## ----echo = FALSE, message = FALSE-------------------------------------------- knitr::opts_chunk$set(collapse = TRUE, comment = "#>") options(tibble.print_min = 4L, tibble.print_max = 4L, max.print = 4L) ## ----------------------------------------------------------------------------- library(epidatr) library(dplyr) # Obtain the most up-to-date version of the smoothed covid-like illness (CLI) # signal from the COVID-19 Trends and Impact survey for the US epidata <- pub_covidcast( source = "fb-survey", signals = "smoothed_cli", geo_type = "nation", time_type = "day", geo_values = "us", time_values = epirange(20210105, 20210410) ) knitr::kable(head(epidata)) ## ----eval = FALSE------------------------------------------------------------- # # Obtain the most up-to-date version of the smoothed covid-like illness (CLI) # # signal from the COVID-19 Trends and Impact survey for all states # pub_covidcast( # source = "fb-survey", # signals = "smoothed_cli", # geo_type = "state", # time_type = "day", # geo_values = "*", # time_values = epirange(20210105, 20210410) # ) ## ----eval = FALSE------------------------------------------------------------- # # Obtain the most up-to-date version of the smoothed covid-like illness (CLI) # # signal from the COVID-19 Trends and Impact survey for Pennsylvania # pub_covidcast( # source = "fb-survey", # signals = "smoothed_cli", # geo_type = "state", # time_type = "day", # geo_values = c("pa", "ca", "fl"), # time_values = "*" # ) ## ----eval = FALSE------------------------------------------------------------- # # Obtain the smoothed covid-like illness (CLI) signal from the COVID-19 # # Trends and Impact survey for Pennsylvania as it was on 2021-06-01 # pub_covidcast( # source = "fb-survey", # signals = "smoothed_cli", # geo_type = "state", # time_type = "day", # geo_values = "pa", # time_values = epirange(20210105, 20210410), # as_of = "2021-06-01" # ) ## ----out.height="65%"--------------------------------------------------------- library(ggplot2) ggplot(epidata, aes(x = time_value, y = value)) + geom_line() + labs( title = "Smoothed CLI from Facebook Survey", subtitle = "PA, 2021", x = "Date", y = "CLI" ) ## ----class.source = "fold-hide", out.height="65%"----------------------------- library(maps) # Obtain the most up-to-date version of the smoothed covid-like illness (CLI) # signal from the COVID-19 Trends and Impact survey for all states on a single day cli_states <- pub_covidcast( source = "fb-survey", signals = "smoothed_cli", geo_type = "state", time_type = "day", geo_values = "*", time_values = 20210410 ) # Get a mapping of states to longitude/latitude coordinates states_map <- map_data("state") # Convert state abbreviations into state names cli_states <- mutate( cli_states, state = ifelse( geo_value == "dc", "district of columbia", state.name[match(geo_value, tolower(state.abb))] %>% tolower() ) ) # Add coordinates for each state cli_states <- left_join(states_map, cli_states, by = c("region" = "state")) # Plot ggplot(cli_states, aes(x = long, y = lat, group = group, fill = value)) + geom_polygon(colour = "black", linewidth = 0.2) + coord_map("polyconic") + labs( title = "Smoothed CLI from Facebook Survey", subtitle = "All states, 2021-04-10", x = "Longitude", y = "Latitude" ) ## ----eval = FALSE------------------------------------------------------------- # avail_endpoints() ## ----echo = FALSE------------------------------------------------------------- invisible(capture.output(endpts <- avail_endpoints())) knitr::kable(endpts)