r - ggplot2: Independent Continuous Fill for Summary Row & Column -

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i using strategy plot summary (totals) rows in heatmap using geom_tile, involves creating rows in data_frame row , column totals: 

library(dplyr) library(ggplot2)      entitites = letters[1:10] # create sample data df_foo = bind_cols(   data_frame(group1 = rep(c("a", "b"), each = 100)),   bind_rows(     expand.grid(       left = entitites, right = entitites,       stringsasfactors = false     ),     expand.grid(       left = entitites, right = entitites,       stringsasfactors = false     )   ),   data_frame(value = rpois(200, 15)) )  # create summary row & column df_foo_aug = bind_rows(   df_foo,   df_foo %>%      group_by(left, group1) %>%      summarize(       value = sum(value),       right = "total"     ),   df_foo %>%      group_by(right, group1) %>%      summarize(       value = sum(value),       left = "total"     ) )  # create plot df_foo_aug %>%    ggplot(aes(x = right, y = left, fill = value)) +    geom_tile() +    facet_wrap(~ group1) +    theme_bw()

this yields:

enter image description here

obviously, totals row/column need own fill gradient, not clear how (if) can add second continuous/gradient fill.

any other way achieve same intended outcome acceptable solution question well.

the problem here in ggplot, in principle, aesthetic can have 1 scale. fill can have 1 scale. however, there ways avoid this, example using color second scale. alternatively, mess around grobs job done, per shayaa's comment.

here possible examples, using geom_point display totals:

base_plot <-     ggplot(df_foo_aug, aes(x = right, y = left)) +    geom_tile(data = filter(df_foo_aug, right != 'total', left != 'total'),              aes(fill = value)) +   coord_equal() +   facet_wrap(~ group1) +    scale_y_discrete(limits = rev(sort(unique(df_foo_aug$left)))) +   theme_classic() + theme(strip.background = element_blank())

a standard approach:

base_plot +   geom_point(data = filter(df_foo_aug, right == 'total' | left == 'total'),               aes(col = value), size = 9.2, shape = 15) +   scale_color_gradient('total', low = 'black', high = 'red')

enter image description here

using color scales wider perceptual range:

base_plot +   geom_point(data = filter(df_foo_aug, right == 'total' | left == 'total'),              aes(col = value), size = 9.2, shape = 15) +   viridis::scale_fill_viridis(option = 'b') +   viridis::scale_color_viridis('total', option = 'd')

enter image description here

also mapping size total value:

base_plot +   geom_point(data = filter(df_foo_aug, right == 'total' | left == 'total'),               aes(col = value, size = value)) +   scale_size_area(max_size = 8, guide = 'none') +   viridis::scale_fill_viridis(option = 'b') +   viridis::scale_color_viridis('total', option = 'd')

enter image description here

personally, quite last one.

one final improvement move y-axis up, recommend cowplot package.


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