LalaNguyen / dataproduct-pitching

title	author	highlighter	mode	hitheme	knit	subtitle	framework	widgets
Wind & Temperature Measurement	Lala NG	highlight.js	selfcontained	tomorrow	slidify::knit2slides	Data Product Development	io2012

Objectives

1. Demonstrate the ability of using basic shiny app
2. In Slide 1, reactive output display with isolate. GGplot2 is used. Temperature on Monthly basis is recorded.
3. Slide 2 presents Wind Measurement on regular daily basis using scatter plot
4. Data Source Interaction - airquality.

---

Temperature Measurement on Monthly basis

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%

Wind Measurement classified by Day

*** =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.

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Wind Measurement classified by Day (cont)

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 Source Interaction

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/