data-raw/survey_template.R

In gilesjohnr/hmob: Tools for analyzing human mobility data

survey.template <- data.frame(
     date_start=as.Date(character()),
     date_stop=as.Date(character()),
     date_span=as.difftime(numeric(), units='days'),
     indiv_id=integer(),      # unique individual identifier
     indiv_age=numeric(),     # Age of participant
     indiv_sex=logical(),     # Gender of perticipant
     indiv_type=character(),     # If individual participants belong to different groups
     orig_adm0=character(),   # Name of highest administration level of origin location (country)
     orig_adm1=character(),   # Name of administration level 1 of origin location
     orig_adm2=character(),   # Name of administration level 2 of origin location
     orig_adm3=character(),   # Name of administration level 3 of origin location
     orig_adm4=character(),   # Name of administration level 4 of origin location
     orig_adm5=character(),   # Name of administration level 5 of origin location
     orig_type=character(),   # What is the administrative type for the origin location? (e.g. sub-district, community vs town, or urban vs rural)
     orig_x=numeric(),        # Longitude of origin location in decimal degrees
     orig_y=numeric(),        # Latitude of origin location in decimal degrees
     orig_pop=numeric(),      # Population size of lowest administrative unit
     dest_adm0=character(),   # Name of highest administration level of destination location (country)
     dest_adm1=character(),   # Name of administration level 1 of destination location
     dest_adm2=character(),   # Name of administration level 2 of destination location
     dest_adm3=character(),   # Name of administration level 3 of destination location
     dest_adm4=character(),   # Name of administration level 4 of destination location
     dest_adm5=character(),   # Name of administration level 5 of destination location
     dest_type=character(),   # If origin and destination locations have different types (e.g. community vs town, or urban vs rural)
     dest_x=numeric(),        # Longitude of origin location in decimal degrees
     dest_y=numeric(),        # Latitude of origin location in decimal degrees
     dest_pop=numeric(),      # Population size of lowest administrative unit
     trips=numeric(),          # Total number of trips individual made from origin to destination during time span of travel survey
stringsAsFactors=FALSE)

save(survey.template, file='data/survey.template.rda')