R-如何拆分/组合多个变量的列
我是R方面的新手,我还没有找到一个答案,即如何将一个包含多个变量的列(示例1-4)拆分为单独的列,同时移动与之相关的数据。下面是一个例子:R-如何拆分/组合多个变量的列,r,statistics,tidyr,R,Statistics,Tidyr,我是R方面的新手,我还没有找到一个答案,即如何将一个包含多个变量的列(示例1-4)拆分为单独的列,同时移动与之相关的数据。下面是一个例子: Samples Content Sample 1 70.7 Sample 1 91.6 Sample 1 92.6 Sample 1 65.2 Sample 1 80.0 Sample 1 82.1 Sample 1 88.1 Sample 1 92.2 Sample 1 53.3 Sample
Samples Content
Sample 1 70.7
Sample 1 91.6
Sample 1 92.6
Sample 1 65.2
Sample 1 80.0
Sample 1 82.1
Sample 1 88.1
Sample 1 92.2
Sample 1 53.3
Sample 1 80.0
Sample 1 60.3
Sample 1 89.7
Sample 1 84.8
Sample 1 94.0
Sample 1 71.8
Sample 1 76.9
Sample 1 91.4
Sample 1 57.9
Sample 1 61.9
Sample 1 71.5
Sample 2 88.7
Sample 2 67.6
Sample 2 61.7
Sample 2 70.8
Sample 2 45.3
Sample 2 55.6
Sample 2 64.6
Sample 2 62.7
Sample 2 72.4
Sample 2 46.8
Sample 2 59.0
Sample 2 63.7
Sample 2 67.0
Sample 2 71.6
Sample 2 48.3
Sample 2 55.6
Sample 2 62.5
Sample 2 60.0
Sample 2 72.9
Sample 2 47.4
Sample 3 42.3
Sample 3 48.2
Sample 3 64.0
Sample 3 33.3
Sample 3 19.0
Sample 3 41.0
Sample 3 53.1
Sample 3 46.5
Sample 3 30.0
Sample 3 43.4
Sample 3 43.7
Sample 3 92.0
Sample 3 53.0
Sample 3 33.0
Sample 3 48.4
Sample 3 43.2
Sample 3 41.8
Sample 3 62.5
Sample 3 33.3
Sample 3 49.3
Sample 4 51.8
Sample 4 57.3
Sample 4 43.3
Sample 4 42.3
Sample 4 37.6
Sample 4 54.9
Sample 4 71.1
Sample 4 33.8
Sample 4 43.1
Sample 4 39.1
Sample 4 63.0
Sample 4 74.0
Sample 4 31.0
Sample 4 48.3
Sample 4 42.9
Sample 4 62.2
Sample 4 35.4
Sample 4 33.8
Sample 4 40.7
Sample 4 41.2
我试了一次,但没有成功。我希望输出是这样的
Sample 1 Sample 2 Sample 3 Sample 4
70.7 88.7 42.3 51.8
91.6 67.6 48.2 57.3
92.6 61.7 64.0 43.3
65.2 70.8 33.3 42.3
80.0 45.3 19.0 37.6
82.1 55.6 41.0 54.9
88.1 64.6 53.1 71.1
92.2 62.7 46.5 33.8
53.3 72.4 30.0 43.1
80.0 46.8 43.4 39.1
60.3 59.0 43.7 63.0
89.7 63.7 92.0 74.0
84.8 67.0 53.0 31.0
94.0 71.6 33.0 48.3
71.8 48.3 48.4 42.9
76.9 55.6 43.2 62.2
91.4 62.5 41.8 35.4
57.9 60.0 62.5 33.8
61.9 72.9 33.3 40.7
71.5 47.4 49.3 41.2
非常感谢,如果确定了一个解决方案,如果我想做回报,有没有答案
额外-是否有任何方法可以对堆叠在一列(如第一个示例)中的数据进行t检验,而无需对其进行转换?由于每个“样本”的元素数量相同,我们可以使用
从基本R
中取消堆叠
unstack(df1, Content~Samples)
