ggplot2 图层

library(tidyverse)

# install.packages('wesanderson')

library(wesanderson)

# 安装

# remotes::install_github("davidsjoberg/ggstream")

library(ggstream)

# 示例数据

blockbusters

#> # A tibble: 157 x 3

#>     year genre     box_office

#>    <dbl> <chr>          <dbl>

#>  1  1977 Action         2.98 

#>  2  1977 Adventure      0.209

#>  3  1977 Comedy         0.516

#>  4  1977 Drama          2.54 

#>  5  1978 Action         1.92 

#>  6  1978 Adventure      0.760

#>  7  1978 Comedy         1.04 

#>  8  1978 Drama          0.202

#>  9  1979 Action         1.15 

#> 10  1979 Adventure      0.312

#> # … with 147 more rows

# 绘图示例

ggplot(blockbusters, aes(year, box_office, fill = genre)) +

  geom_stream() +

  scale_fill_manual(values = wes_palette("Darjeeling2"))

# 安装

# install.packages("ggridges")

library(ggridges)

ggplot(blockbusters, aes(x = box_office, y = genre, fill = genre)) +

  geom_density_ridges(scale = 4) +

  scale_fill_manual(values = wes_palette("Darjeeling2", n = 5))

# 安装

# devtools::install_github("davidsjoberg/ggsankey")

library(ggsankey)

# 准备示例数据：

mtcars %>% 

  as_tibble()

#> # A tibble: 32 x 11

#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb

#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

#>  1  21       6  160    110  3.9   2.62  16.5     0     1     4     4

#>  2  21       6  160    110  3.9   2.88  17.0     0     1     4     4

#>  3  22.8     4  108     93  3.85  2.32  18.6     1     1     4     1

#>  4  21.4     6  258    110  3.08  3.22  19.4     1     0     3     1

#>  5  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2

#>  6  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1

#>  7  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4

#>  8  24.4     4  147.    62  3.69  3.19  20       1     0     4     2

#>  9  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2

#> 10  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4

#> # … with 22 more rows

mtcars %>%

  make_long(cyl, vs, am, gear, carb) -> example_dat

example_dat %>% 

  as_tibble()

#> # A tibble: 160 x 4

#>    x      node next_x next_node

#>    <fct> <dbl> <fct>      <dbl>

#>  1 cyl       6 vs             0

#>  2 vs        0 am             1

#>  3 am        1 gear           4

#>  4 gear      4 carb           4

#>  5 carb      4 <NA>          NA

#>  6 cyl       6 vs             0

#>  7 vs        0 am             1

#>  8 am        1 gear           4

#>  9 gear      4 carb           4

#> 10 carb      4 <NA>          NA

#> # … with 150 more rows

ggplot(example_dat,

       aes(x = x, 

               next_x = next_x, 

               node = node, 

               next_node = next_node,

               fill = factor(node))) +

   geom_sankey(flow.alpha = 0.6)

# 安装

# install.packages("ggalluvial")

library(ggalluvial)

ggplot(as.data.frame(UCBAdmissions),

       aes(y = Freq, axis1 = Gender, axis2 = Dept)) +

  geom_alluvium(aes(fill = Admit), width = 1/12) +

  scale_fill_manual(values = wes_palette("Darjeeling2"))

# 安装

# devtools::install_github("davidsjoberg/ggbump")

library(ggbump)

blockbusters %>% 

  dplyr::filter(genre %in% c("Action", "Comedy", "Drama")) %>% 

  group_by(year) %>% 

  mutate(rank = rank(box_office)) -> blockbusters2

ggplot(blockbusters2, aes(year, rank, color = genre)) +

  geom_point(size = 7) +

  geom_bump() +

  scale_color_manual(values = wes_palette("Darjeeling2"))

# 安装

# install.packages("waffle", repos = "https://cinc.rud.is")

library(waffle)

ggplot(as_tibble(Titanic), aes(fill = Sex, values = n)) +

  geom_waffle(n_rows = 20, color = "white") +

  facet_wrap(~ Survived, ncol = 1)  +

  scale_fill_manual(values = wes_palette("Darjeeling2"))

# 安装

# install.packages("ggbeeswarm")

library(ggbeeswarm)

ggplot(blockbusters, aes(x = genre, y = box_office, color = genre)) + 

  geom_quasirandom() +

  scale_color_manual(values = wes_palette("Darjeeling2"))

# 安装

# devtools::install_github("haleyjeppson/ggmosaic")

library(ggmosaic)

ggplot(as.data.frame(UCBAdmissions)) +

  geom_mosaic(aes(x = product(Admit, Dept), fill = Gender, weight = Freq)) +

  scale_fill_manual(values = wes_palette("Darjeeling2")) + 

  coord_flip()