title | author | highlighter | mode | hitheme | knit | subtitle | framework | widgets |
---|---|---|---|---|---|---|---|---|
Wind & Temperature Measurement |
Lala NG |
highlight.js |
selfcontained |
tomorrow |
slidify::knit2slides |
Data Product Development |
io2012 |
- Demonstrate the ability of using basic shiny app
- In Slide 1, reactive output display with isolate. GGplot2 is used. Temperature on Monthly basis is recorded.
- Slide 2 presents Wind Measurement on regular daily basis using scatter plot
- Data Source Interaction - airquality.
Temperature is remarkbly higher in middle of summer.
This is the link to the shiny app: https://lalang.shinyapps.io/dataproduct/
--- &twocol w1:40% w2:60%
*** =right
library(UsingR)
require(ggplot2)
require(knitr)
data(airquality)
ggplot(airquality, aes(Day, Wind, color = Month))+geom_point()+geom_line(stat = "hline", yintercept = "mean", aes(colour = Month))
*** =left
- The variation of wind's velocity is generally low at the beginning of autumn. In contrast, summer's days have fluctuated pattern.
- Top windy day is around 15-17 in June.
To plot the wind measurement on daily basis, we use ggplots2 and the avg line
require(ggplot2)
require(knitr)
data(airquality)
p1 <- ggplot(airquality, aes(Day, Wind, color = Month))+
geom_point()+
geom_line(stat = "hline", yintercept = "mean", aes(colour = Month))
This is the link to the shiny app: https://lalang.shinyapps.io/dataproduct/
Data manipulation can be done in R while navigating the data source tab.
This is the link to the shiny app: https://lalang.shinyapps.io/dataproduct/