R/get_data.R
In USGS-R/HASP: Hydrologic AnalySis Package
Defines functions
data_available
site_summary
get_state_data
get_aquifer_data
Documented in
data_available
get_aquifer_data
get_state_data
site_summary
#' get_aquifer_data
#'
#' Get USGS data based on aquiferCd
#'
#' @param aquiferCd character. To see valid aquifer codes, see the included data
#' frame \code{local_aqfr}.
#' @param startDate date or string. Beginning date of when to pull data.
#' @param endDate date of string Ending date to pull data.
#' @param parameter_cd 5-digit character USGS parameter code.
#' @export
#'
#' @examples
#' end_date <- "2021-01-01"
#' start_date <- "1989-12-31"
#'
#' aquiferCd <- "S100CSLLWD"
#' \donttest{
#' aq_data <- get_aquifer_data(aquiferCd, start_date, end_date)
#' }
get_aquifer_data <- function(aquiferCd, startDate, endDate,
parameter_cd = "72019"){
aquifer_data <- data.frame()
site_data <- data.frame()
states <- unlist(summary_aquifers$states[summary_aquifers$nat_aqfr_cd == aquiferCd])
for(state in states){
message("Getting data from: ", state)
state_data <- tryCatch(
expr = {
get_state_data(state = state,
aquiferCd = aquiferCd,
startDate = startDate,
endDate = endDate,
parameter_cd = parameter_cd)
},
error = function(e){
cat(state, "errored \n")
}
)
if(inherits(state_data, "error")) next
if(!all(is.na(state_data$site_no))){
state_data_sites <- dataRetrieval::readNWISsite(unique(state_data$site_no))
state_data_sites <- state_data_sites %>%
dplyr::select(station_nm, site_no, dec_lat_va, dec_long_va)
aquifer_data <- dplyr::bind_rows(aquifer_data, state_data)
site_data <- dplyr::bind_rows(site_data, state_data_sites)
}
}
attr(aquifer_data, "siteInfo") <- site_data
return(aquifer_data)
}
#' get_state_data
#'
#' Get USGS data based for a single state with specific aquifer codes.
#'
#' @param state character. Can be state abbreviation, long name, or numeric code.
#' @param aquiferCd character. To see valid aquifer codes, see the included data
#' frame \code{local_aqfr}.
#' @param startDate date or string. Beginning date of when to pull data.
#' @param endDate date of string Ending date to pull data.
#' @param parameter_cd 5-digit character USGS parameter code. Default is "72019".
#' @export
#'
#' @examples
#' end_date <- "2021-01-01"
#' start_date <- "1989-12-31"
#' aquiferCd <- "S100CSLLWD"
#'
#' \donttest{
#' st_data <- get_state_data("WI", aquiferCd,
#' start_date, end_date)
#' }
get_state_data <- function(state, aquiferCd,
startDate, endDate,
parameter_cd = "72019"){
levels <- dataRetrieval::readNWISdata(stateCd = state,
service = "gwlevels",
startDate= startDate,
endDate = endDate,
aquiferCd = aquiferCd,
format = "rdb,3.0")
levels_dv <- dataRetrieval::readNWISdata(stateCd = state,
service = "dv",
statCd = "00003",
startDate= startDate,
endDate = endDate,
aquiferCd = aquiferCd)
if(nrow(levels) + nrow(levels_dv) == 0){
return(data.frame())
}
if(nrow(levels) > 0){
state_data <- levels %>%
dplyr::filter(lev_age_cd == "A") %>%
dplyr::select(lev_dt, site_no, parameter_cd, lev_va, sl_lev_va) %>%
dplyr::mutate(value = dplyr::case_when(is.na(lev_va) ~ sl_lev_va,
TRUE ~ lev_va),
state_call = state,
year = as.integer(format(as.Date(lev_dt), "%Y")),
water_year = water_year(lev_dt),
lev_dt = as.Date(lev_dt)) %>%
dplyr::select(-lev_va, -sl_lev_va)
} else {
state_data <- data.frame()
}
if(nrow(levels_dv) > 0){
state_dv <- levels_dv %>%
dplyr::mutate(year = as.numeric(format(dateTime, "%Y")),
water_year = water_year(dateTime),
dateTime = as.character(as.Date(dateTime)),
state_call = state,
lev_dt = as.Date(dateTime))
cds <- which(!grepl("_cd", names(state_dv)) &
!names(state_dv) %in% c("agency_cd", "site_no", "water_year",
"dateTime", "tz_cd", "year",
"state_call", "lev_dt"))
names(state_dv)[cds] <- sprintf("%s_value", names(state_dv)[cds])
state_dv <- state_dv %>%
tidyr::pivot_longer(cols = c(-agency_cd, -site_no, -water_year,
-dateTime, -tz_cd, -year,
-state_call, -lev_dt),
names_to = c("pcode", ".value"),
names_pattern = "(.+)_(.+)") %>%
dplyr::mutate(pcode = gsub("X_", "", pcode),
pcode = substr(pcode, 1, 5)) %>%
dplyr::rename(lev_status_cd = cd,
parameter_cd = pcode) %>%
dplyr::filter(lev_status_cd == "A") %>%
dplyr::select(-dateTime, -tz_cd, -agency_cd, -lev_status_cd)
} else {
state_dv = data.frame()
}
state_data_tots <- dplyr::bind_rows(state_data,
state_dv)
return(state_data_tots)
}
#' site_summary
#'
#' Get station summary information
#'
#' @param siteID character
#' @param markdown logical. Use markdown formating or console-friendly.
