Package ‘ggpmisc’ (Miscellaneous Extensions to ‘ggplot2’) is a set of extensions to R package ‘ggplot2’ (> 2.2.1) useful when plotting diverse types of data.

Functions try_data_frame() and try_tibble() can be used to convert time series objects into data frames or tibbles suitable for plotting. To complement these functions ggplot methods for "ts" and "xts" classes are defined.

A geometry, geom_table() allows adding tables from tibble objects mapped to the label aesthetic.

Two statistics automate finding the location and labeling peaks and/or valleys.

Several statistics are provided for annotations related to model fits: fitted polynomial equations as labels, fitted equations for other model fits including non-linear ones, ANOVA tables, model summary tables, highlighting deviations from a fitted curve, and plotting residuals on-the-fly.

Statistics are provided for filtering and/or tagging data from regions of plot panels with high/low densities of observations (the stats are designed to work nicely together with package ‘ggrepel’).

Another group of ggplot statistics and geometries which echo their data input to the R console and/or plot aim at easing debugging during development of new geoms and statistics (or learning how ggplot layers work).

Please, see the web site r4photobiology for details and update notices, and the docs site. Other packages, aimed at easing photobiology-related calculations including the quantification of biologically effective radiation in meteorology are available as part of a suite described at the same website.

The current release of ‘ggpmisc’ is available through CRAN for R (>= 3.3.0).