boB Rudis
4 anni fa
20 ha cambiato i file con 683 aggiunte e 33 eliminazioni
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#' Retrieve U.S. Clinical Laboratories Reporting SARS-CoV-2 Test Results to CDC |
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#' |
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#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/reporting-cov2-results.html> |
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#' @return data frame |
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#' @export |
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clinical_labs <- function() { |
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pg <- xml2::read_html("https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/reporting-cov2-results.html") |
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clab_tbl <- rvest::html_table(pg, header = TRUE, trim = TRUE)[[1]] |
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colnames(clab_tbl) <- c("week", "num_labs", "tested", "tested_pos", "pct_pos") |
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clab_tbl$region <- "National" |
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clab_tbl$source <- "Clinical Labs" |
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clab_tbl$week <- clean_int(clab_tbl$week) |
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clab_tbl$num_labs <- clean_int(clab_tbl$num_labs) |
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clab_tbl$tested <- clean_int(clab_tbl$tested) |
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clab_tbl$tested_pos <- clean_int(clab_tbl$tested_pos) |
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clab_tbl$pct_pos <- clean_num(clab_tbl$pct_pos)/100 |
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as_tibble(clab_tbl[!is.na(clab_tbl$week),]) |
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} |
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#' Retrieve NCHS Mortality Surveillance Data |
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#' |
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#' @return data frame |
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#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nchs-data.html> |
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#' @export |
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mortality_surveillance_data <- function() { |
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pg <- xml2::read_html("https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nchs-data.html") |
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nat_tbl <- rvest::html_nodes(pg, xpath=".//table[contains(., 'Total Deaths')]") |
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nat_rows <- rvest::html_nodes(nat_tbl, "tbody > tr") |
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lapply(nat_rows, function(.x) { |
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nat_tds <- rvest::html_nodes(.x, "td") |
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nat_tds <- gsub(",", "", rvest::html_text(nat_tds)) |
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as_tibble(as.data.frame( |
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as.list( |
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set_names( |
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nat_tds, sprintf("X%02d", 1:length(nat_tds)) |
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) |
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), |
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stringsAsFactors = FALSE |
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)) |
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}) -> nat_rows |
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nat_tbl <- do.call(rbind.data.frame, nat_rows) |
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cov <- set_names(nat_tbl[, 1:5], c("year", "week", "total_deaths", "deaths", "pct_deaths")) |
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cov$cause <- "COVID-19" |
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pnu <- set_names(nat_tbl[, c(1:3, 6:7)], c("year", "week", "total_deaths", "deaths", "pct_deaths")) |
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pnu$cause <- "Pneumonia" |
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flu <- set_names(nat_tbl[, c(1:3, 8:9)], c("year", "week", "total_deaths", "deaths", "pct_deaths")) |
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flu$cause <- "Influenza" |
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nat_tbl <- rbind(cov, pnu, flu, stringsAsFactors = FALSE) |
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nat_tbl$region <- "National" |
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nat_tbl$source <- "NCHS" |
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nat_tbl$year <- clean_int(nat_tbl$year) |
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nat_tbl$week <- clean_int(nat_tbl$week) |
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nat_tbl$total_deaths <- clean_int(nat_tbl$total_deaths) |
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nat_tbl$deaths <- clean_int(nat_tbl$deaths) |
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nat_tbl$pct_deaths <- clean_num(nat_tbl$pct_deaths)/100 |
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as_tibble(nat_tbl[!is.na(nat_tbl$week),]) |
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} |
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#' Retrieve Regional Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI) |
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#' |
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#' @return data frame |
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#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html> |
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#' @export |
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nssp_er_visits_regional <- function() { |
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xml2::read_html( |
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"https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html" |
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) -> pg |
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regions <- sprintf("Region %d", 1:10) |
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lapply(regions, function(region){ |
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reg_tbl <- rvest::html_nodes(pg, xpath=".//table[contains(., 'National')]") |
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nat_rows <- rvest::html_nodes(reg_tbl, "tbody > tr") |
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lapply(nat_rows, function(.x) { |
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nat_tds <- rvest::html_nodes(.x, "td") |
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nat_tds <- gsub(",", "", rvest::html_text(nat_tds)) |
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as_tibble(as.data.frame( |
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as.list( |
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set_names( |
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nat_tds, sprintf("X%02d", 1:length(nat_tds)) |
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) |
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), |