#' @export
#'
#' @examples
#' siteID <- "263819081585801"
#' site_metadata <- site_summary(siteID)
site_summary <- function(siteID, markdown = FALSE){
site_info <- dataRetrieval::readNWISsite(siteID)
if(!any(grepl("GW", site_info$site_tp_cd))){
warning("Site is not identified as a groundwater site")
return(site_info)
}
end_of_line <- ifelse(markdown, "<br/>", "\n\n")
nat_aqfrs <- nat_aqfr_state %>%
dplyr::select(dplyr::all_of(c("nat_aqfr_cd", "long_name"))) %>%
dplyr::distinct()
names(nat_aqfrs)[names(nat_aqfrs) == "long_name"] <- "nat_aq"
site_info_cleaned <- site_info %>%
dplyr::select(dplyr::all_of(c("site_no", "station_nm", "lat_va", "long_va",
"site_tp_cd", "state_cd", "county_cd", "huc_cd",
"nat_aqfr_cd", "aqfr_cd", "land_net_ds", "well_depth_va",
"alt_va", "alt_datum_cd"))) %>%
dplyr::left_join(nat_aqfrs, by = "nat_aqfr_cd") %>%
dplyr::left_join(dplyr::rename(local_aqfr,
local_aq = Aqfr_Name_prpr), by = "aqfr_cd") %>%
dplyr::mutate(state = dataRetrieval::stateCdLookup(state_cd,
outputType = "fullName"),
county = dataRetrieval::countyCdLookup(state = state_cd,
county = county_cd,
outputType = "fullName"),
lat_deg = substr(lat_va, start = 1, stop = 2),
lat_min = substr(lat_va, start = 3, stop = 4),
lat_sec = substr(lat_va, start = 5, stop = 6),
long_deg = substr(long_va, start = 1, stop = 2),
long_min = substr(long_va, start = 3, stop = 4),
long_sec = substr(long_va, start = 5, stop = 6))
cat(site_info_cleaned$site_no, site_info_cleaned$station_nm, end_of_line)
cat("Latitude: ", site_info_cleaned$lat_deg, "deg",
site_info_cleaned$lat_min, "'",
site_info_cleaned$lat_sec, '"', end_of_line)
cat("Longitude: ", site_info_cleaned$long_deg, "deg",
site_info_cleaned$long_min, "'",
site_info_cleaned$long_sec, '"', end_of_line)
cat(site_info_cleaned$county, ",", site_info_cleaned$state, end_of_line)
cat("Hydrologic Unit: ", site_info_cleaned$huc_cd, end_of_line)
cat("Well depth: ", site_info_cleaned$well_depth_va, " feet",end_of_line)
cat("Land surface altitude: ", site_info_cleaned$alt_va, " feet above", site_info_cleaned$alt_datum_cd , end_of_line)
cat('Well completed in : "', site_info_cleaned$nat_aq,'" (',
site_info_cleaned$nat_aqfr_cd, ") national aquifer.", end_of_line, sep = "")
cat('Well completed in : "', site_info_cleaned$local_aq,'" (',
site_info_cleaned$aqfr_cd, ") local aquifer.",end_of_line, sep = "")
return(site_info_cleaned)
}
#' site_summary
#'
#' Get station summary information
#'
#' @param siteID character. USGS site ID for a groundwater site.
