> <fct> <fct> <fct>
#> 1 AB12345 AB12345-CH… id-11 CHN-9 28 YEARS F NATI… HISPA… CHN N
#> 2 AB12345 AB12345-CH… id-352 CHN-16 28 YEARS M ASIAN HISPA… CHN N
#> 3 AB12345 AB12345-CH… id-186 CHN-1 27 YEARS M ASIAN NOT H… CHN N
#> 4 AB12345 AB12345-CH… id-371 CHN-1 28 YEARS F ASIAN NOT H… CHN Y
#> 5 AB12345 AB12345-CH… id-233 CHN-1 36 YEARS F BLAC… NOT H… CHN N
#> 6 AB12345 AB12345-US… id-131 USA-12 44 YEARS F AMER… NOT H… USA N
#> # … with 33 more variables: INVID <chr>, INVNAM <chr>, ARM <fct>, ARMCD <fct>,
#> # ACTARM <fct>, ACTARMCD <fct>, TRT01P <fct>, TRT01A <fct>, REGION1 <fct>,
#> # STRATA1 <fct>, STRATA2 <fct>, BMRKR1 <dbl>, BMRKR2 <fct>, ITTFL <fct>,
#> # SAFFL <fct>, BMEASIFL <fct>, BEP01FL <fct>, RANDDT <date>, TRTSDTM <dttm>,
#> # TRTEDTM <dttm>, EOSSTT <fct>, EOTSTT <fct>, EOSDT <date>, EOSDY <int>,
#> # DCSREAS <fct>, DTHDT <date>, DTHCAUS <fct>, DTHCAT <fct>, LDDTHELD <int>,
#> # LDDTHGR1 <fct>, LSTALVDT <date>, DTHADY <int>, study_duration_secs <dbl>
get_dataset(x)$get_metadata()
#> $type
#> [1] "scda"
#>
#> $version
#> [1] "latest"
#>
x$get_raw_data()
#> # A tibble: 400 × 44
#> STUDYID USUBJID SUBJID SITEID AGE AGEU SEX RACE ETHNIC COUNTRY DTHFL
#> <chr> <chr> <chr> <chr> <int> <fct> <fct> <fct> <fct> <fct> <fct>
#> 1 AB12345 AB12345-C… id-128 CHN-3 32 YEARS M ASIAN NOT H… CHN N
#> 2 AB12345 AB12345-C… id-262 CHN-15 35 YEARS M BLAC… NOT H… CHN N
#> 3 AB12345 AB12345-R… id-378 RUS-3 30 YEARS F ASIAN NOT H… RUS N
#> 4 AB12345 AB12345-C… id-220 CHN-11 26 YEARS F ASIAN NOT H… CHN N
#> 5 AB12345 AB12345-C… id-267 CHN-7 40 YEARS M ASIAN UNKNO… CHN N
#> 6 AB12345 AB12345-C… id-201 CHN-15 49 YEARS M ASIAN NOT H… CHN N
#> 7 AB12345 AB12345-U… id-45 USA-1 34 YEARS F ASIAN NOT H… USA N
#> 8 AB12345 AB12345-U… id-261 USA-1 32 YEARS F ASIAN NOT H… USA N
#> 9 AB12345 AB12345-N… id-173 NGA-11 24 YEARS F BLAC… NOT H… NGA N
#> 10 AB12345 AB12345-C… id-307 CHN-1 24 YEARS M ASIAN NOT H… CHN N
#> # … with 390 more rows, and 33 more variables: INVID <chr>, INVNAM <chr>,
#> # ARM <fct>, ARMCD <fct>, ACTARM <fct>, ACTARMCD <fct>, TRT01P <fct>,
#> # TRT01A <fct>, REGION1 <fct>, STRATA1 <fct>, STRATA2 <fct>, BMRKR1 <dbl>,
#> # BMRKR2 <fct>, ITTFL <fct>, SAFFL <fct>, BMEASIFL <fct>, BEP01FL <fct>,
#> # RANDDT <date>, TRTSDTM <dttm>, TRTEDTM <dttm>, EOSSTT <fct>, EOTSTT <fct>,
#> # EOSDT <date>, EOSDY <int>, DCSREAS <fct>, DTHDT <date>, DTHCAUS <fct>,
#> # DTHCAT <fct>, LDDTHELD <int>, LDDTHGR1 <fct>, LSTALVDT <date>, …
metadata_fun <- callable_function(function(a) list(type = a))
metadata_fun$set_args(args = list(a = "scda"))
y <- scda_dataset_connector(
dataname = "ADSL", scda_dataname = "adsl",
metadata = metadata_fun
)
load_dataset(y)
get_dataset(y)$get_metadata()
#> $type
#> [1] "scda"
#>