Nothing
## ----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 = epirange(20210105, 20210410)
# )
## -----------------------------------------------------------------------------
# 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
epidata <- pub_covidcast(
source = "fb-survey",
signals = "smoothed_cli",
geo_type = "state",
time_type = "day",
geo_values = "pa",
time_values = epirange(20210105, 20210410)
)
knitr::kable(head(epidata))
## ----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)
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