#' @export
#'
#' @examples
#' siteID <- "263819081585801"
#' site_data_available <- data_available(siteID)
data_available <- function(siteID){
data_info <- dataRetrieval::whatNWISdata(siteNumber = siteID)
data_info_clean <- data_info %>%
dplyr::group_by(data_type_cd) %>%
dplyr::summarise(begin = min(begin_date, na.rm = TRUE),
end = max(end_date, na.rm = TRUE),
count = max(count_nu, na.rm = TRUE)) %>%
dplyr::ungroup() %>%
dplyr::mutate(`Data Type` = "")
if("uv" %in% data_info_clean$data_type_cd){
uv_codes <- data_info %>%
dplyr::filter(data_type_cd == "uv") %>%
dplyr::group_by(parm_cd) %>%
dplyr::summarise(begin = min(begin_date, na.rm = TRUE),
end = max(end_date, na.rm = TRUE),
count = max(count_nu, na.rm = TRUE))
#TODO: add something similar to dv
data_info_clean$count[data_info_clean$data_type_cd == "uv"] <- NA
data_info_clean$`Data Type`[data_info_clean$data_type_cd == "uv"] <- paste0('<a href="https://nwis.waterdata.usgs.gov/nwis/uv?site_no=', siteID, '">Current / Historical Observations</a>')
}
if("gw" %in% data_info_clean$data_type_cd){
data_info_clean$`Data Type`[data_info_clean$data_type_cd == "gw"] <- paste0('<a href="https://nwis.waterdata.usgs.gov/nwis/gwlevels?site_no=', siteID, '">Field groundwater-level measurements</a>')
}
if("ad" %in% data_info_clean$data_type_cd){
data_info_clean$`Data Type`[data_info_clean$data_type_cd == "ad"] <- paste0('<a href="https://nwis.waterdata.usgs.gov/nwis/wys_rpt?site_no=', siteID, '">Water-Year Summary</a>')
}
if("qw" %in% data_info_clean$data_type_cd){
data_info_clean$`Data Type`[data_info_clean$data_type_cd == "qw"] <- paste0('<a href="https://nwis.waterdata.usgs.gov/nwis/qwdata?site_no=', siteID, '">Field/Lab water-quality samples</a>')
}
if("dv" %in% data_info_clean$data_type_cd){
dv_codes <- data_info %>%
dplyr::filter(data_type_cd == "dv") %>%
dplyr::group_by(parm_cd) %>%
dplyr::summarise(begin = min(begin_date, na.rm = TRUE),
end = max(end_date, na.rm = TRUE),
count = max(count_nu, na.rm = TRUE)) %>%
dplyr::ungroup() %>%
dplyr::mutate(`Data Type` = dataRetrieval::readNWISpCode(parm_cd)[["parameter_nm"]]) %>%
dplyr::select(-parm_cd)
data_info_clean$`Data Type`[data_info_clean$data_type_cd == "dv"] <- paste0('<a href="https://nwis.waterdata.usgs.gov/nwis/dv?site_no=', siteID, '">Daily Data</a>')
data_info_clean$begin[data_info_clean$data_type_cd == "dv"] <- NA
data_info_clean$end[data_info_clean$data_type_cd == "dv"] <- NA
data_info_clean$count[data_info_clean$data_type_cd == "dv"] <- NA
rows_to_dv <- which(data_info_clean$data_type_cd == "dv")
if(length(rows_to_dv) > 0){
insert_row <- rows_to_dv + 1
if(rows_to_dv == 1){
data_info_clean_new <- data_info_clean[1,] %>%
dplyr::bind_rows(dv_codes) %>%
dplyr::bind_rows(data_info_clean[(rows_to_dv + nrow(dv_codes)):nrow(data_info_clean),])
} else {
data_info_clean_new <- data_info_clean[1:rows_to_dv,] %>%
dplyr::bind_rows(dv_codes) %>%
dplyr::bind_rows(data_info_clean[(rows_to_dv + nrow(dv_codes)):nrow(data_info_clean),])
data_info_clean <- data_info_clean_new
}
}
}
data_info_clean <- data_info_clean %>%
dplyr::select(`Data Type`,
`Begin Date` = begin,
`End Date` = end,
Count = count)
return(data_info_clean)
}
USGS-R/HASP documentation built on July 28, 2024, 7:53 a.m.
