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Load data from connection

load_dataset.Rd

[Stable] Load data from connection. Function used on TealDatasetConnector and TealDataset to obtain data from connection.

Usage 

load_dataset(x, ...)

# S3 method for TealDataset
load_dataset(x, ...)

# S3 method for TealDatasetConnector
load_dataset(x, args = NULL, try = FALSE, conn = NULL, ...)

Arguments

x

(TealDatasetConnector or TealDataset)

...

not used, only for support of S3

args

(NULL or named list)
additional dynamic arguments passed to function which loads the data.

try

(logical) whether perform function evaluation inside try clause

conn

Optional (TealDataConnection) object required to pull the data.

Value

x with loaded dataset object

Examples 


# TealDataset --------
library(scda)
ADSL <- synthetic_cdisc_data("latest")$adsl
ADSL_dataset <- dataset("ADSL", x = ADSL)

load_dataset(ADSL_dataset)

# TealDatasetConnector --------
library(scda)
pull_fun_adsl <- callable_function(
  function() {
    synthetic_cdisc_data("latest")$adsl
  }
)
adsl <- dataset_connector("ADSL", pull_fun_adsl)
load_dataset(adsl)
get_dataset(adsl)
#> A TealDataset object containing the following data.frame (400 rows and 56 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     HISPANIC OR LATINO     CHN     Y  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 NOT HISPANIC OR LATINO     CHN     N  INV ID CHN-7
#> 6                     ASIAN NOT HISPANIC OR LATINO     CHN     Y 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         TRT02P         TRT02A REGION1 STRATA1 STRATA2
#> 1      A: Drug X     B: Placebo      A: Drug X    Asia       C      S2
#> 2 C: Combination     B: Placebo C: Combination    Asia       C      S1
#> 3 C: Combination      A: Drug X     B: Placebo Eurasia       A      S1
#> 4     B: Placebo     B: Placebo     B: Placebo    Asia       B      S2
#> 5     B: Placebo C: Combination      A: Drug X    Asia       C      S1
#> 6 C: Combination     B: Placebo C: Combination    Asia       C      S2
#>      BMRKR1 BMRKR2 ITTFL SAFFL BMEASIFL BEP01FL AEWITHFL     RANDDT
#> 1 14.424934 MEDIUM     Y     Y        Y       Y        N 2019-02-22
#> 2  4.055463    LOW     Y     Y        N       N        Y 2019-02-26
#> 3  2.803240   HIGH     Y     Y        Y       N        N 2019-02-24
#> 4 10.262734 MEDIUM     Y     Y        Y       Y        N 2019-02-27
#> 5  6.206763    LOW     Y     Y        N       N        N 2019-03-01
#> 6  6.906799 MEDIUM     Y     Y        Y       N        N 2019-03-05
#>               TRTSDTM             TRTEDTM           TRT01SDTM
#> 1 2019-02-24 11:09:18 2022-02-12 03:55:58 2019-02-24 11:09:18
#> 2 2019-02-26 09:05:00 2022-02-26 02:32:36 2019-02-26 09:05:00
#> 3 2019-02-28 03:19:08 2022-02-27 20:46:44 2019-02-28 03:19:08
#> 4 2019-03-01 13:33:03 2022-03-01 07:00:39 2019-03-01 13:33:03
#> 5 2019-03-02 00:09:16 2022-03-01 17:36:52 2019-03-02 00:09:16
#> 6 2019-03-05 15:23:44 2022-02-19 03:34:25 2019-03-05 15:23:44
#>             TRT01EDTM           TRT02SDTM           TRT02EDTM
#> 1 2021-02-11 22:06:46 2021-02-11 22:06:46 2022-02-12 03:55:58
#> 2 2021-02-25 20:43:24 2021-02-25 20:43:24 2022-02-26 02:32:36
