Time Series and Visualization

Time series can be seen as a vector or matrix of numbers, along with qualitative and quantitative data that has been recorded. once stored in R studio you can create a visualization graphs of that data and see forecasting results. The are many form of time series visualization for example, trend which show increase and decrease of data over long period of time. there's seasonal, which show where the data has been affected by factors like year or the day of the week. and last there's cycle where time series data rises or falls without a  fixed period.  below is one example of trend time series based on unemployment economic growth. 

code:
plot2 <- qplot(date, uempmed, data = economics, geom = "line")
+ grid.arrange(plot1, plot2, ncol=2)
plot1 <- qplot(unemploy/pop, uempmed, data = economics, geom = c("point", "path"))
 plot2 <- qplot(unemploy/pop, uempmed, data = economics, geom = c("point", "path"), color=year)
grid.arrange(plot1, plot2, ncol=2)
plot2