R语言ggblanket美化ggplot图
KJY
2022-05-15
参考：
https://davidhodge931.github.io/ggblanket/
# install.packages("ggblanket")library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(ggplot2)
library(ggblanket)penguins2 <- palmerpenguins::penguins %>%
tidyr::drop_na() %>%
mutate(body_mass_kg = body_mass_g / 1000)
sample_n(penguins2, 10)## # A tibble: 10 x 9
## species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
## <fct> <fct> <dbl> <dbl> <int> <int>
## 1 Adelie Biscoe 35.9 19.2 189 3800
## 2 Chinstrap Dream 43.2 16.6 187 2900
## 3 Adelie Dream 40.2 20.1 200 3975
## 4 Chinstrap Dream 50.5 19.6 201 4050
## 5 Gentoo Biscoe 50 15.9 224 5350
## 6 Chinstrap Dream 51.9 19.5 206 3950
## 7 Gentoo Biscoe 47.7 15 216 4750
## 8 Gentoo Biscoe 48.4 14.4 203 4625
## 9 Chinstrap Dream 48.5 17.5 191 3400
## 10 Adelie Dream 36 17.8 195 3450
## # … with 3 more variables: sex <fct>, year <int>, body_mass_kg <dbl>这是默认的gg histogram
penguins2 %>%
ggplot() +
geom_histogram(aes(x = body_mass_kg)) ## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
使用这个包的话就步骤更简单，然后更好看
penguins2 %>%
gg_histogram(x = body_mass_kg)## Scale for 'x' is already present. Adding another scale for 'x', which will
## replace the existing scale.## Warning: Removed 2 rows containing missing values (geom_bar).
这是默认的图
penguins2 %>%
group_by(species, sex, island) %>%
summarise(body_mass_kg = mean(body_mass_kg)) %>%
ggplot() +
geom_col(
aes(x = body_mass_kg, y = species, fill = sex),
position = "dodge"
) +
facet_wrap( ~ island) +
theme(legend.position = "bottom")## `summarise()` has grouped output by 'species', 'sex'. You can override using the `.groups` argument.
可以看得到就代码更加简单了
penguins2 %>%
group_by(species, sex, island) %>%
summarise(body_mass_kg = mean(body_mass_kg)) %>%
gg_col(
x = body_mass_kg,
y = species,
col = sex,
facet = island,
position = "dodge",
col_legend_place = "b"
)## `summarise()` has grouped output by 'species', 'sex'. You can override using the `.groups` argument.## {ggblanket} merges col and fill aesthetics into a single col aesthetic## {ggblanket} treats faceting as an aesthetic## Warning: Ignoring unknown parameters: stat
storms %>%
group_by(year) %>%
summarise(wind = mean(wind, na.rm = TRUE)) %>%
gg_line(x = year,
y = wind,
y_zero = TRUE,
title = "Storm wind speed",
subtitle = "USA average storm wind speed, 1975\u20132020",
y_title = "Wind speed (knots)",
caption = "Source: NOAA",
theme = gg_theme(y_grid = TRUE)) +
geom_point()
penguins2 %>%
gg_density(
x = body_mass_kg,
col = species,
facet = sex,
col_legend_place = "b")## {ggblanket} merges col and fill aesthetics into a single col aesthetic## {ggblanket} treats faceting as an aesthetic## Scale for 'x' is already present. Adding another scale for 'x', which will
## replace the existing scale.
penguins2 %>%
gg_smooth(
x = bill_length_mm,
y = flipper_length_mm,
col = species,
) ## {ggblanket} merges col and fill aesthetics into a single col aesthetic## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
这里有个包：‘pals’
https://cran.r-project.org/web/packages/pals/vignettes/pals_examples.html
penguins2 %>%
gg_histogram(
x = body_mass_kg,
col = species,
facet = sex,
col_legend_place = "b",
pal = pals::brewer.dark2(3))## {ggblanket} merges col and fill aesthetics into a single col aesthetic## {ggblanket} treats faceting as an aesthetic## Scale for 'x' is already present. Adding another scale for 'x', which will