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stringsAsFactors = FALSE |
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)) |
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}) -> nat_rows |
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reg_tbl <- do.call(rbind.data.frame, nat_rows) |
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cli <- set_names(reg_tbl[, 1:5], c("week", "num_fac", "total_ed_visits", "visits", "pct_visits")) |
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cli$visit_type <- "cli" |
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ili <- set_names(reg_tbl[, c(1:3, 6:7)], c("week", "num_fac", "total_ed_visits", "visits", "pct_visits")) |
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ili$visit_type <- "ili" |
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reg_tbl <- rbind(ili, cli, stringsAsFactors = FALSE) |
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reg_tbl$region <- region |
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reg_tbl$source <- "Emergency Departments" |
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reg_tbl$week <- as.character(clean_int(reg_tbl$week)) |
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reg_tbl$year <- clean_int(substr(reg_tbl$week, 1, 4)) |
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reg_tbl$week <- clean_int(substr(reg_tbl$week, 5, 6)) |
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reg_tbl$num_fac <- clean_int(reg_tbl$num_fac) |
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reg_tbl$visits <- clean_int(reg_tbl$visits) |
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reg_tbl$pct_visits <- clean_num(reg_tbl$pct_visits)/100 |
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reg_tbl[!is.na(reg_tbl$week),] |
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}) -> regs |
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out <- do.call(rbind.data.frame, regs) |
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as_tibble(out) |
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} |
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#' Retrieve National Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI) |
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#' |
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#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html> |
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#' @return data frame |
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#' @export |
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nssp_er_visits_national <- function() { |
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pg <- xml2::read_html("https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html") |
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nat_tbl <- rvest::html_nodes(pg, xpath=".//table[contains(., 'National')]") |
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nat_rows <- rvest::html_nodes(nat_tbl, "tbody > tr") |
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lapply(nat_rows, function(.x) { |
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nat_tds <- rvest::html_nodes(.x, "td") |
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nat_tds <- gsub(",", "", rvest::html_text(nat_tds)) |
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as_tibble(as.data.frame( |
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as.list( |
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set_names( |
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nat_tds, sprintf("X%02d", 1:length(nat_tds)) |
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) |
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), |
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stringsAsFactors = FALSE |
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)) |
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}) -> nat_rows |
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nat_tbl <- do.call(rbind.data.frame, nat_rows) |
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cli <- set_names(nat_tbl[, 1:5], c("week", "num_fac", "total_ed_visits", "visits", "pct_visits")) |
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cli$visit_type <- "cli" |
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ili <- set_names(nat_tbl[, c(1:3, 6:7)], c("week", "num_fac", "total_ed_visits", "visits", "pct_visits")) |
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ili$visit_type <- "ili" |
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nat_tbl <- rbind(ili, cli, stringsAsFactors = FALSE) |
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nat_tbl$region <- "National" |
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nat_tbl$source <- "Emergency Departments" |
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nat_tbl$year <- clean_int(substr(nat_tbl$week, 1, 4)) |
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nat_tbl$week <- clean_int(substr(nat_tbl$week, 5, 6)) |
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nat_tbl$num_fac <- clean_int(nat_tbl$num_fac) |
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nat_tbl$visits <- clean_int(nat_tbl$visits) |
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nat_tbl$pct_visits <- clean_num(nat_tbl$pct_visits)/100 |
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as_tibble(nat_tbl[!is.na(nat_tbl$week),]) |
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} |
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#' Retrieve Provisional Death Counts for Coronavirus Disease (COVID-19) |
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#' |
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#' @note Please see the indicated reference for all the caveats and precise meanings for each field. Also, |
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#' this function used the JSON API (<https://data.cdc.gov/resource/hc4f-j6nb.json>) |
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#' @return a list with 4 named elements: `by_week`, `by_age`, `by_state`, `by_sex` |
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#' @references <https://data.cdc.gov/api/views/hc4f-j6nb/rows.csv?accessType=DOWNLOAD&bom=true&format=true> |
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#' @export |
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provisional_death_counts <- function() { |
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res <- jsonlite::fromJSON("https://data.cdc.gov/resource/hc4f-j6nb.json") |
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res <- as_tibble(res) |
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res$covid_deaths <- clean_int(res$covid_deaths) |
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res$total_deaths <- clean_int(res$total_deaths) |
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res$pneumonia_deaths <- clean_int(res$pneumonia_deaths) |
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res$pneumonia_and_covid_deaths <- clean_int(res$pneumonia_and_covid_deaths) |
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res$all_influenza_deaths_j09_j11 <- clean_int(res$all_influenza_deaths_j09_j11) |
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res$percent_expected_deaths <- clean_num(res$percent_expected_deaths) |
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by_week <- res[res$group == "By week",] |
