This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# | |
# Copyright (c) 2020 Anthony J. Greenberg | |
# | |
# Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: | |
# | |
# 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. | |
# | |
# 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. | |
# | |
# 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. | |
# | |
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, | |
# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS | |
# BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF | |
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER | |
# IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF | |
# THE POSSIBILITY OF SUCH DAMAGE. | |
# | |
library(data.table) | |
library(ggplot2) | |
# | |
# This script downloads New York State COVID-19 test data and plots various statistics. | |
# The plots are exported as HTML widgets for embedding on a website. | |
# Plotting and export require ggplot2, plotly, and htmlwidgets. Data wrangling requires data.table. | |
# Interactions with the New York State DOH API require RSocrata. | |
# | |
# Download the NYS data. | |
nysDT <- as.data.table(RSocrata::read.socrata( | |
"https://health.data.ny.gov/resource/xdss-u53e.json", | |
stringsAsFactors=FALSE)) | |
nysDT <- nysDT[, test_date := as.Date(test_date)] | |
num.cols <- c("new_positives", "cumulative_number_of_positives", | |
"total_number_of_tests", "cumulative_number_of_tests") | |
nysDT <- nysDT[, (num.cols) := lapply(.SD, as.integer), .SDcols = num.cols] | |
# | |
# Extract the data for Tompkins and surrounding counties. | |
# | |
region <- data.table(county = c("Tompkins", "Tioga", "Chemung", | |
"Schuyler", "Seneca", "Cayuga", | |
"Cortland", "Broome", "Onondaga"), | |
population = c(103000, 49000, 86000, 18000, 35000, | |
78000, 48000, 194000, 464000)) | |
nysDT <- nysDT[county %in% region[, county],] | |
locDT <- nysDT[county != "Tompkins", lapply(.SD, sum), by = test_date, | |
.SDcols = c("new_positives", "cumulative_number_of_positives", | |
"total_number_of_tests", "cumulative_number_of_tests")] | |
tomDT <- nysDT[county == "Tompkins", | |
c("test_date", "new_positives", "cumulative_number_of_positives", | |
"total_number_of_tests", "cumulative_number_of_tests")] | |
# | |
# Separate the Tompkins and whole region data; calculate per capita statistics. | |
# | |
tomDT <- tomDT[, data := "Tompkins"] | |
locDT <- locDT[, data := "region"] | |
locDT <- rbind(tomDT, locDT) | |
locDT <- locDT[, population := rep( | |
c(region[county == "Tompkins", sum(population)], | |
region[county != "Tompkins", sum(population)]), | |
times = unlist(locDT[, .N, by = data][, 2]))] | |
locDT <- locDT[, pc_tests := total_number_of_tests / population] | |
locDT <- locDT[, percent_positive := 100 * new_positives / total_number_of_tests] | |
locDT <- locDT[, pctPosMn := frollmean(percent_positive, 7, na.rm = TRUE)] | |
# | |
# Get Tompkins county hospitalization data and add to what I already have | |
# | |
prevData <- fread("../tcDOHactiveHosp.tsv") | |
orevData <- prevData[, date := as.Date(date)] | |
curlCmd <- paste0("curl -s https://tompkinscountyny.gov/health#table", | |
" | grep -B 8 'END TABLE' | head -1 |", | |
" sed 's/\\s\\+//g' | sed 's/<\\/td>//'") | |
ahToday <- system(curlCmd, intern = FALSE) | |
prevData <- rbind(prevData, | |
data.table(date = Sys.Date(), active.hospitalizations = ahToday)) | |
fwrite(prevData, file="../tcDOHactiveHosp.tsv", sep = "\t", quote = FALSE, na = "NA") | |
prevData <- prevData[, | |
rlMean := frollmean(active.hospitalizations, 7, na.rm = TRUE)] | |
# | |
# Plot and export to HTML | |
# | |
ggp <- ggplot(data = locDT, | |
aes(x = test_date, y = new_positives, fill = data)) + | |
geom_col() + | |
theme_classic(base_size = 18) + | |
theme(legend.title = element_blank(), axis.title.x = element_blank()) + | |
ylab("daily number of positives") | |
py <- plotly::ggplotly(ggp) | |
htmlwidgets::saveWidget(plotly::as_widget(py), "positivesPlot.html") | |
ggp <- ggplot(data = locDT, | |
aes(x = test_date, y = total_number_of_tests, fill = data)) + | |
geom_col() + | |
theme_classic(base_size = 18) + | |
theme(legend.title = element_blank(), axis.title.x = element_blank()) + | |
ylab("daily number of tests") | |
py <- plotly::ggplotly(ggp) | |
htmlwidgets::saveWidget(plotly::as_widget(py), "testsPlot.html") | |
ggp <- ggplot(data = locDT, aes(x = test_date, y = pc_tests, fill = data)) + | |
geom_col() + | |
theme_classic(base_size = 18) + | |
theme(legend.title = element_blank(), axis.title.x = element_blank()) + | |
ylab("daily number of tests per capita") | |
py <- plotly::ggplotly(ggp) | |
htmlwidgets::saveWidget(plotly::as_widget(py), "pcTestsPlot.html") | |
ggp <- ggplot(data = locDT, | |
aes(x = test_date, y = percent_positive, color = data)) + | |
geom_point(size = 1, alpha = 0.5) + | |
geom_line(data = locDT, | |
aes(x = test_date, y = pctPosMn, color = data), size = 1.2) + | |
theme_classic(base_size = 18) + | |
theme(legend.title = element_blank(), axis.title.x = element_blank()) + | |
ylab("% positive") | |
py <- plotly::ggplotly(ggp) | |
htmlwidgets::saveWidget(plotly::as_widget(py), "pctPositivePlot.html") | |
ggp <- ggplot(data = prevData, aes(x = date, y = active.hospitalizations)) + | |
geom_col(fill = "grey60") + | |
theme_classic(base_size = 18) + | |
ylab("number of people hospitalized") | |
py <- plotly::ggplotly(ggp) | |
htmlwidgets::saveWidget(plotly::as_widget(py), "tcDOHhosp.html") |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment