Closed jayhesselberth closed 7 years ago
I am wondering if there could be a link between the clinical trials table the projects table by the application ID (rather than just the project num).
library(nihexporter) #> Loading required package: jsonlite #> Loading required package: httr #> Loading required package: dplyr #> #> Attaching package: 'dplyr' #> The following objects are masked from 'package:stats': #> #> filter, lag #> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union library(tidyverse) #> Loading tidyverse: ggplot2 #> Loading tidyverse: tibble #> Loading tidyverse: tidyr #> Loading tidyverse: readr #> Loading tidyverse: purrr #> Conflicts with tidy packages ---------------------------------------------- #> filter(): dplyr, stats #> lag(): dplyr, stats # this produces several NA values for application.id left_join(clinical_studies, projects) %>% select(application.id, one_of(names(clinical_studies))) #> Joining, by = "project.num" #> # A tibble: 248,786 × 4 #> application.id project.num trial.id #> <int> <chr> <chr> #> 1 NA 261201100031C-0-0-1 NCT01831778 #> 2 NA 261201200042I-0-26100006-1 NCT02772003 #> 3 NA 261201400046C-0-0-1 NCT02464332 #> 4 NA 268200700015C-2-0-0 NCT00534495 #> 5 NA 268200700036C-5-0-1 NCT00556439 #> 6 NA 268200900040C-1-0-1 NCT01206062 #> 7 NA 268201000048C-5-0-1 NCT01322165 #> 8 NA 268201300046C-4-0-1 NCT00005485 #> 9 NA 268201300047C-4-0-1 NCT00005485 #> 10 NA 268201300048C-4-0-1 NCT00005485 #> # ... with 248,776 more rows, and 1 more variables: study.status <fctr>
Thanks for the quick response and solution.