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by_age <- res[res$group == "By age",] |
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by_state <- res[res$group == "By state",] |
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by_sex <- res[res$group == "By sex",] |
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by_week <- by_week[!grepl("total", tolower(by_week$indicator)),] |
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by_week$group <- NULL |
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by_week$indicator <- as.Date(by_week$indicator, "%m/%d/%Y") |
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colnames(by_week) <- c( |
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"week", "covid_deaths", "total_deaths", "percent_expected_deaths", |
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"pneumonia_deaths", "pneumonia_and_covid_deaths", "all_influenza_deaths_j09_j11" |
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) |
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by_age$group <- NULL |
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colnames(by_age) <- c( |
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"age_group", "covid_deaths", "total_deaths", "percent_expected_deaths", |
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"pneumonia_deaths", "pneumonia_and_covid_deaths", "all_influenza_deaths_j09_j11" |
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) |
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by_age$age_group <- sub("–", "-", by_age$age_group, fixed=TRUE) |
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by_age$age_group <- sub("yea.*", "yr", by_age$age_group) |
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by_state$group <- NULL |
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colnames(by_state) <- c( |
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"state", "covid_deaths", "total_deaths", "percent_expected_deaths", |
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"pneumonia_deaths", "pneumonia_and_covid_deaths", "all_influenza_deaths_j09_j11" |
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) |
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by_state <- by_state[by_state$state != "Total US",] |
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by_sex$group <- NULL |
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colnames(by_sex) <- c( |
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"sex", "covid_deaths", "total_deaths", "percent_expected_deaths", |
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"pneumonia_deaths", "pneumonia_and_covid_deaths", "all_influenza_deaths_j09_j11" |
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) |
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by_sex <- by_sex[!grepl("Total", by_sex$sex),] |
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list( |
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by_week = as_tibble(by_week), |
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by_age = as_tibble(by_age), |
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by_state = as_tibble(by_state), |
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by_sex = as_tibble(by_sex) |
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) |
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} |
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#' Retrieve National Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC |
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#' |
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#' @return data frame |
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#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html> |
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#' @export |
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public_health_labs_national <- function() { |
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xml2::read_html( |
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"https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html" |
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) -> pg |
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nat_tbl <- rvest::html_nodes(pg, xpath=".//table[contains(., 'National')]") |
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nat_rows <- rvest::html_nodes(nat_tbl, "tbody > tr") |
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lapply(nat_rows, function(.x) { |
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nat_tds <- rvest::html_nodes(.x, "td") |
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nat_tds <- gsub(",", "", rvest::html_text(nat_tds)) |
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as_tibble(as.data.frame( |
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as.list( |
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set_names( |
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nat_tds, sprintf("X%02d", 1:length(nat_tds)) |
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) |
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), |
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stringsAsFactors = FALSE |
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)) |
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}) -> nat_rows |
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nat_tbl <- do.call(rbind.data.frame, nat_rows) |
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total <- set_names(nat_tbl[, 1:5], c("week", "num_labs", "tested", "tested_pos", "pct_pos")) |
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total$age_group <- "Overall" |
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a1 <- set_names(nat_tbl[, c(1:2, 6:8)], c("week", "num_labs", "tested", "tested_pos", "pct_pos")) |
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a1$age_group <- "0-4 yr" |
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a2 <- set_names(nat_tbl[, c(1:2, 9:11)], c("week", "num_labs", "tested", "tested_pos", "pct_pos")) |
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a2$age_group <- "5-17 yr" |
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a3 <- set_names(nat_tbl[, c(1:2, 12:14)], c("week", "num_labs", "tested", "tested_pos", "pct_pos")) |
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a3$age_group <- "18-49 yr" |
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a4 <- set_names(nat_tbl[, c(1:2, 15:17)], c("week", "num_labs", "tested", "tested_pos", "pct_pos")) |
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a4$age_group <- "50-64 yr" |
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a5 <- set_names(nat_tbl[, c(1:2, 18:20)], c("week", "num_labs", "tested", "tested_pos", "pct_pos")) |
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a5$age_group <- "65+ yr" |
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nat_tbl <- rbind(total, a1, a2, a3, a4, a5, stringsAsFactors = FALSE) |
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nat_tbl$region <- "National" |
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nat_tbl$source <- "Public Health Labs" |
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nat_tbl$week <- clean_int(nat_tbl$week) |
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nat_tbl$num_labs <- clean_int(nat_tbl$num_labs) |
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nat_tbl$tested <- clean_int(nat_tbl$tested) |
