R ggplot2 geom_bar 條形圖

geom_bar(
  mapping = NULL,
  data = NULL,
  stat = "count",
  position = "stack",
  ...,
  just = 0.5,
  width = NULL,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_col(
  mapping = NULL,
  data = NULL,
  position = "stack",
  ...,
  just = 0.5,
  width = NULL,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_count(
  mapping = NULL,
  data = NULL,
  geom = "bar",
  position = "stack",
  ...,
  width = NULL,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_histogram() 用於連續數據，position_dodge() 和 position_dodge2() 用於創建並排條形圖。

stat_bin() ，它將數據存儲在範圍內並計算每個範圍內的情況。它與 stat_count() 不同，stat_count() 計算每個 x 位置的事例數量(不分檔到範圍中)。 stat_bin() 需要連續的x 數據，而stat_count() 可用於離散和連續的x 數據。

# geom_bar is designed to make it easy to create bar charts that show
# counts (or sums of weights)
g <- ggplot(mpg, aes(class))
# Number of cars in each class:
g + geom_bar()

# Total engine displacement of each class
g + geom_bar(aes(weight = displ))

# Map class to y instead to flip the orientation
ggplot(mpg) + geom_bar(aes(y = class))


# Bar charts are automatically stacked when multiple bars are placed
# at the same location. The order of the fill is designed to match
# the legend
g + geom_bar(aes(fill = drv))


# If you need to flip the order (because you've flipped the orientation)
# call position_stack() explicitly:
ggplot(mpg, aes(y = class)) +
 geom_bar(aes(fill = drv), position = position_stack(reverse = TRUE)) +
 theme(legend.position = "top")


# To show (e.g.) means, you need geom_col()
df <- data.frame(trt = c("a", "b", "c"), outcome = c(2.3, 1.9, 3.2))
ggplot(df, aes(trt, outcome)) +
  geom_col()

# But geom_point() displays exactly the same information and doesn't
# require the y-axis to touch zero.
ggplot(df, aes(trt, outcome)) +
  geom_point()


# You can also use geom_bar() with continuous data, in which case
# it will show counts at unique locations
df <- data.frame(x = rep(c(2.9, 3.1, 4.5), c(5, 10, 4)))
ggplot(df, aes(x)) + geom_bar()

# cf. a histogram of the same data
ggplot(df, aes(x)) + geom_histogram(binwidth = 0.5)


# Use `just` to control how columns are aligned with axis breaks:
df <- data.frame(x = as.Date(c("2020-01-01", "2020-02-01")), y = 1:2)
# Columns centered on the first day of the month
ggplot(df, aes(x, y)) + geom_col(just = 0.5)

# Columns begin on the first day of the month
ggplot(df, aes(x, y)) + geom_col(just = 1)