%>% ds filter(location=="Canberra") %>% ggplot(aes(x=date, y=max_temp)) + geom_point(shape=".") + geom_smooth(method="gam", formula=y~s(x, bs="cs")) + labs(x=vnames["date"], y=vnames["max_temp"])
This scatter plot of x=
max_temp shows a pattern of seasonality over
the dataset and a trend line over the period of the dataset.
The scatter plot is again created using ggplot2::geom_point().
Typical of scatter plots of big data there will be many overlaid
points. To reduce the impact the points are reduced to a small dot
An additional layer of a smooth fitted curve, using
ggplot2::geom_smooth(), is added. The dataset has many points
and so a smoothing method recommended is
"gam" which will automatically be chosen if
not specified but with a message to that effect. The formula specified
using formula= is also the default for
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