library(tidyverse)
library(stringr)
library(devtools)
path_to_file <- file.path('data-raw', 'raw_ctgov')
ct_files <- list.files(path_to_file)
imported_ct <- purrr::map(file.path(path_to_file, ct_files),
~ readr::read_delim(.,
delim = '|',
quote = '\"',
na = c("", "NA", "N/A")
)
)
imported_ct <- purrr:::map(imported_ct, ~ {
names(.) <- tolower(names(.))
.
})
names(imported_ct) <- ct_files
summaries_ct <- dplyr::full_join(
imported_ct$brief_summaries.txt,
imported_ct$detailed_descriptions.txt,
by = c("id" = "id", "nct_id" = "nct_id")
) %>%
dplyr::select(-id) %>%
full_join(
imported_ct$studies.txt %>%
select(nct_id, first_received_date, brief_title, official_title),
by = c('nct_id' = 'nct_id')
) %>%
full_join(
imported_ct$central_contacts.txt %>%
select(nct_id, contact_type, name),
by = c('nct_id' = 'nct_id')
) %>%
transmute(
final = NA_integer_,
id = nct_id,
title = str_c(brief_title, official_title),
year = str_extract(first_received_date, '[0-9]{4}') %>% as.integer,
authors = str_c(name, ' (', contact_type, ')'),
abstract = str_c(
str_replace_na(description.x, replacement = ' '),
str_replace_na(description.y, replacement = ' ')
)
)
devtools::use_data(summaries_ct, overwrite = TRUE, compress = 'xz')
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