## ----setup, include = FALSE--------------------------------------------------- options(rmarkdown.html_vignette.check_title = FALSE) knitr::opts_chunk$set( collapse = TRUE, comment = "#>", warning = FALSE, message = FALSE ) ## ----libraries---------------------------------------------------------------- library(brolgar) library(ggplot2) ## ----selected-sample---------------------------------------------------------- wages %>% sample_n_keys(size = 20) wages %>% sample_n_keys(size = 20) %>% ggplot(aes(x = xp, y = ln_wages, group = id)) + geom_line() ## ----show-add-n-obs----------------------------------------------------------- wages %>% add_n_obs() ## ----filter-sample------------------------------------------------------------ library(dplyr) wages %>% add_n_obs() %>% filter(n_obs >= 5) %>% sample_n_keys(size = 20) %>% ggplot(aes(x = xp, y = ln_wages, group = id)) + geom_line() ## ----facet-strata------------------------------------------------------------- set.seed(2019-07-23-1936) library(ggplot2) ggplot(wages, aes(x = xp, y = ln_wages, group = id)) + geom_line() + facet_strata() ## ----facet-strata-options----------------------------------------------------- set.seed(2019-07-23-1936) library(ggplot2) ggplot(wages, aes(x = xp, y = ln_wages, group = id)) + geom_line() + facet_strata(n_strata = 6) ## ----facet-strata-nrow-ncol--------------------------------------------------- set.seed(2019-07-23-1936) library(ggplot2) ggplot(wages, aes(x = xp, y = ln_wages, group = id)) + geom_line() + facet_strata(n_strata = 6, nrow = 3, ncol = 2) ## ----facet-sample------------------------------------------------------------- set.seed(2019-07-23-1937) ggplot(wages, aes(x = xp, y = ln_wages, group = id)) + geom_line() + facet_sample() ## ----facet-sample-n-obs------------------------------------------------------- set.seed(2019-07-23-1937) wages %>% add_n_obs() %>% filter(n_obs >= 5) %>% ggplot(aes(x = xp, y = ln_wages, group = id)) + geom_line() + facet_sample() ## ----gg-high-mono------------------------------------------------------------- library(gghighlight) wages %>% features(ln_wages, feat_monotonic) %>% left_join(wages, by = "id") %>% ggplot(aes(x = xp, y = ln_wages, group = id)) + geom_line() + gghighlight(increase) ## ----wages-key-slope---------------------------------------------------------- wages %>% key_slope(ln_wages ~ xp) ## ----wages-ts-slope----------------------------------------------------------- library(dplyr) wages_slope <- wages %>% key_slope(ln_wages ~ xp) %>% left_join(wages, by = "id") gg_wages_slope <- ggplot(wages_slope, aes(x = xp, y = ln_wages, group = id)) + geom_line() gg_wages_slope + gghighlight(.slope_xp < 0) ## ----wages-ts-slope-pos------------------------------------------------------- gg_wages_slope + gghighlight(.slope_xp > 0) ## ----wags-ts-slope-facet------------------------------------------------------ gg_wages_slope + facet_wrap(~.slope_xp > 0) ## ----strata-along------------------------------------------------------------- wages_slope <- wages %>% key_slope(ln_wages ~ xp) %>% # ensures that we keep the data as a `tsibble` left_join(x = wages, y = ., by = "id") gg_wages_slope <- ggplot(wages_slope, aes(x = xp, y = ln_wages, group = id)) + geom_line() gg_wages_slope + facet_strata(n_strata = 12, along = .slope_xp) ## ----wages-features-along----------------------------------------------------- wages_five <- wages %>% features(ln_wages, feat_five_num) %>% # ensures that we keep the data as a `tsibble` left_join(x = wages, y = ., by = "id") wages_five ## ----gg-wages-features-along-------------------------------------------------- gg_wages_five <- ggplot(wages_five, aes(x = xp, y = ln_wages, group = id)) + geom_line() gg_wages_five ## ----wages-features-min------------------------------------------------------- gg_wages_five + facet_strata(n_strata = 12, along = min) ## ----wages-features-max------------------------------------------------------- gg_wages_five + facet_strata(n_strata = 12, along = max) ## ----wages-features-med------------------------------------------------------- gg_wages_five + facet_strata(n_strata = 12, along = med)