11.14 Faceted Location Scatter Plot
%>% ds ggplot(aes(x=date, y=max_temp)) + geom_point(alpha=0.05, shape=".") + geom_smooth(method="gam", formula=y~s(x, bs="cs")) + facet_wrap(~location) + theme(axis.text.x=element_text(angle=45, hjust=1)) + labs(x=vnames["date"], y=vnames["max_temp"])
Partitioning the dataset by a categoric variable reduces the blob
effect for big data. The plot uses
location as the faceted
variable to separately plot each location’s maximum temperature over
time. Notice the seasonal effect across all plots, some with quite
The plot uses ggplot2::facet_wrap() to separately plot each
location. Using ggplot2::geom_point() with alpha=
reduces the effect of overlaid points as does using smaller dots on
the plots by way of shape=. Together this works to
de-clutter the plot and improves the presentation with an emphasis on
the patterns. The x-axis tick labels are rotated \(45^\circ\) using
45 within ggplot2::element_text() to
avoid the labels overlapping. The hjust=
the labels to be right justified.
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