Plotly is a tool that makes it easy to create interactive charts. There is a web version of plotly, as well as packages for R and Python.

In R, plotly works nicely with R Markdown files, which are files that seamlessly blend R code and other visual content like text and images. R Markdown files can be compiled (or “knit”) into a variety of formats. When you have interactive plotly charts, you can knit the R Markdown file to an HTML document that can be shared directly with others or hosted on a website.

box <- plot_ly(nc_no2_hourly, x = ~`Sample Measurement`, color = ~`County Name`, type = "box")
box
no2_by_county <- nc_no2_hourly %>%
  pivot_wider(names_from = `County Name`, values_from = `Sample Measurement`)

line <- plot_ly(no2_by_county, x=~`timestamp`, y=~`Forsyth`, name='Forsyth', type = 'scatter', mode='lines') %>%
  add_trace(y = ~`Mecklenburg`, name = 'Mecklenburg') %>%
  add_trace(y = ~`Wake`, name = 'Wake')
  
line  
no2_by_county_daily <- nc_no2_hourly %>%
  group_by(`County Name`, `Date Local`) %>%
  summarise(mean_measurement = mean(`Sample Measurement`, na.rm=T)) %>%
  pivot_wider(names_from = `County Name`, values_from = mean_measurement)

line <- plot_ly(no2_by_county_daily, x=~`Date Local`, y=~`Forsyth`, name='Forsyth', type = 'scatter', mode='lines') %>%
  add_trace(y = ~`Mecklenburg`, name = 'Mecklenburg') %>%
  add_trace(y = ~`Wake`, name = 'Wake')
  
line