## replace the existing scale.## Warning: Removed 12 rows containing missing values (geom_bar).
df <- data.frame(
trt = factor(c(1, 1, 2, 2)),
resp = c(1, 5, 3, 4),
group = factor(c(1, 2, 1, 2)),
upper = c(1.1, 5.3, 3.3, 4.2),
lower = c(0.8, 4.6, 2.4, 3.6)
)
dodger <- position_dodge(width = 0.75)
gg_blank(df, x = resp, xmin = lower, xmax = upper, y = trt, col = group) +
geom_col(position = dodger, width = 0.75, alpha = 0.9) +
geom_errorbar(position = dodger, width = 0.2, col = "#232323")## {ggblanket} merges col and fill aesthetics into a single col aesthetic
查看函数
能看到查看的函数内的功能也更简单
gg_histogram## function (data = NULL, x = NULL, y = NULL, col = NULL, facet = NULL,
## group = NULL, stat = "bin", position = "stack", pal = NULL,
## pal_na = "#7F7F7F", alpha = 0.9, size = 0.5, bins = 40, ...,
## title = NULL, subtitle = NULL, coord = ggplot2::coord_cartesian(clip = "off"),
## x_breaks = NULL, x_breaks_n = NULL, x_breaks_width = NULL,
## x_expand = NULL, x_labels = NULL, x_limits = NULL, x_oob = scales::oob_censor,
## x_title = NULL, x_zero = NULL, x_zero_mid = FALSE, y_breaks = NULL,
## y_breaks_n = NULL, y_breaks_width = NULL, y_expand = NULL,
## y_labels = NULL, y_limits = NULL, y_oob = scales::oob_censor,
## y_title = NULL, y_zero = NULL, y_zero_mid = FALSE, col_breaks = NULL,
## col_breaks_n = NULL, col_breaks_width = NULL, col_intervals = NULL,
## col_labels = NULL, col_legend_place = NULL, col_legend_ncol = NULL,
## col_legend_nrow = NULL, col_limits = NULL, col_title = NULL,
## facet_intervals = NULL, facet_labels = snakecase::to_sentence_case,
## facet_ncol = NULL, facet_nrow = NULL, facet_scales = "fixed",
## caption = NULL, theme = NULL)
## {
## x <- rlang::enquo(x)
## y <- rlang::enquo(y)
## col <- rlang::enquo(col)
## facet <- rlang::enquo(facet)
## group <- rlang::enquo(group)
## if (rlang::is_null(data))
## rlang::abort("data is required")
## if (!rlang::quo_is_null(col))
## rlang::inform(c(i = "{ggblanket} merges col and fill aesthetics into a single col aesthetic"))
## if (!rlang::quo_is_null(facet))
## rlang::inform(c(i = "{ggblanket} treats faceting as an aesthetic"))
## data <- dplyr::ungroup(data)
## if (rlang::quo_is_null(x)) {
## if (rlang::is_null(x_title)) {
## if (stat %in% c("bin", "count"))
## x_title <- "Count"
## }
## }
## else if (rlang::is_null(x_title))
## x_title <- snakecase::to_sentence_case(rlang::as_name(x))
## if (rlang::quo_is_null(y)) {
## if (rlang::is_null(y_title)) {
## if (stat %in% c("bin", "count"))
## y_title <- "Count"
## }
## }
## else if (rlang::is_null(y_title))
## y_title <- snakecase::to_sentence_case(rlang::as_name(y))
## if (rlang::is_null(theme)) {
## x_grid <- ifelse(is.numeric(rlang::eval_tidy(x, data)) |
## lubridate::is.Date(rlang::eval_tidy(x, data)) | rlang::quo_is_null(x),
## TRUE, FALSE)
## y_grid <- ifelse(is.numeric(rlang::eval_tidy(y, data)) |
## lubridate::is.Date(rlang::eval_tidy(y, data)) | rlang::quo_is_null(y),
## TRUE, FALSE)
## theme <- gg_theme(x_grid = x_grid, y_grid = y_grid)
## }
## if (rlang::is_null(x_zero))
## x_zero <- FALSE
## if (rlang::is_null(y_zero))
## y_zero <- FALSE
## if (!rlang::quo_is_null(x)) {
## if (is.logical(rlang::eval_tidy(x, data))) {