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Defines functions data_available site_summary get_state_data get_aquifer_data
Documented in data_available get_aquifer_data get_state_data site_summary
#' get_aquifer_data
#'
#' Get USGS data based on aquiferCd
#'
#' @param aquiferCd character. To see valid aquifer codes, see the included data
#' frame \code{local_aqfr}.
#' @param startDate date or string. Beginning date of when to pull data.
#' @param endDate date of string Ending date to pull data.
#' @param parameter_cd 5-digit character USGS parameter code.
#' @export
#'
#' @examples
#' end_date <- "2021-01-01"
#' start_date <- "1989-12-31"
#'
#' aquiferCd <- "S100CSLLWD"
#' \donttest{
#' aq_data <- get_aquifer_data(aquiferCd, start_date, end_date)
#' }
get_aquifer_data <- function(aquiferCd, startDate, endDate,
parameter_cd = "72019"){
aquifer_data <- data.frame()
site_data <- data.frame()
states <- unlist(summary_aquifers$states[summary_aquifers$nat_aqfr_cd == aquiferCd])
for(state in states){
message("Getting data from: ", state)
state_data <- tryCatch(
expr = {
get_state_data(state = state,
aquiferCd = aquiferCd,
startDate = startDate,
endDate = endDate,
parameter_cd = parameter_cd)
},
error = function(e){
cat(state, "errored \n")
}
)
if(inherits(state_data, "error")) next
if(!all(is.na(state_data$site_no))){
state_data_sites <- dataRetrieval::readNWISsite(unique(state_data$site_no))
state_data_sites <- state_data_sites %>%
dplyr::select(station_nm, site_no, dec_lat_va, dec_long_va)
aquifer_data <- dplyr::bind_rows(aquifer_data, state_data)
site_data <- dplyr::bind_rows(site_data, state_data_sites)
}
}
attr(aquifer_data, "siteInfo") <- site_data
return(aquifer_data)
}
#' get_state_data
#'
#' Get USGS data based for a single state with specific aquifer codes.
#'
#' @param state character. Can be state abbreviation, long name, or numeric code.
#' @param aquiferCd character. To see valid aquifer codes, see the included data
#' frame \code{local_aqfr}.
#' @param startDate date or string. Beginning date of when to pull data.
#' @param endDate date of string Ending date to pull data.
#' @param parameter_cd 5-digit character USGS parameter code. Default is "72019".
#' @export
#'
#' @examples
#' end_date <- "2021-01-01"
#' start_date <- "1989-12-31"
#' aquiferCd <- "S100CSLLWD"
#'
#' \donttest{
#' st_data <- get_state_data("WI", aquiferCd,
#' start_date, end_date)
#' }
get_state_data <- function(state, aquiferCd,
startDate, endDate,
parameter_cd = "72019"){
levels <- dataRetrieval::readNWISdata(stateCd = state,
service = "gwlevels",
startDate= startDate,
endDate = endDate,
aquiferCd = aquiferCd,
format = "rdb,3.0")
levels_dv <- dataRetrieval::readNWISdata(stateCd = state,
service = "dv",
statCd = "00003",
startDate= startDate,
endDate = endDate,
aquiferCd = aquiferCd)
if(nrow(levels) + nrow(levels_dv) == 0){
return(data.frame())
}
if(nrow(levels) > 0){
state_data <- levels %>%
dplyr::filter(lev_age_cd == "A") %>%
dplyr::select(lev_dt, site_no, parameter_cd, lev_va, sl_lev_va) %>%
dplyr::mutate(value = dplyr::case_when(is.na(lev_va) ~ sl_lev_va,
TRUE ~ lev_va),
state_call = state,
year = as.integer(format(as.Date(lev_dt), "%Y")),
water_year = water_year(lev_dt),
lev_dt = as.Date(lev_dt)) %>%
dplyr::select(-lev_va, -sl_lev_va)
} else {
state_data <- data.frame()
}
if(nrow(levels_dv) > 0){
state_dv <- levels_dv %>%
dplyr::mutate(year = as.numeric(format(dateTime, "%Y")),
water_year = water_year(dateTime),
dateTime = as.character(as.Date(dateTime)),
state_call = state,
lev_dt = as.Date(dateTime))
cds <- which(!grepl("_cd", names(state_dv)) &
!names(state_dv) %in% c("agency_cd", "site_no", "water_year",
"dateTime", "tz_cd", "year",
"state_call", "lev_dt"))
names(state_dv)[cds] <- sprintf("%s_value", names(state_dv)[cds])
state_dv <- state_dv %>%
tidyr::pivot_longer(cols = c(-agency_cd, -site_no, -water_year,
-dateTime, -tz_cd, -year,
-state_call, -lev_dt),
names_to = c("pcode", ".value"),
names_pattern = "(.+)_(.+)") %>%
dplyr::mutate(pcode = gsub("X_", "", pcode),
pcode = substr(pcode, 1, 5)) %>%
dplyr::rename(lev_status_cd = cd,
parameter_cd = pcode) %>%
dplyr::filter(lev_status_cd == "A") %>%
dplyr::select(-dateTime, -tz_cd, -agency_cd, -lev_status_cd)
} else {
state_dv = data.frame()
}
state_data_tots <- dplyr::bind_rows(state_data,
state_dv)
return(state_data_tots)
}
#' site_summary
#'
#' Get station summary information
#'
#' @param siteID character
#' @param markdown logical. Use markdown formating or console-friendly.
