# Seasonal Dot Plot Plot average/min/max seasonal values faceted by season ```r seasonal_dot(swmpr_in, ...) ## S3 method for class 'swmpr' seasonal_dot( swmpr_in, param = NULL, lm_trend = FALSE, lm_lab = FALSE, free_y = FALSE, log_trans = FALSE, converted = FALSE, plot_title = FALSE, plot = TRUE, ... ) ``` ## Arguments - `swmpr_in`: input swmpr object - `...`: additional arguments passed to other methods. See `assign_season` - `param`: chr string of variable to plot - `lm_trend`: logical, add linear trend line? - `lm_lab`: logical, add significance label? Statistically significant results will appear in bold. - `free_y`: logical, should the y-axis be free? Defaults to `FALSE`. If `FALSE`, defaults to zero, unless negative values are present. If `TRUE`, y-axis limits are selected by `ggplot` - `log_trans`: logical, should y-axis be log? Defaults to `FALSE` - `converted`: logical, were the units converted from the original units used by CDMO? Defaults to `FALSE`. See `y_labeler` for details. - `plot_title`: logical, should the station name be included as the plot title? Defaults to `FALSE` - `plot`: logical, should a plot be returned? Defaults to `TRUE` ## Returns Returns a `ggplot` object ## Details This function summarizes minimum, mean, and maximum values calculated on a seasonal basis to allow for easier intra-season comparisons over time. `lm_trend = TRUE` adds a linear regression to the plot, and `lm_lab = TRUE` will add p-values from the linear regression to the plot. If the p-values are significant (p < 0.05) then the text will appear in bold. `lm_lab` text is color coded to match with the corresponding dots. ## Examples ```r dat_wq <- elksmwq #dat_wq <- subset(dat_wq, subset = c('2010-01-01 0:00', '2017-01-01 0:00')) dat_wq <- qaqc(dat_wq, qaqc_keep = c(0, 3, 5)) x <- seasonal_dot(dat_wq, param = 'do_mgl' , lm_trend = TRUE , lm_lab = TRUE , plot_title = TRUE) y <- seasonal_dot(dat_wq, param = 'do_mgl' , lm_trend = FALSE , lm_lab = FALSE , plot_title = TRUE) z <- seasonal_dot(dat_wq, param = 'do_mgl' , lm_trend = TRUE , lm_lab = FALSE , plot_title = TRUE) dat_nut <- elknmnut dat_nut <- subset(dat_nut, subset = c('2007-01-01 0:00', '2017-01-01 0:00')) dat_nut <- qaqc(dat_nut, qaqc_keep = c(0, 3, 5)) x1 <- seasonal_dot(dat_nut , param = 'chla_n' , season_grps = list(c(1,2,3), c(4,5,6), c(7,8,9), c(10, 11, 12)) , season_names = c('Winter', 'Spring', 'Summer', 'Fall') , season_start = 'Spring' , lm_trend = FALSE , lm_lab = FALSE , plot_title = TRUE) y1 <- seasonal_dot(dat_nut, param = 'chla_n' , lm_trend = TRUE , lm_lab = FALSE , plot_title = TRUE) z1 <- seasonal_dot(dat_nut, param = 'chla_n' , lm_trend = TRUE , lm_lab = TRUE , plot_title = TRUE) ``` ## See Also `ggplot`, `assign_season`, `y_labeler` ## Author(s) Julie Padilla, Dave Eslinger

seasonal_dot function