## data <- data %>% dplyr::mutate(dplyr::across(!!x,
## ~factor(.x, levels = c("TRUE", "FALSE"))))
## }
## }
## if (!rlang::quo_is_null(y)) {
## if (is.logical(rlang::eval_tidy(y, data))) {
## data <- data %>% dplyr::mutate(dplyr::across(!!y,
## ~factor(.x, levels = c("TRUE", "FALSE"))))
## }
## if (is.character(rlang::eval_tidy(y, data)) | is.factor(rlang::eval_tidy(y,
## data))) {
## if (!rlang::quo_is_null(col) & (identical(rlang::eval_tidy(y,
## data), rlang::eval_tidy(col, data)))) {
## }
## else {
## data <- data %>% dplyr::mutate(dplyr::across(!!y,
## ~forcats::fct_rev(.x)))
## }
## }
## }
## if (!rlang::quo_is_null(col)) {
## if (is.logical(rlang::eval_tidy(col, data))) {
## data <- data %>% dplyr::mutate(dplyr::across(!!col,
## ~factor(.x, levels = c("TRUE", "FALSE"))))
## }
## if (is.factor(rlang::eval_tidy(col, data)) | is.character(rlang::eval_tidy(col,
## data))) {
## if (is.factor(rlang::eval_tidy(y, data)) | is.character(rlang::eval_tidy(y,
## data))) {
## data <- data %>% dplyr::mutate(dplyr::across(!!col,
## ~forcats::fct_rev(.x)))
## }
## }
## }
## if (!rlang::quo_is_null(facet)) {
## if (is.logical(class(rlang::eval_tidy(facet, data)))) {
## data <- data %>% dplyr::mutate(dplyr::across(!!facet,
## ~factor(.x, levels = c("TRUE", "FALSE"))))
## }
## if (!rlang::is_null(facet_intervals)) {
## data <- data %>% dplyr::mutate(dplyr::across(!!facet,
## facet_intervals))
## }
## }
## if (rlang::quo_is_null(col)) {
## if (rlang::is_null(pal))
## pal <- pal_viridis_mix(1)
## else pal <- pal[1]
## col_scale <- ggplot2::scale_colour_manual(values = pal,
## na.value = pal_na, aesthetics = c("col", "fill"))
## col_legend_place <- "n"
## }
## else {
## if (rlang::is_null(col_title))
## col_title <- snakecase::to_sentence_case(rlang::as_name(col))
## col_title_position <- ifelse(col_title == "", "right",
## "top")
## if (rlang::is_null(col_legend_place)) {
## if (!rlang::quo_is_null(x) & (identical(rlang::eval_tidy(col,
## data), rlang::eval_tidy(x, data)))) {
## col_legend_place <- "n"
## }
## else if (!rlang::quo_is_null(y) & (identical(rlang::eval_tidy(col,
## data), rlang::eval_tidy(y, data)))) {
## col_legend_place <- "n"
## }
## else if (!rlang::quo_is_null(facet) & (identical(rlang::eval_tidy(col,
## data), rlang::eval_tidy(facet, data)))) {
## col_legend_place <- "n"
## }
## else col_legend_place <- "r"
## }
## if (is.numeric(rlang::eval_tidy(col, data))) {
## if (rlang::is_null(col_intervals)) {
## if (rlang::is_null(col_breaks)) {
## col_vctr <- dplyr::pull(data, !!col)
## col_min_max <- c(min(col_vctr, na.rm = TRUE),
## max(col_vctr, na.rm = TRUE))
## if (!rlang::is_null(col_limits))
## col_min_max <- col_limits
## if (!rlang::is_null(col_breaks_width)) {
## col_breaks <- scales::fullseq(col_min_max,
## size = col_breaks_width)
## }
## else {
## if (rlang::is_null(col_breaks_n)) {
## if (col_legend_place %in% c("b", "t"))
## col_breaks_n <- 3
## else col_breaks_n <- 4
## }
## col_breaks <- pretty(col_min_max, n = col_breaks_n)
## }
## }
## if (rlang::is_null(pal))
## pal <- viridis::viridis(100)
## if (rlang::is_null(col_labels))
## col_labels <- scales::label_comma()
## col_scale <- ggplot2::scale_colour_gradientn(colors = pal,
## labels = col_labels, breaks = col_breaks, limits = col_limits,
## na.value = pal_na, name = col_title, aesthetics = c("col",
## "fill"), guide = ggplot2::guide_colorbar(title.position = col_title_position))
## }
## else {
## data <- data %>% dplyr::mutate(dplyr::across(!!col,
## col_intervals))
## col_levels <- levels(rlang::eval_tidy(col, data))
## col_n <- length(col_levels)
## if (rlang::is_null(pal))
## pal <- pal_viridis_mix(col_n)
## else pal <- pal[1:col_n]
## if (is.numeric(rlang::eval_tidy(y, data)) | lubridate::is.Date(rlang::eval_tidy(y,
## data))) {
## if (col_legend_place %in% c("b", "t"))
## col_legend_rev <- FALSE
## else col_legend_rev <- TRUE
## }
## else if (is.factor(rlang::eval_tidy(y, data)) |
## is.character(rlang::eval_tidy(y, data))) {
## if (col_legend_place %in% c("b", "t"))
## col_legend_rev <- TRUE
## else col_legend_rev <- FALSE
## pal <- rev(pal)
## }
## else col_legend_rev <- FALSE
## if (rlang::is_null(col_breaks))
## col_breaks <- ggplot2::waiver()
## if (rlang::is_null(col_labels))
## col_labels <- ggplot2::waiver()
## col_scale <- ggplot2::scale_colour_manual(values = pal,
## breaks = col_levels, limits = col_levels, labels = col_labels,
## na.value = pal_na, name = col_title, aesthetics = c("col",
## "fill"), guide = ggplot2::guide_legend(reverse = col_legend_rev,
## title.position = col_title_position, ncol = col_legend_ncol,
## nrow = col_legend_nrow, byrow = TRUE))
## }
## }
## else {
## if (!rlang::is_null(col_limits))
## col_n <- length(col_limits)
## else if (!rlang::is_null(col_breaks))
## col_n <- length(col_breaks)
## else {
## if (is.factor(rlang::eval_tidy(col, data))) {
## col_n <- length(levels(rlang::eval_tidy(col,
## data)))
## }
## else col_n <- length(unique(rlang::eval_tidy(col,
## data)))
## }
## if (rlang::is_null(pal))
## pal <- pal_d3_mix(col_n)
## else pal <- pal[1:col_n]
## if (is.numeric(rlang::eval_tidy(y, data)) | lubridate::is.Date(rlang::eval_tidy(y,
## data))) {
## if (is.factor(rlang::eval_tidy(col, data)) |
## is.character(rlang::eval_tidy(col, data))) {
## col_legend_rev <- FALSE
## }
## else if (col_legend_place %in% c("b", "t"))
## col_legend_rev <- FALSE
## else col_legend_rev <- TRUE
## }
## else if (is.factor(rlang::eval_tidy(y, data)) | is.character(rlang::eval_tidy(y,
## data))) {
## if (is.factor(rlang::eval_tidy(col, data)) |
## is.character(rlang::eval_tidy(col, data))) {
## col_legend_rev <- TRUE
## }
## else if (col_legend_place %in% c("b", "t"))
## col_legend_rev <- TRUE
## else col_legend_rev <- FALSE
## pal <- rev(pal)
## }
## else col_legend_rev <- FALSE
## if (rlang::is_null(col_breaks))
## col_breaks <- ggplot2::waiver()
## if (rlang::is_null(col_labels))
## col_labels <- snakecase::to_sentence_case
## col_scale <- ggplot2::scale_colour_manual(values = pal,
## breaks = col_breaks, limits = col_limits, labels = col_labels,
## na.value = pal_na, name = col_title, aesthetics = c("col",
## "fill"), guide = ggplot2::guide_legend(reverse = col_legend_rev,
## title.position = col_title_position, ncol = col_legend_ncol,
## nrow = col_legend_nrow, byrow = TRUE))
## }
## }
## if (!rlang::quo_is_null(x) & !rlang::quo_is_null(y)) {
## if (!rlang::quo_is_null(col)) {
## plot <- data %>% ggplot2::ggplot(mapping = ggplot2::aes(x = !!x,
## y = !!y, col = !!col, fill = !!col, group = !!group))
## }
## else if (rlang::quo_is_null(col)) {
## plot <- data %>% ggplot2::ggplot(mapping = ggplot2::aes(x = !!x,
## y = !!y, col = "", fill = "", group = !!group))
## }
## }
## else if (!rlang::quo_is_null(x) & rlang::quo_is_null(y)) {
## if (!rlang::quo_is_null(col)) {
## plot <- data %>% ggplot2::ggplot(mapping = ggplot2::aes(x = !!x,
## col = !!col, fill = !!col, group = !!group))
## }
## else if (rlang::quo_is_null(col)) {
## plot <- data %>% ggplot2::ggplot(mapping = ggplot2::aes(x = !!x,
## col = "", fill = "", group = !!group))
## }
## }
## else if (rlang::quo_is_null(x) & !rlang::quo_is_null(y)) {
## if (!rlang::quo_is_null(col)) {
## plot <- data %>% ggplot2::ggplot(mapping = ggplot2::aes(y = !!y,
## col = !!col, fill = !!col, group = !!group))
## }
## else if (rlang::quo_is_null(col)) {
## plot <- data %>% ggplot2::ggplot(mapping = ggplot2::aes(y = !!y,
## col = "", fill = "", group = !!group))
## }
## }
## else if (rlang::quo_is_null(x) & rlang::quo_is_null(y)) {
## if (!rlang::quo_is_null(col)) {
## plot <- data %>% ggplot2::ggplot(mapping = ggplot2::aes(col = !!col,
## fill = !!col, group = !!group))
## }
## else if (rlang::quo_is_null(col)) {
## plot <- data %>% ggplot2::ggplot(mapping = ggplot2::aes(col = "",
## fill = "", group = !!group))
## }
## }
## plot <- plot + ggplot2::geom_histogram(stat = stat, position = position,
## alpha = alpha, size = size, bins = bins, ...)
## if (!rlang::quo_is_null(facet)) {
## if (!rlang::is_null(facet_intervals)) {
## plot <- plot + ggplot2::facet_wrap(ggplot2::vars(!!facet),
## scales = facet_scales, ncol = facet_ncol, nrow = facet_nrow)
## }
## else {
## plot <- plot + ggplot2::facet_wrap(ggplot2::vars(!!facet),
## labeller = ggplot2::as_labeller(facet_labels),
## scales = facet_scales, ncol = facet_ncol, nrow = facet_nrow)
## }
## }
## if (!rlang::quo_is_null(x) & rlang::quo_is_null(y)) {
## if (is.character(rlang::eval_tidy(x, data)) | is.factor(rlang::eval_tidy(x,
## data))) {
## if (rlang::is_null(x_expand))
## x_expand <- ggplot2::waiver()
## if (rlang::is_null(x_labels))
## x_labels <- snakecase::to_sentence_case
## x_scale <- ggplot2::scale_x_discrete(expand = x_expand,
## labels = x_labels)
## }
## else {
## if (facet_scales %in% c("fixed", "free_y")) {
## x_vctr <- dplyr::pull(data, !!x)
## x_min <- min(x_vctr, na.rm = TRUE)
## x_max <- max(x_vctr, na.rm = TRUE)
## if (rlang::is_null(x_breaks)) {
## x_min_max <- c(x_min, x_max)
## if (x_zero)
## x_min_max <- c(0, x_min_max)
## if (x_zero_mid)
## x_min_max <- c(-x_min_max, x_min_max)
## if (!rlang::is_null(x_limits) & !any(is.na(x_limits)))
## x_min_max <- x_limits
## if (!rlang::is_null(x_breaks_width)) {
## x_breaks <- scales::fullseq(x_min_max, size = x_breaks_width)
## }
## else {
## if (rlang::is_null(x_breaks_n)) {
## x_breaks_n <- ifelse(rlang::quo_is_null(facet),
## 5, 3)
## }
## x_breaks <- pretty(x_min_max, n = x_breaks_n)
## }
## }
## if (rlang::is_null(x_limits))
## x_limits <- c(min(x_breaks), max(x_breaks))
