Bob Rudis
6 years ago
22 changed files with 370 additions and 113 deletions
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Package: cdcfluview |
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Type: Package |
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Title: cdcfluview is package that retrieves the data behind the CDC's FluView portal |
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Version: 0.3 |
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Date: 2015-08-07 |
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Title: Retrieve Flu Season Data from the CDC FluView Portal |
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Version: 0.4.0.9000 |
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Date: 2015-08-09 |
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Author: Bob Rudis (@hrbrmstr) |
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Maintainer: Bob Rudis <bob@rudis.net> |
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Description: The CDC's FluView is a Flash portal and the only way to get flu season |
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data is to use GUI controls, making it tedious to retrieve updates. This package |
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uses the same API the portal does to programmatically retrieve data. |
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Description: The U.S. Centers for Disease Control (CDC) maintains a portal |
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<http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html> for |
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accessing state, regional and national influenza statistics. The Flash |
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interface makes it difficult and time-consuming to select and retrieve |
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influenza data. This package provides functions to access the data provided |
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by portal's underlying API. |
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URL: http://github.com/hrbrmstr/cdcfluview |
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BugReports: https://github.com/hrbrmstr/cdcfluview/issues |
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License: MIT + file LICENSE |
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LazyData: TRUE |
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Suggests: |
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testthat |
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Imports: |
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httr (>= 0.3.0), |
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pbapply |
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pbapply, |
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xml2, |
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dplyr |
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Depends: |
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R (>= 3.0.0) |
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|
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#' A package to retrive data behind the CDC FluView portal |
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#' Retrieve Flu Season Data from the CDC FluView Portal |
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#' |
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#' The U.S. Centers for Disease Control (CDC) maintains a portal |
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#' \code{http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html} for |
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#' accessing state, regional and national influenza statistics. The Flash |
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#' interface makes it difficult and time-consuming to select and retrieve |
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#' influenza data. This package provides functions to access the data provided |
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#' by portal's underlying API. |
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#' |
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#' @name cdcfluview |
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#' @docType package |
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#' @author Bob Rudis (@@hrbrmstr) |
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#' @import httr pbapply |
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#' @import httr pbapply xml2 dplyr |
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NULL |
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|
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#' @title HHS Region Table |
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#' @description This dataset contains the names, numbers, regional offices for |
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#' and states/territories belonging to the (presently) 10 HHS U.S. |
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#' regions in "long" format. It consists of a \code{data.frame} |
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#' with the following columns: |
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#' |
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#' \itemize{ |
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#' \item \code{region}: the official HHS region name (e.g. "\code{Region 1}") |
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#' \item \code{region_number}: the associated region number |
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#' \item \code{regional_office}: the HHS regional office for the entire region |
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#' \item \code{state_or_territory}: state or territory belonging to the region |
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#' } |
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#' |
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#' @docType data |
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#' @keywords datasets |
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#' @name hhs_regions |
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#' |
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#' @references \url{http://www.hhs.gov/iea/regional/} |
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#' @usage data(hhs_regions) |
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#' @note Last updated 2015-08-09. |
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#' @format A data frame with 59 rows and 4 variables |
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NULL |
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#' Retrieves weekly influenza surveillance report from the CDC |
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#' |
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#' The CDC publishes a \href{http://www.cdc.gov/flu/weekly/usmap.htm}{weekly |
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#' influenza report} detailing high-level flu activity per-state. They also |
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#' publish a data file (see \code{References}) of historical report readings. |
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#' This function reads that XML file and produces a long \code{data_frame} |
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#' with the historical surveillance readings.\cr |
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#' \cr |
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#' This function provides similar data to \code{\link{get_state_data}} but without |
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#' the reporting source metadata and a limit on the historical flu information. |
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#' |
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#' @references \url{http://www.cdc.gov/flu/weekly/flureport.xml} |
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#' @return \code{tbl_df} (also classed with \code{cdcweeklyreport}) with six |
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#' columns: \code{year}, \code{week_number}, \code{state}, \code{color}, |
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#' \code{label}, \code{subtitle} |
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#' @export |
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#' @examples \dontrun{ |
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#' get_weekly_flu_report() |
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#' } |
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get_weekly_flu_report <- function() { |
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|
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# grab the report |
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doc <- read_xml("http://www.cdc.gov/flu/weekly/flureport.xml") |
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# extract the time periods |
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periods <- xml_attrs(xml_find_all(doc, "timeperiod")) |
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# for each period extract the state information and |
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# shove it all into a data frame |
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bind_rows(pblapply(periods, function(period) { |
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tp <- sprintf("//timeperiod[@number='%s' and @year='%s']", |
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period["number"], period["year"]) |
