package main

var rCode string = `
library(tidyverse)
library(ggplot2)
library(gridExtra)
library(lubridate)

gc()

options(scipen=100000)

d <- read_csv('~/prog/covid/nyopendata/rows.csv')
d <- pivot_longer(d, c('New Positives', 'Total Number of Tests Performed'))
d <- transmute(d, date=mdy(d$'Test Date'), county=County, name=name, value=value)
queens <- subset(d, county=='Queens')
qrate <- pivot_wider(queens, names_from='name') %>% transmute(date=date,county=county,name='Positive Rate', value=ifelse(`+"`"+`New Positives`+"`"+`==0,0,`+"`"+`New Positives`+"`"+`/`+"`"+`Total Number of Tests Performed`+"`"+`))

totals <- group_by(d, date, county='New York', name) %>% summarize(value=sum(value)) %>% ungroup
trate <- pivot_wider(totals, names_from='name') %>% transmute(date=date,county=county,name='Positive Rate', value=ifelse(`+"`"+`New Positives`+"`"+`==0,0,`+"`"+`New Positives`+"`"+`/`+"`"+`Total Number of Tests Performed`+"`"+`))

d2 <- rbind(queens, totals)

p1 <- ggplot(queens, aes(x=date, y=value, color=name))+geom_line()+scale_y_log10(n.breaks=6)+labs(y='',color='')+ggtitle('Queens')+theme(plot.title=element_text(hjust = 0.5))+theme(legend.position='bottom')
#p2 <- ggplot(d, aes(x=date, y=value, color=name))+geom_line(data=queens)+stat_smooth(geom='line', linetype='dotted', data=queens, method='gam', se=FALSE)+geom_line(alpha=1/3, data=totals)+stat_smooth(geom='line', linetype='dotted', data=totals, method='gam', se=FALSE)+scale_y_log10(n.breaks=6)+labs(y='')+labs(color='')+ggtitle('New York')+theme(plot.title=element_text(hjust = 0.5))+theme(legend.position='bottom')
p2 <- ggplot(totals, aes(x=date, y=value, color=name))+geom_line()+stat_smooth(geom='line', linetype='dotted', method='gam', se=FALSE)+scale_y_log10(n.breaks=6)+labs(y='')+labs(color='')+ggtitle('New York')+theme(plot.title=element_text(hjust = 0.5))+theme(legend.position='bottom')

pr1 <- ggplot(qrate, aes(x=date, y=value)) + geom_line()+geom_smooth(method='gam',formula=y~s(x, bs="cs"),se=FALSE)+scale_y_continuous(labels = scales::percent,)+labs(y='Positive Rate')+coord_cartesian(ylim=c(0,0.04))+ggtitle('Queens')+theme(plot.title=element_text(hjust = 0.5))
pr2 <- ggplot(trate, aes(x=date, y=value)) + geom_line()+geom_smooth(method='gam',formula=y~s(x, bs="cs"),se=FALSE)+scale_y_continuous(labels = scales::percent)+labs(y='Positive Rate')+coord_cartesian(ylim=c(0,0.04))+ggtitle('New York')+theme(plot.title=element_text(hjust = 0.5))

p <- grid.arrange(p1,p2,pr1,pr2,ncol=2)

zip <- read_csv('~/prog/covid/nyopendata/timeseries.csv')
zip <- pivot_longer(zip, c('COVID_CASE_COUNT','COVID_DEATH_COUNT','TOTAL_COVID_TESTS'))
zip$date <- mdy(zip$date)
`