# Sample.1 Sample.2 Sample.3 Sample.4
#1 70.7 88.7 42.3 51.8
#2 91.6 67.6 48.2 57.3
#3 92.6 61.7 64.0 43.3
#4 65.2 70.8 33.3 42.3
#5 80.0 45.3 19.0 37.6
#6 82.1 55.6 41.0 54.9
#7 88.1 64.6 53.1 71.1
#8 92.2 62.7 46.5 33.8
#9 53.3 72.4 30.0 43.1
#10 80.0 46.8 43.4 39.1
#11 60.3 59.0 43.7 63.0
#12 89.7 63.7 92.0 74.0
#13 84.8 67.0 53.0 31.0
#14 94.0 71.6 33.0 48.3
#15 71.8 48.3 48.4 42.9
#16 76.9 55.6 43.2 62.2
#17 91.4 62.5 41.8 35.4
#18 57.9 60.0 62.5 33.8
#19 61.9 72.9 33.3 40.7
#20 71.5 47.4 49.3 41.2
不使用外部软件包
如果“样本”元素的数量不同,则可以使用来自数据的dcast
。表
(在两种情况下都适用)
由于每个“样本”的元素数量相同,我们可以使用从基本R
unstack(df1, Content~Samples)
# Sample.1 Sample.2 Sample.3 Sample.4
#1 70.7 88.7 42.3 51.8
#2 91.6 67.6 48.2 57.3
#3 92.6 61.7 64.0 43.3
#4 65.2 70.8 33.3 42.3
#5 80.0 45.3 19.0 37.6
#6 82.1 55.6 41.0 54.9
#7 88.1 64.6 53.1 71.1
#8 92.2 62.7 46.5 33.8
#9 53.3 72.4 30.0 43.1
#10 80.0 46.8 43.4 39.1
#11 60.3 59.0 43.7 63.0
#12 89.7 63.7 92.0 74.0
#13 84.8 67.0 53.0 31.0
#14 94.0 71.6 33.0 48.3
#15 71.8 48.3 48.4 42.9
#16 76.9 55.6 43.2 62.2
#17 91.4 62.5 41.8 35.4
#18 57.9 60.0 62.5 33.8
#19 61.9 72.9 33.3 40.7
#20 71.5 47.4 49.3 41.2
不使用外部软件包
如果“样本”元素的数量不同,则可以使用来自数据的dcast
。表
(在两种情况下都适用)
使用tidyr::spread
可能会出现“重复标识符”问题。您首先需要生成Sample+标识符的唯一组合,您可以这样做(假设数据帧名为df1
):
“如果我想做回报”
你的意思是换一种方式,从宽型回到原来的长型吗?然后使用聚集
。将此添加到上述代码的末尾,然后查看发生了什么:
%>% gather(Samples, Content)
t-test:有很多方法可以对长格式数据运行t-test。例如,比较样本1和样本2的基本方法可能是:
t.test(df1[df1$Samples == "Sample 1", "Content"],
df1[df1$Samples == "Sample 2", "Content"])
使用tidyr::spread
可能会出现“重复标识符”问题。您首先需要生成Sample+标识符的唯一组合,您可以这样做(假设数据帧名为df1
):
“如果我想做回报”
你的意思是换一种方式,从宽型回到原来的长型吗?然后使用聚集
。将此添加到上述代码的末尾,然后查看发生了什么:
%>% gather(Samples, Content)
t-test:有很多方法可以对长格式数据运行t-test。例如,比较样本1和样本2的基本方法可能是:
t.test(df1[df1$Samples == "Sample 1", "Content"],
df1[df1$Samples == "Sample 2", "Content"])
do.call(cbind,split(df$Content,df$Samples)
查看tidyr::spread
或restrape2::dcast(?)
do.call(cbind,split(df$Content,df$Samples)
查看tidyr::spread
或restrape2::dcast(?)
非常感谢你们两位的帮助!)太棒了,非常感谢你们对你们两个的帮助(太棒了,非常感谢你们对你们两个的帮助很高兴在问题被关闭之前发布了这篇文章!太棒了,非常感谢你们两位的帮助!:)很高兴在问题被关闭之前发布了这篇文章!