在R中从直方图得到频率值。

I know how to draw histograms or other frequency/percentage related tables. But now I want to know, how can I get those frequency values in a table to use after the fact.

我知道如何绘制直方图或其他频率/百分比相关的表。但是现在我想知道，如何在一个表格中得到这些频率值。

I have a massive dataset, now I draw a histogram with a set binwidth. I want to extract the frequency value (i.e. value on y-axis) that corresponds to each binwidth and save it somewhere.

我有一个庞大的数据集，现在我画了一个带有一个集合binwidth的直方图。我想要提取对应于每个binwidth的频率值(即y轴上的值)，并将其保存到某个地方。

Can someone please help me with this? Thank you!

有人能帮我吗?谢谢你！

3 个解决方案

#1

The hist function has a return value (an object of class histogram):

hist函数具有返回值(类直方图的对象):

R> res <- hist(rnorm(100))
R> res
$breaks
[1] -4 -3 -2 -1  0  1  2  3  4

$counts
[1]  1  2 17 27 34 16  2  1

$intensities
[1] 0.01 0.02 0.17 0.27 0.34 0.16 0.02 0.01

$density
[1] 0.01 0.02 0.17 0.27 0.34 0.16 0.02 0.01

$mids
[1] -3.5 -2.5 -1.5 -0.5  0.5  1.5  2.5  3.5

$xname
[1] "rnorm(100)"

$equidist
[1] TRUE

attr(,"class")
[1] "histogram"

#2

From ?hist: Value

从?嘘:价值

an object of class "histogram" which is a list with components:

一个类“直方图”的对象，它是一个包含组件的列表:

breaks the n+1 cell boundaries (= breaks if that was a vector). These are the nominal breaks, not with the boundary fuzz.
打破n+1细胞边界(如果这是一个向量的话)。这些是名义上的休息，而不是边界模糊。
counts n integers; for each cell, the number of x[] inside.
数n个整数;对于每个单元格，内部的x[]数。
density values f^(x[i]), as estimated density values. If all(diff(breaks) == 1), they are the relative frequencies counts/n and in general satisfy sum[i; f^(x[i]) (b[i+1]-b[i])] = 1, where b[i] = breaks[i].
密度值f ^(x[我]),作为估计的密度值。如果全部(diff(break) == 1)，它们是相对频率计数/n，总体上满足[i;f ^(x[我])(b - b(i + 1)[我]))= 1,b[我]=[我]。
intensities same as density. Deprecated, but retained for compatibility.
强度与密度相同。弃用，但为了兼容性而保留。
mids the n cell midpoints.
将n个细胞的中点。
xname a character string with the actual x argument name.
用实际的x参数名称命名一个字符串。
equidist logical, indicating if the distances between breaks are all the same.
equidist逻辑，表示中断之间的距离是相同的。

breaks and density provide just about all you need:

破碎和密度提供了你所需要的一切:

histrv<-hist(x)
histrv$breaks
histrv$density

#3

Just in case someone hits this question with ggplot's geom_histogram in mind, note that there is a way to extract the data from a ggplot object.

如果有人用ggplot的地形图来回答这个问题，请注意，有一种方法可以从ggplot对象中提取数据。

The following convenience function outputs a dataframe with the lower limit of each bin (xmin), the upper limit of each bin (xmax), the mid-point of each bin (x), as well as the frequency value (y).

下面的便利函数输出每个bin (xmin)的下限，每个bin (xmax)的上限，每个bin (x)的中点，以及频率值(y)。

## Convenience function
get_hist <- function(p) {
    d <- ggplot_build(p)$data[[1]]
    data.frame(x = d$x, xmin = d$xmin, xmax = d$xmax, y = d$y)
}

# make a dataframe for ggplot
set.seed(1)
x = runif(100, 0, 10)
y = cumsum(x)
df <- data.frame(x = sort(x), y = y)

# make geom_histogram 
p <- ggplot(data = df, aes(x = x)) + 
    geom_histogram(aes(y = cumsum(..count..)), binwidth = 1, boundary = 0,
                color = "black", fill = "white")

Illustration:

说明:

hist = get_hist(p)
head(hist$x)
## [1] 0.5 1.5 2.5 3.5 4.5 5.5
head(hist$y)
## [1]  7 13 24 38 52 57
head(hist$xmax)
## [1] 1 2 3 4 5 6
head(hist$xmin)
## [1] 0 1 2 3 4 5

A related question I answered here (Cumulative histogram with ggplot2).

我在这里回答了一个相关的问题(累积直方图和ggplot2)。

#1