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weeks <- xml_find_one(doc, tp) |
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kids <- xml_children(weeks) |
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abbrev <- xml_text(xml_find_all(kids, "abbrev"), TRUE) |
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color <- xml_text(xml_find_all(kids, "color"), TRUE) |
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label <- xml_text(xml_find_all(kids, "label"), TRUE) |
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data_frame(year=period["year"], |
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week_number=period["number"], |
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state=abbrev, |
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color=color, |
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label=label, |
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subtitle=period["subtitle"]) |
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})) -> out |
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class(out) <- c("cdcweeklyreport", class(out)) |
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out |
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} |
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After Width: | Height: | Size: 183 KiB |
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After Width: | Height: | Size: 343 KiB |
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After Width: | Height: | Size: 83 KiB |
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Before Width: | Height: | Size: 140 KiB After Width: | Height: | Size: 140 KiB |
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hhs_regions <- read.table(text="region;region_number;regional_office;state_or_territory |
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Region 1;1;Boston;Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont |
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Region 2;2;New York;New Jersey, New York, Puerto Rico, Virgin Islands |
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Region 3;3;Philadelphia;Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia |
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Region 4;4;Atlanta;Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee |
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Region 5;5;Chicago;Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin |
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Region 6;6;Dallas;Arkansas, Louisiana, New Mexico, Oklahoma, Texas |
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Region 7;7;Kansas City;Iowa, Kansas, Missouri, Nebraska |
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Region 8;8;Denver;Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming |
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Region 9;9;San Francisco;Arizona, California, Hawaii, Nevada, American Samoa, Commonwealth of the Northern Mariana Islands, Federated States of Micronesia, Guam, Marshall Islands, Republic of Palau |
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Region 10;10;Seattle;Alaska, Idaho, Oregon, Washington", sep=";", stringsAsFactors=FALSE, header=TRUE) |
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library(stringr) |
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do.call(rbind.data.frame, lapply(1:nrow(hhs_regions), function(i) { |
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x <- hhs_regions[i,] |
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rownames(x) <- NULL |
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out <- data.frame(x[, c(1:3)], |
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str_split(x$state_or_territory, ", ")[1], |
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stringsAsFactors=FALSE) |
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colnames(out) <- c("region", "region_number", "regional_office", "state_or_territory") |
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out |
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})) -> hhs_regions |
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str(hhs_regions) |
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devtools::use_data(hhs_regions, overwrite=TRUE) |
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% Generated by roxygen2 (4.1.1): do not edit by hand |
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% Please edit documentation in R/get_weekly_flu_report.r |
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\name{get_weekly_flu_report} |
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\alias{get_weekly_flu_report} |
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\title{Retrieves weekly influenza surveillance report from the CDC} |
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\usage{ |
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get_weekly_flu_report() |
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} |
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\value{ |
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\code{tbl_df} (also classed with \code{cdcweeklyreport}) with six |
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columns: \code{year}, \code{week_number}, \code{state}, \code{color}, |
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\code{label}, \code{subtitle} |
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} |
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\description{ |
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The CDC publishes a \href{http://www.cdc.gov/flu/weekly/usmap.htm}{weekly |
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influenza report} detailing high-level flu activity per-state. They also |
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publish a data file (see \code{References}) of historical report readings. |
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This function reads that XML file and produces a long \code{data_frame} |
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with the historical surveillance readings.\cr |
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\cr |
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This function provides similar data to \code{\link{get_state_data}} but without |
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the reporting source metadata and a limit on the historical flu information. |
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} |
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\examples{ |
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\dontrun{ |
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get_weekly_flu_report() |
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} |
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} |
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\references{ |
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\url{http://www.cdc.gov/flu/weekly/flureport.xml} |
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} |
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|
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% Generated by roxygen2 (4.1.1): do not edit by hand |
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% Please edit documentation in R/datasets.r |
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\docType{data} |
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\name{hhs_regions} |
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\alias{hhs_regions} |
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\title{HHS Region Table} |
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\format{A data frame with 59 rows and 4 variables} |
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\usage{ |
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data(hhs_regions) |
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} |
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\description{ |
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This dataset contains the names, numbers, regional offices for |
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and states/territories belonging to the (presently) 10 HHS U.S. |
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regions in "long" format. It consists of a \code{data.frame} |
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with the following columns: |
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|
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\itemize{ |
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\item \code{region}: the official HHS region name (e.g. "\code{Region 1}") |
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\item \code{region_number}: the associated region number |
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\item \code{regional_office}: the HHS regional office for the entire region |
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\item \code{state_or_territory}: state or territory belonging to the region |
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} |
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} |
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\note{ |
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Last updated 2015-08-09. |
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} |
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\references{ |
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\url{http://www.hhs.gov/iea/regional/} |
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} |
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\keyword{datasets} |
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|
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