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nat_tbl$tested_pos <- clean_int(nat_tbl$tested_pos) |
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nat_tbl$pct_pos <- clean_num(nat_tbl$pct_pos)/100 |
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nat_tbl[!is.na(nat_tbl$week),] |
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} |
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#' Retrieve Regional Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC |
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#' |
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#' @return data frame |
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#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html> |
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#' @export |
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public_health_labs_regional <- function() { |
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xml2::read_html( |
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"https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html" |
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) -> pg |
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regions <- sprintf("Region %d", 1:10) |
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lapply(regions, function(region){ |
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rvest::html_node( |
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pg, |
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xpath=sprintf(".//table[contains(., '%s (')]", region) |
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) -> reg_tbl |
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|
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reg_tbl <- rvest::html_table(reg_tbl, header = TRUE, trim = TRUE) |
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colnames(reg_tbl) <- c("week", "num_labs", "tested", "tested_pos", "pct_pos") |
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reg_tbl$region <- region |
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reg_tbl$source <- "Public Health Labs" |
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|
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reg_tbl$week <- clean_int(reg_tbl$week) |
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reg_tbl$num_labs <- clean_int(reg_tbl$num_labs) |
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reg_tbl$tested <- clean_int(reg_tbl$tested) |
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reg_tbl$tested_pos <- clean_int(reg_tbl$tested_pos) |
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reg_tbl$pct_pos <- clean_num(reg_tbl$pct_pos)/100 |
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|
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as_tibble(reg_tbl[!is.na(reg_tbl$week),]) |
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|
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}) -> regs |
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|
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out <- do.call(rbind.data.frame, regs) |
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|
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as_tibble(out) |
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|
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} |
@ -0,0 +1,17 @@ |
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% Generated by roxygen2: do not edit by hand |
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% Please edit documentation in R/clinical-labs.R |
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\name{clinical_labs} |
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\alias{clinical_labs} |
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\title{Retrieve U.S. Clinical Laboratories Reporting SARS-CoV-2 Test Results to CDC} |
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\usage{ |
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clinical_labs() |
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} |
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\value{ |
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data frame |
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} |
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\description{ |
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Retrieve U.S. Clinical Laboratories Reporting SARS-CoV-2 Test Results to CDC |
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} |
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\references{ |
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\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/reporting-cov2-results.html} |
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} |
@ -1,11 +0,0 @@ |
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% Generated by roxygen2: do not edit by hand |
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% Please edit documentation in R/utils.R |
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\name{has_bom} |
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\alias{has_bom} |
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\title{Tests whether a raw httr response or character vector has a byte order mark (BOM)} |
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\usage{ |
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has_bom(resp, encoding = "UTF-8") |
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} |
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\description{ |
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Tests whether a raw httr response or character vector has a byte order mark (BOM) |
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} |
@ -0,0 +1,17 @@ |
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% Generated by roxygen2: do not edit by hand |
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% Please edit documentation in R/mortality.R |
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\name{mortality_surveillance_data} |
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\alias{mortality_surveillance_data} |
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\title{Retrieve NCHS Mortality Surveillance Data} |
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\usage{ |
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mortality_surveillance_data() |
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} |
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\value{ |
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data frame |
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} |
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\description{ |
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Retrieve NCHS Mortality Surveillance Data |
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} |
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\references{ |
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\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nchs-data.html} |
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} |
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% Generated by roxygen2: do not edit by hand |
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% Please edit documentation in R/nssp-cd.R |
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\name{nssp_er_visits_national} |
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\alias{nssp_er_visits_national} |