## if (rlang::is_null(x_expand))
## x_expand <- c(0, 0)
## }
## else if (facet_scales %in% c("free", "free_x")) {
## if (rlang::is_null(x_breaks))
## x_breaks <- ggplot2::waiver()
## x_limits <- NULL
## if (rlang::is_null(x_expand))
## x_expand <- ggplot2::waiver()
## }
## if (rlang::is_null(x_labels)) {
## if (is.numeric(rlang::eval_tidy(x, data)) | rlang::quo_is_null(x))
## x_labels <- scales::label_comma()
## else if (lubridate::is.Date(rlang::eval_tidy(x,
## data)))
## x_labels <- scales::label_date_short()
## else x_labels <- ggplot2::waiver()
## }
## if (is.numeric(rlang::eval_tidy(x, data)) | rlang::quo_is_null(x)) {
## x_scale <- ggplot2::scale_x_continuous(breaks = x_breaks,
## limits = x_limits, expand = x_expand, labels = x_labels,
## oob = x_oob)
## }
## else if (lubridate::is.Date(rlang::eval_tidy(x, data))) {
## x_scale <- ggplot2::scale_x_date(breaks = x_breaks,
## limits = x_limits, expand = x_expand, labels = x_labels,
## oob = x_oob)
## }
## }
## plot <- plot + x_scale
## }
## if (!rlang::quo_is_null(y) & rlang::quo_is_null(x)) {
## if (is.character(rlang::eval_tidy(y, data)) | is.factor(rlang::eval_tidy(y,
## data))) {
## if (rlang::is_null(y_expand))
## y_expand <- ggplot2::waiver()
## if (rlang::is_null(y_labels))
## y_labels <- snakecase::to_sentence_case
## y_scale <- ggplot2::scale_y_discrete(expand = y_expand,
## labels = y_labels)
## }
## else {
## if (facet_scales %in% c("fixed", "free_x")) {
## y_vctr <- dplyr::pull(data, !!y)
## y_min <- min(y_vctr, na.rm = TRUE)
## y_max <- max(y_vctr, na.rm = TRUE)
## if (rlang::is_null(y_breaks)) {
## y_min_max <- c(y_min, y_max)
## if (y_zero)
## y_min_max <- c(0, y_min_max)
## if (y_zero_mid)
## y_min_max <- c(-y_min_max, y_min_max)
## if (!rlang::is_null(y_limits) & !any(is.na(y_limits)))
## y_min_max <- y_limits
## if (!rlang::is_null(y_breaks_width)) {
## y_breaks <- scales::fullseq(y_min_max, size = y_breaks_width)
## }
## else {
## if (rlang::is_null(y_breaks_n)) {
## y_breaks_n <- ifelse(rlang::quo_is_null(facet),
## 5, 4)
## }
## y_breaks <- pretty(y_min_max, n = y_breaks_n)
## }
## }
## if (rlang::is_null(y_limits))
## y_limits <- c(min(y_breaks), max(y_breaks))
## if (rlang::is_null(y_expand))
## y_expand <- c(0, 0)
## }
## else if (facet_scales %in% c("free", "free_y")) {
## if (rlang::is_null(y_breaks))
## y_breaks <- ggplot2::waiver()
## y_limits <- NULL
## if (rlang::is_null(y_expand))
## y_expand <- ggplot2::waiver()
## }
## if (rlang::is_null(y_labels)) {
## if (is.numeric(rlang::eval_tidy(y, data)) | rlang::quo_is_null(y))
## y_labels <- scales::label_comma()
## else if (lubridate::is.Date(rlang::eval_tidy(y,
## data)))
## y_labels <- scales::label_date_short()
## else y_labels <- ggplot2::waiver()
## }
## if (is.numeric(rlang::eval_tidy(y, data)) | rlang::quo_is_null(y)) {
## y_scale <- ggplot2::scale_y_continuous(breaks = y_breaks,
## limits = y_limits, expand = y_expand, labels = y_labels,
## oob = y_oob)
## }
## else if (lubridate::is.Date(rlang::eval_tidy(y, data))) {
## y_scale <- ggplot2::scale_y_date(breaks = y_breaks,
## limits = y_limits, expand = y_expand, labels = y_labels,
## oob = y_oob)
## }
## }
## plot <- plot + y_scale
