dplry::filter()

stats::filter()

ggplot(legosets, aes(x=pieces, y=US_retailPrice, color=availability)) + geom_point()

ggplot(legosets, aes(x=pieces, y=US_retailPrice, color=availability)) + geom_point(alpha = 0.3) + theme_minimal()

ggplot(legosets, aes(x=pieces, y=US_retailPrice, color=availability)) + geom_jitter()

ggplot(legosets, aes(x = availability, y = US_retailPrice, color = availability)) + geom_point() + geom_boxplot(alpha = 0.3) + scale_y_log10() + theme(legend.position = ‘none’)

ggplot(legosets, aes(x = availability, y = US_retailPrice, color = availability)) + geom_jitter() + geom_boxplot(alpha = 0.3) + scale_y_log10() + theme(legend.position = ‘none’)

legosets2 <- legosets[complete.cases(legosets),] ggplot(legosets2, aes(x = pieces, y = US_retailPrice, color = availability)) + geom_density2d() + theme(legend.position = ‘none’)

my_formula <- y ~ m * x + b class(my_formula) all.vars(my_formula)

library(psych) tab <- describeBy(legosets\(US_retailPrice, group = legosets\)availability, mat = TRUE)[,c(‘group1’, ‘mean’)] tab names(tab) <- c(‘availability’, ‘US_retailPrice’)

ggplot(legosets, aes(x=availability, y=US_retailPrice)) + geom_boxplot() + geom_point(data = tab, color = ‘blue’) + scale_y_log10()

ggplot(legosets, aes(x = US_retailPrice)) + geom_histogram() ggplot(legosets, aes(x = US_retailPrice)) + geom_histogram(bins = 50) ggplot(legosets, aes(x = US_retailPrice)) + geom_histogram(binwidth = 25)

ggplot(legosets, aes(x = US_retailPrice, color = availability)) + geom_density() ggplot(legosets, aes(x = US_retailPrice, color = availability)) + geom_density() + scale_x_log10() ggplot(legosets, aes(x = US_retailPrice, color = availability)) + geom_density() + scale_x_log10() + facet_wrap(~ availability) + theme(legend.position = ‘none’)

ggplot(legosets, aes(x = pieces)) + geom_histogram(fill = ‘blue’)