Compute empirical cumulative distribution — stat_ecdf
The empirical cumulative distribution function (ECDF) provides an alternative visualisation of distribution. Compared to other visualisations that rely on density (like geom_histogram()), the ECDF doesn't require any tuning parameters and handles both continuous and categorical variables. The downside is that it requires more training to accurately interpret, and the underlying visual tasks are so
Function reference
A layer combines data, aesthetic mapping, a geom (geometric object), a stat (statistical transformation), and a position adjustment. Typically, you will create layers using a geom_ function, overriding the default position and stat if needed. layer_geoms Layer geometry display geom_abline() geom_hline() geom_vline() Reference lines: horizontal, vertical, and diagonal geom_bar() geom_col() stat_cou
element_text. ggplot2 0.9.2.1
Usage element_text ( family = NULL , face = NULL , colour = NULL , size = NULL , hjust = NULL , vjust = NULL , angle = NULL , lineheight = NULL , color = NULL ) Arguments family font family face font face ("plain", "italic", "bold", "bold.italic") colour text colour size text size (in pts) hjust horizontal justification (in [0, 1]) vjust vertical justification (in [0, 1]) angle angle (in [0, 360])
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