What follows is a set of examples of California STD Surveillance data visualized using the plotly package for R. Add another descriptive sentence here.
#simple barchart
plot_ly(
std_gg1,
x= ~year,
y= ~cases,
color= ~sex,
type="bar"
# mode="bar"
) #bar chart - side by side vs stacked
plot_ly(
std_gg1,
x= ~year,
y= ~cases,
color= ~sex,
type="bar"
) %>%
layout(barmode="stack")std_gg2a <- std_gg %>%
filter(county != "California" & year=="2018" & sex=="Total") %>%
select(county, disease_f, rate)
#boxplot
plot_ly(
std_gg2a,
y=~rate,
color=~disease_f,
type="box"
)#trend over time in alameda county with confidence intervals
std_gg3 <- std_gg %>%
filter(county=="Alameda" & sex=="Total")
#make a presentable table
plot_ly(
std_gg3,
x=~year,
y=~rate,
color=~disease_f,
type="scatter",
mode="lines",
colors=c("darkorange","darkcyan","darkslateblue"),
text = ~paste('Cases: ',cases,'<br>Population: ',population,'<br>Rate: ',rate)
) %>%
layout(
title="Alameda County STD Rates, 2001-2018",
yaxis=list(title="Case Rate per 100,000"),
xaxis=list(title="Year"),
paper_bgcolor="azure",
plot_bgcolor="white"
)#add trace example
std_gg3b <- std_gg %>%
filter(county=="Alameda" & sex=="Total") %>%
select(year,disease,rate) %>%
pivot_wider(names_from=disease, values_from=rate)
plot_ly(
std_gg3b,
x=~year,
y=~`Chlamydia`,
name="Chlamydia",
type="scatter",
mode="markers"
) %>%
add_trace(y=~`Gonorrhea`,name="Gonorrhea",mode="lines")%>%
add_trace(y=~`Early Syphilis`,name="Early Syphilis",mode="lines+markers") %>%
layout(yaxis=list(title="Rate per 100,000"))#subplot example
plot1 <- plot_ly(std_gg3b,
x=~year,
y=~`Chlamydia`,
name="Chlamydia",
type="scatter")
plot2 <- plot_ly(std_gg3b,
x=~year,
y=~`Gonorrhea`,
name="Gonorrhea",
type="scatter")
subplot(plot1,plot2,nrows=2,shareX=T)subplot(plot1,plot2,shareY=T)