## }
## layer_data <- ggplot2::layer_data(plot)
## if (is.character(rlang::eval_tidy(x, data)) | is.factor(rlang::eval_tidy(x,
## data))) {
## if (rlang::is_null(x_expand))
## x_expand <- ggplot2::waiver()
## if (rlang::is_null(x_labels))
## x_labels <- snakecase::to_sentence_case
## x_scale <- ggplot2::scale_x_discrete(expand = x_expand,
## labels = x_labels)
## }
## else {
## if (facet_scales %in% c("fixed", "free_y")) {
## x_vctr <- layer_data %>% dplyr::select(tidyselect::matches(stringr::regex("^x$|^xmin$|^xmax$|^xend$|^xmax_final$"))) %>%
## tidyr::pivot_longer(cols = tidyselect::everything()) %>%
## dplyr::pull(.data$value)
## if (lubridate::is.Date(rlang::eval_tidy(x, data))) {
## x_vctr <- as.Date(x_vctr, origin = "1970-01-01")
## }
## x_min <- min(x_vctr, na.rm = TRUE)
## x_max <- max(x_vctr, na.rm = TRUE)
## if (rlang::is_null(x_breaks)) {
## x_min_max <- c(x_min, x_max)
## if (x_zero)
## x_min_max <- c(0, x_min_max)
## if (x_zero_mid)
## x_min_max <- c(-x_min_max, x_min_max)
## if (!rlang::is_null(x_breaks_width)) {
## x_breaks <- scales::fullseq(x_min_max, size = x_breaks_width)
## }
## else {
## if (rlang::is_null(x_breaks_n)) {
## x_breaks_n <- ifelse(rlang::quo_is_null(facet),
## 5, 3)
## }
## x_breaks <- pretty(x_min_max, n = x_breaks_n)
## }
## }
## if (length(class(position)) == 1) {
## if (position == "fill")
## x_limits <- c(NA, NA)
## }
## else if (class(position)[1] == "PositionFill") {
## x_limits <- c(NA, NA)
## }
## if (rlang::is_null(x_limits))
## x_limits <- c(min(x_breaks), max(x_breaks))
## if (rlang::is_null(x_expand))
## x_expand <- c(0, 0)
## }
## else if (facet_scales %in% c("free", "free_x")) {
## if (rlang::is_null(x_breaks))
## x_breaks <- ggplot2::waiver()
## x_limits <- NULL
## if (rlang::is_null(x_expand))
## x_expand <- ggplot2::waiver()
## }
## if (rlang::is_null(x_labels)) {
## if (is.numeric(rlang::eval_tidy(x, data)) | rlang::quo_is_null(x))
## x_labels <- scales::label_comma()
## else if (lubridate::is.Date(rlang::eval_tidy(x, data)))
## x_labels <- scales::label_date_short()
## else x_labels <- ggplot2::waiver()
## }
## if (is.numeric(rlang::eval_tidy(x, data)) | rlang::quo_is_null(x)) {
## x_scale <- ggplot2::scale_x_continuous(breaks = x_breaks,
## limits = x_limits, expand = x_expand, labels = x_labels,
## oob = x_oob)
## }
## else if (lubridate::is.Date(rlang::eval_tidy(x, data))) {
## x_scale <- ggplot2::scale_x_date(breaks = x_breaks,
## limits = x_limits, expand = x_expand, labels = x_labels,
## oob = x_oob)
## }
## }
## plot <- plot + x_scale
## if (is.character(rlang::eval_tidy(y, data)) | is.factor(rlang::eval_tidy(y,
## data))) {
## if (rlang::is_null(y_expand))
## y_expand <- ggplot2::waiver()
## if (rlang::is_null(y_labels))
## y_labels <- snakecase::to_sentence_case
## y_scale <- ggplot2::scale_y_discrete(expand = y_expand,
## labels = y_labels)
## }
## else {
## if (facet_scales %in% c("fixed", "free_x")) {
## y_vctr <- layer_data %>% dplyr::select(tidyselect::matches(stringr::regex("^y$|^ymin$|^ymax$|^yend$|^ymax_final$"))) %>%
## tidyr::pivot_longer(cols = tidyselect::everything()) %>%
## dplyr::pull(.data$value)
## if (lubridate::is.Date(rlang::eval_tidy(y, data))) {
