如何为表格的每一列生成直方图?

问题描述

我有一个数据表，其中的一列代表每个研究对象(行)的实验室值.

I have a table of data with a column representing a lab value for each study subject (rows).

我想生成一系列直方图，显示每个实验室测试(即列)的值分布.理想情况下，每组实验室值都应具有不同的bin宽度(有些是整数，范围是数百，有些是数字，范围是2-3).

I want to generate a series of histograms showing the distribution of values for each lab test (i.e. column). Each set of lab values would ideally have a different bin width (some are integers with a range of hundreds, some are numeric with a range of 2-3).

我该怎么做?

推荐答案

如果结合使用tidyr和ggplot2包，则可以使用facet_wrap来快速创建数据中每个变量的直方图集.框架.

If you combine the tidyr and ggplot2 packages, you can use facet_wrap to make a quick set of histograms of each variable in your data.frame.

您需要使用tidyr::gather将数据重整为长格式，因此您将具有key和value列，例如:

You need to reshape your data to long form with tidyr::gather, so you have key and value columns like such:

library(tidyr)
library(ggplot2)
# or `library(tidyverse)`

mtcars %>% gather() %>% head()
#>   key value
#> 1 mpg  21.0
#> 2 mpg  21.0
#> 3 mpg  22.8
#> 4 mpg  21.4
#> 5 mpg  18.7
#> 6 mpg  18.1

使用此数据作为我们的数据，我们可以将value映射为x变量，并使用facet_wrap以key列分隔:

Using this as our data, we can map value as our x variable, and use facet_wrap to separate by the key column:

ggplot(gather(mtcars), aes(value)) +
    geom_histogram(bins = 10) +
    facet_wrap(~key, scales = 'free_x')

scales = 'free_x'是必需的，除非您的数据具有相似的比例.

The scales = 'free_x' is necessary unless your data is all of a similar scale.

您可以用任何能得出数字的值代替bins = 10，这可能使您可以通过一些创造力来分别设置它们.另外，您可以设置binwidth，这可能更实用，具体取决于数据的外观.无论如何，分箱都需要一些技巧.

You can replace bins = 10 with anything that evaluates to a number, which may allow you to set them somewhat individually with some creativity. Alternatively, you can set binwidth, which may be more practical, depending on what your data looks like. Regardless, binning will take some finesse.

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