inst/project_initiate/manipulation/fetch.R

In hebrewseniorlife/coretools: Bootstrap Some Common Tasks to Initial R Projects

source("manipulation/global.R")

# Read in data
auth <- read_csv("manipulation/auth")
db <- as_data_frame(redcap_read_oneshot(redcap_uri = auth$uri,
                                        token = auth$token)$data)
db_version <- as.character(Sys.time())

# In the next few steps, you should split data into smaller pieces

## When the redcap project is large, you may want to read in only one
## piece of the database.

baseline <- db %>%
  # set up a filter to only select rows with baseline data
  filter(redcap_event_name %in% c("phone", "visit 1")) %>%
  # Select variables that matters
  select(studyid, redcap_event_name, something, something2, anotherthing)

test <- db %>%
  # select relavent rows and columns
  filter(redcap_event_name %in% c("visit 1", "visit 2", "visit 3")) %>%
  select(studyid, redcap_event_name, test1_1:test1_5, test2, test3) %>%
  # Perform some calculations
  mutate(test1 = sum(test1_1, test1_2, test1_3, test1_4, test1_5,
                     na.rm = T)) %>%
  # downsize the data
  select(studyid, redcap_event_name, test1, test2, test3)

# If if requires some complicated manipulation, you can put analytical
# code in a separate file and source it here. For example
source("manipulation/baseline.R")

# After everything, you have the option to export a cleaned version of
# the data to somewhere. In many cases, you don't need to
# write(baseline, "data/baseline.csv")
# write(baseline, "data/tests.csv")