#' @export
#'
#' @examples
#' siteID <- "263819081585801"
#' site_metadata <- site_summary(siteID)
site_summary <- function(siteID, markdown = FALSE){
site_info <- dataRetrieval::readNWISsite(siteID)
if(!any(grepl("GW", site_info$site_tp_cd))){
warning("Site is not identified as a groundwater site")
return(site_info)
}
end_of_line <- ifelse(markdown, "<br/>", "\n\n")
nat_aqfrs <- nat_aqfr_state %>%
dplyr::select(dplyr::all_of(c("nat_aqfr_cd", "long_name"))) %>%
dplyr::distinct()
names(nat_aqfrs)[names(nat_aqfrs) == "long_name"] <- "nat_aq"
site_info_cleaned <- site_info %>%
dplyr::select(dplyr::all_of(c("site_no", "station_nm", "lat_va", "long_va",
"site_tp_cd", "state_cd", "county_cd", "huc_cd",
"nat_aqfr_cd", "aqfr_cd", "land_net_ds", "well_depth_va",
"alt_va", "alt_datum_cd"))) %>%
dplyr::left_join(nat_aqfrs, by = "nat_aqfr_cd") %>%
dplyr::left_join(dplyr::rename(local_aqfr,
local_aq = Aqfr_Name_prpr), by = "aqfr_cd") %>%
dplyr::mutate(state = dataRetrieval::stateCdLookup(state_cd,
outputType = "fullName"),
county = dataRetrieval::countyCdLookup(state = state_cd,
county = county_cd,
outputType = "fullName"),
lat_deg = substr(lat_va, start = 1, stop = 2),
lat_min = substr(lat_va, start = 3, stop = 4),
lat_sec = substr(lat_va, start = 5, stop = 6),
long_deg = substr(long_va, start = 1, stop = 2),
long_min = substr(long_va, start = 3, stop = 4),
long_sec = substr(long_va, start = 5, stop = 6))
cat(site_info_cleaned$site_no, site_info_cleaned$station_nm, end_of_line)
cat("Latitude: ", site_info_cleaned$lat_deg, "deg",
site_info_cleaned$lat_min, "'",
site_info_cleaned$lat_sec, '"', end_of_line)
cat("Longitude: ", site_info_cleaned$long_deg, "deg",
site_info_cleaned$long_min, "'",
site_info_cleaned$long_sec, '"', end_of_line)
cat(site_info_cleaned$county, ",", site_info_cleaned$state, end_of_line)
cat("Hydrologic Unit: ", site_info_cleaned$huc_cd, end_of_line)
cat("Well depth: ", site_info_cleaned$well_depth_va, " feet",end_of_line)
cat("Land surface altitude: ", site_info_cleaned$alt_va, " feet above", site_info_cleaned$alt_datum_cd , end_of_line)
cat('Well completed in : "', site_info_cleaned$nat_aq,'" (',
site_info_cleaned$nat_aqfr_cd, ") national aquifer.", end_of_line, sep = "")
cat('Well completed in : "', site_info_cleaned$local_aq,'" (',
site_info_cleaned$aqfr_cd, ") local aquifer.",end_of_line, sep = "")
return(site_info_cleaned)
}
#' site_summary
#'
#' Get station summary information
#'
#' @param siteID character. USGS site ID for a groundwater site.