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\title{Retrieve National Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI)} |
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\usage{ |
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nssp_er_visits_national() |
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} |
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\value{ |
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data frame |
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} |
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\description{ |
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Retrieve National Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI) |
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} |
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\references{ |
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\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html} |
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} |
@ -0,0 +1,17 @@ |
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% Generated by roxygen2: do not edit by hand |
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% Please edit documentation in R/nss-cd-reg.R |
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\name{nssp_er_visits_regional} |
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\alias{nssp_er_visits_regional} |
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\title{Retrieve Regional Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI)} |
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\usage{ |
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nssp_er_visits_regional() |
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} |
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\value{ |
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data frame |
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} |
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\description{ |
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Retrieve Regional Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI) |
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} |
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\references{ |
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\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html} |
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} |
@ -0,0 +1,21 @@ |
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% Generated by roxygen2: do not edit by hand |
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% Please edit documentation in R/provisional-deaths.R |
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\name{provisional_death_counts} |
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\alias{provisional_death_counts} |
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\title{Retrieve Provisional Death Counts for Coronavirus Disease (COVID-19)} |
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\usage{ |
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provisional_death_counts() |
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} |
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\value{ |
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a list with 4 named elements: \code{by_week}, \code{by_age}, \code{by_state}, \code{by_sex} |
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} |
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\description{ |
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Retrieve Provisional Death Counts for Coronavirus Disease (COVID-19) |
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} |
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\note{ |
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Please see the indicated reference for all the caveats and precise meanings for each field. Also, |
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this function used the JSON API (\url{https://data.cdc.gov/resource/hc4f-j6nb.json}) |
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} |
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\references{ |
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\url{https://data.cdc.gov/api/views/hc4f-j6nb/rows.csv?accessType=DOWNLOAD&bom=true&format=true} |
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} |
@ -0,0 +1,17 @@ |
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% Generated by roxygen2: do not edit by hand |
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% Please edit documentation in R/public-health-labs-national.R |
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\name{public_health_labs_national} |
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\alias{public_health_labs_national} |
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\title{Retrieve National Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC} |
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\usage{ |
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public_health_labs_national() |
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} |
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\value{ |
|||
data frame |
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} |
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\description{ |
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Retrieve National Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC |
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} |
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\references{ |
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\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html} |
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} |
@ -0,0 +1,17 @@ |
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% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/public-health-labs-regional.R |
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\name{public_health_labs_regional} |
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\alias{public_health_labs_regional} |
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\title{Retrieve Regional Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC} |
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\usage{ |
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public_health_labs_regional() |
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} |
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\value{ |
|||
data frame |
|||
} |
|||
\description{ |
|||
Retrieve Regional Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC |
|||
} |
|||
\references{ |
|||
\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html} |
|||
} |
@ -1,11 +0,0 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/utils.R |
|||
\name{sans_bom} |
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\alias{sans_bom} |
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\title{Remove byte order mark (BOM) from \code{httr::response} object or character vector} |
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\usage{ |
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sans_bom(resp) |
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} |
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\description{ |
|||
Remove byte order mark (BOM) from \code{httr::response} object or character vector |
|||
} |
Caricamento…
Reference in new issue