## y_vctr <- as.Date(y_vctr, origin = "1970-01-01")
## }
## y_min <- min(y_vctr, na.rm = TRUE)
## y_max <- max(y_vctr, na.rm = TRUE)
## if (rlang::is_null(y_breaks)) {
## y_min_max <- c(y_min, y_max)
## if (y_zero)
## y_min_max <- c(0, y_min_max)
## if (y_zero_mid)
## y_min_max <- c(-y_min_max, y_min_max)
## if (!rlang::is_null(y_limits) & !any(is.na(y_limits)))
## y_min_max <- y_limits
## if (!rlang::is_null(y_breaks_width)) {
## y_breaks <- scales::fullseq(y_min_max, size = y_breaks_width)
## }
## else {
## if (rlang::is_null(y_breaks_n)) {
## y_breaks_n <- ifelse(rlang::quo_is_null(facet),
## 5, 4)
## }
## y_breaks <- pretty(y_min_max, n = y_breaks_n)
## }
## }
## if (length(class(position)) == 1) {
## if (position == "fill")
## y_limits <- c(NA, NA)
## }
## else if (class(position)[1] == "PositionFill") {
## y_limits <- c(NA, NA)
## }
## if (rlang::is_null(y_limits))
## y_limits <- c(min(y_breaks), max(y_breaks))
## if (rlang::is_null(y_expand))
## y_expand <- c(0, 0)
## }
## else if (facet_scales %in% c("free", "free_y")) {
## if (rlang::is_null(y_breaks))
## y_breaks <- ggplot2::waiver()
## y_limits <- NULL
## if (rlang::is_null(y_expand))
## y_expand <- ggplot2::waiver()
## }
## if (rlang::is_null(y_labels)) {
## if (is.numeric(rlang::eval_tidy(y, data)) | rlang::quo_is_null(y))
## y_labels <- scales::label_comma()
## else if (lubridate::is.Date(rlang::eval_tidy(y, data)))
## y_labels <- scales::label_date_short()
## else y_labels <- ggplot2::waiver()
## }
## if (is.numeric(rlang::eval_tidy(y, data)) | rlang::quo_is_null(y)) {
## y_scale <- ggplot2::scale_y_continuous(breaks = y_breaks,
## limits = y_limits, expand = y_expand, labels = y_labels,
## oob = y_oob)
## }
## else if (lubridate::is.Date(rlang::eval_tidy(y, data))) {
## y_scale <- ggplot2::scale_y_date(breaks = y_breaks,
## limits = y_limits, expand = y_expand, labels = y_labels,
## oob = y_oob)
## }
## }
## plot <- plot + y_scale
## plot <- plot + col_scale + coord + ggplot2::labs(title = title,
## subtitle = subtitle, x = x_title, y = y_title, caption = caption) +
## theme
## if (col_legend_place == "b") {
## plot <- plot + ggplot2::theme(legend.direction = "horizontal") +
## ggplot2::theme(legend.position = "bottom")
## }
## else if (col_legend_place == "t") {
## plot <- plot + ggplot2::theme(legend.direction = "horizontal") +
## ggplot2::theme(legend.position = "top")
## }
## else if (col_legend_place == "n" | rlang::quo_is_null(col)) {
## plot <- plot + ggplot2::theme(legend.position = "none")
## }
## else if (col_legend_place == "l") {
## plot <- plot + ggplot2::theme(legend.position = "left")
## }
## return(plot)
## }
## <bytecode: 0x7fea0e508848>
## <environment: namespace:ggblanket>这样的就很不清楚
geom_col## function (mapping = NULL, data = NULL, position = "stack", ...,
## width = NULL, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)
## {
## layer(data = data, mapping = mapping, stat = "identity",
## geom = GeomCol, position = position, show.legend = show.legend,
## inherit.aes = inherit.aes, params = list(width = width,
## na.rm = na.rm, ...))
## }
## <bytecode: 0x7fea11bcfd28>
## <environment: namespace:ggplot2>最后一次修改于 2022-05-15