#> 3 2021-02-27 14:57:32 2021-02-27 14:57:32 2022-02-27 20:46:44
#> 4 2021-03-01 01:11:27 2021-03-01 01:11:27 2022-03-01 07:00:39
#> 5 2021-03-01 11:47:40 2021-03-01 11:47:40 2022-03-01 17:36:52
#> 6 2021-02-18 21:45:13 2021-02-18 21:45:13 2022-02-19 03:34:25
#>              AP01SDTM            AP01EDTM            AP02SDTM
#> 1 2019-02-24 11:09:18 2021-02-11 22:06:46 2021-02-11 22:06:46
#> 2 2019-02-26 09:05:00 2021-02-25 20:43:24 2021-02-25 20:43:24
#> 3 2019-02-28 03:19:08 2021-02-27 14:57:32 2021-02-27 14:57:32
#> 4 2019-03-01 13:33:03 2021-03-01 01:11:27 2021-03-01 01:11:27
#> 5 2019-03-02 00:09:16 2021-03-01 11:47:40 2021-03-01 11:47:40
#> 6 2019-03-05 15:23:44 2021-02-18 21:45:13 2021-02-18 21:45:13
#>              AP02EDTM       EOSSTT       EOTSTT      EOSDT EOSDY DCSREAS
#> 1 2022-02-12 03:55:58 DISCONTINUED DISCONTINUED 2022-02-12  1084   DEATH
#> 2 2022-02-26 02:32:36    COMPLETED    COMPLETED 2022-02-26  1096    <NA>
#> 3 2022-02-27 20:46:44    COMPLETED    COMPLETED 2022-02-27  1096    <NA>
#> 4 2022-03-01 07:00:39    COMPLETED    COMPLETED 2022-03-01  1096    <NA>
#> 5 2022-03-01 17:36:52    COMPLETED    COMPLETED 2022-03-01  1096    <NA>
#> 6 2022-02-19 03:34:25 DISCONTINUED DISCONTINUED 2022-02-19  1082   DEATH
#>        DTHDT       DTHCAUS        DTHCAT LDDTHELD LDDTHGR1   LSTALVDT DTHADY
#> 1 2022-03-06 ADVERSE EVENT ADVERSE EVENT       22     <=30 2022-03-06   1106
#> 2       <NA>          <NA>          <NA>       NA     <NA> 2022-03-17     NA
#> 3       <NA>          <NA>          <NA>       NA     <NA> 2022-03-11     NA
#> 4       <NA>          <NA>          <NA>       NA     <NA> 2022-03-26     NA
#> 5       <NA>          <NA>          <NA>       NA     <NA> 2022-03-15     NA
#> 6 2022-02-22 ADVERSE EVENT ADVERSE EVENT        3     <=30 2022-02-22   1085
#>   ADTHAUT study_duration_secs
#> 1     Yes            63113904
#> 2    <NA>            63113904
#> 3    <NA>            63113904
#> 4    <NA>            63113904
#> 5    <NA>            63113904
#> 6     Yes            63113904
#> 
#> ...
#> # A tibble: 6 × 56
#>   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     Y    
#> 2 AB12345 AB12345-CH… id-352 CHN-16    28 YEARS M     ASIAN UNKNO… 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     N    
#> 5 AB12345 AB12345-CH… id-233 CHN-1     36 YEARS F     BLAC… NOT H… CHN     Y    
#> 6 AB12345 AB12345-US… id-131 USA-12    44 YEARS F     AMER… NOT H… USA     N    
#> # … with 45 more variables: INVID <chr>, INVNAM <chr>, ARM <fct>, ARMCD <fct>,
#> #   ACTARM <fct>, ACTARMCD <fct>, TRT01P <fct>, TRT01A <fct>, TRT02P <fct>,
#> #   TRT02A <fct>, REGION1 <fct>, STRATA1 <fct>, STRATA2 <fct>, BMRKR1 <dbl>,
#> #   BMRKR2 <fct>, ITTFL <fct>, SAFFL <fct>, BMEASIFL <fct>, BEP01FL <fct>,
#> #   AEWITHFL <fct>, RANDDT <date>, TRTSDTM <dttm>, TRTEDTM <dttm>,
#> #   TRT01SDTM <dttm>, TRT01EDTM <dttm>, TRT02SDTM <dttm>, TRT02EDTM <dttm>,
#> #   AP01SDTM <dttm>, AP01EDTM <dttm>, AP02SDTM <dttm>, AP02EDTM <dttm>, …

pull_fun_adae <- callable_function(
  function() {
    synthetic_cdisc_data("latest")$adae
  }
)
adae <- dataset_connector("ADAE", pull_fun_adae)
load_dataset(adae)