In annecori/mRIIDSprocessData: Epidemiological forcasting using real-time data

library(dplyr)
library(magrittr)
library(stringr)
library(ggplot2)

may22_bikoro <- here::here("data/CaseCounts/drc",
                    "22_may_2018.xlsx") %>%
    readxl::read_excel(sheet = "Bikoro")

may22_iboko <- here::here("data/CaseCounts/drc",
                          "22_may_2018.xlsx") %>%
    readxl::read_excel(sheet = "Iboko")

may22_wangata <- here::here("data/CaseCounts/drc",
                          "22_may_2018.xlsx") %>%
    readxl::read_excel(sheet = "Wangata")


all_regions <- data.frame(date = may22_bikoro$date_onset_iso,
                          Bikoro = may22_bikoro$total,
                          Iboko = may22_iboko$total,
                          Wangata = may22_wangata$total)
all_regions$date <- lubridate::ymd(all_regions$date)
all_regions$date <- lubridate::dmy(all_regions$date)
readr::write_csv(x = all_regions,
                 path = here::here("data/CaseCounts/drc",
                                   "22_may_2018.csv"))

annecori/mRIIDSprocessData documentation built on May 29, 2019, 1:16 p.m.