#' @export
#'
#' @examples
#' siteID <- "263819081585801"
#' site_data_available <- data_available(siteID)
data_available <- function(siteID){
data_info <- dataRetrieval::whatNWISdata(siteNumber = siteID)
data_info_clean <- data_info %>%
dplyr::group_by(data_type_cd) %>%
dplyr::summarise(begin = min(begin_date, na.rm = TRUE),
end = max(end_date, na.rm = TRUE),
count = max(count_nu, na.rm = TRUE)) %>%
dplyr::ungroup() %>%
dplyr::mutate(`Data Type` = "")
if("uv" %in% data_info_clean$data_type_cd){
uv_codes <- data_info %>%
dplyr::filter(data_type_cd == "uv") %>%
dplyr::group_by(parm_cd) %>%
dplyr::summarise(begin = min(begin_date, na.rm = TRUE),
end = max(end_date, na.rm = TRUE),
count = max(count_nu, na.rm = TRUE))
#TODO: add something similar to dv
data_info_clean$count[data_info_clean$data_type_cd == "uv"] <- NA
data_info_clean$`Data Type`[data_info_clean$data_type_cd == "uv"] <- paste0('<a href="https://nwis.waterdata.usgs.gov/nwis/uv?site_no=', siteID, '">Current / Historical Observations</a>')
}
if("gw" %in% data_info_clean$data_type_cd){
data_info_clean$`Data Type`[data_info_clean$data_type_cd == "gw"] <- paste0('<a href="https://nwis.waterdata.usgs.gov/nwis/gwlevels?site_no=', siteID, '">Field groundwater-level measurements</a>')
}
if("ad" %in% data_info_clean$data_type_cd){
data_info_clean$`Data Type`[data_info_clean$data_type_cd == "ad"] <- paste0('<a href="https://nwis.waterdata.usgs.gov/nwis/wys_rpt?site_no=', siteID, '">Water-Year Summary</a>')
}
if("qw" %in% data_info_clean$data_type_cd){
data_info_clean$`Data Type`[data_info_clean$data_type_cd == "qw"] <- paste0('<a href="https://nwis.waterdata.usgs.gov/nwis/qwdata?site_no=', siteID, '">Field/Lab water-quality samples</a>')
}
if("dv" %in% data_info_clean$data_type_cd){
dv_codes <- data_info %>%
dplyr::filter(data_type_cd == "dv") %>%
dplyr::group_by(parm_cd) %>%
dplyr::summarise(begin = min(begin_date, na.rm = TRUE),
end = max(end_date, na.rm = TRUE),
count = max(count_nu, na.rm = TRUE)) %>%
dplyr::ungroup() %>%
dplyr::mutate(`Data Type` = dataRetrieval::readNWISpCode(parm_cd)[["parameter_nm"]]) %>%
dplyr::select(-parm_cd)
data_info_clean$`Data Type`[data_info_clean$data_type_cd == "dv"] <- paste0('<a href="https://nwis.waterdata.usgs.gov/nwis/dv?site_no=', siteID, '">Daily Data</a>')
data_info_clean$begin[data_info_clean$data_type_cd == "dv"] <- NA
data_info_clean$end[data_info_clean$data_type_cd == "dv"] <- NA
data_info_clean$count[data_info_clean$data_type_cd == "dv"] <- NA
rows_to_dv <- which(data_info_clean$data_type_cd == "dv")
if(length(rows_to_dv) > 0){
insert_row <- rows_to_dv + 1
if(rows_to_dv == 1){
data_info_clean_new <- data_info_clean[1,] %>%
dplyr::bind_rows(dv_codes) %>%
dplyr::bind_rows(data_info_clean[(rows_to_dv + nrow(dv_codes)):nrow(data_info_clean),])
} else {
data_info_clean_new <- data_info_clean[1:rows_to_dv,] %>%
dplyr::bind_rows(dv_codes) %>%
dplyr::bind_rows(data_info_clean[(rows_to_dv + nrow(dv_codes)):nrow(data_info_clean),])
data_info_clean <- data_info_clean_new
}
}
}
data_info_clean <- data_info_clean %>%
dplyr::select(`Data Type`,
`Begin Date` = begin,
`End Date` = end,
Count = count)
return(data_info_clean)
}
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