[英]Replacing each value in a vector with its rank number for a data.frame
In this hypothetical scenario, I have performed 5 different analyses on 13 chemicals, resulting in a score assigned to each chemical within each analysis. 在这个假设情景中,我对13种化学物质进行了5次不同的分析,得出每次分析中每种化学物质的分数。 I have created a table as follows:
我创建了一个表如下:
---- Analysis1 Analysis2 Analysis3 Analysis4 Analysis5 Chem_1 3.524797844 4.477695034 4.524797844 4.524797844 4.096698498 Chem_2 2.827511555 3.827511555 3.248136118 3.827511555 3.234398548 Chem_3 2.682144761 3.474646298 3.017780505 3.682144761 3.236152242 Chem_4 2.134137304 2.596921333 2.95181339 2.649076603 2.472875191 Chem_5 2.367736454 3.027814219 2.743137896 3.271122346 2.796607809 Chem_6 2.293110565 2.917318708 2.724156207 3.293110565 2.530967343 Chem_7 2.475709113 3.105794018 2.708222528 3.475709113 3.088819908 Chem_8 2.013451822 2.259454085 2.683273938 2.723554966 2.400976121 Chem_9 2.345123123 3.050074893 2.682845391 3.291851228 2.700844104 Chem_10 2.327658894 2.848729452 2.580415233 3.327658894 2.881490893 Chem_11 2.411243882 2.98131398 2.554456095 3.411243882 3.109205453 Chem_12 2.340778276 2.576860244 2.549707035 3.340778276 3.236545826 Chem_13 2.394698249 2.90682524 2.542599327 3.394698249 3.12936843
I would like to create columns corresponding to each analysis which contain the rank position for each chemical. 我想创建对应于每个分析的列,其中包含每种化学品的等级位置。 For instance, under
Analysis1
, Chem_1
would have value "1", Chem_2
would have value "2", Chem_3
would have value "4", Chem_7
would have value "4", Chem_11
would have value "5", and so on. 例如,在
Analysis1
下, Chem_1
值为“1”, Chem_2
值为“2”, Chem_3
值为“4”, Chem_7
值为“4”, Chem_11
值为“5”,依此类推。
We can use dense_rank
from dplyr
我们可以使用
dense_rank
的dplyr
library(dplyr)
df %>%
mutate_each(funs(dense_rank(-.)))
In base R
, we can do 在
base R
,我们可以做到
df[] <- lapply(-df, rank, ties.method="min")
In data.table
, we can use 在
data.table
,我们可以使用
library(data.table)
setDT(df)[, lapply(-.SD, frank, ties.method="dense")]
To avoid the copies from multiplying with -
, as @Arun mentioned in the comments 避免副本与
-
相乘,如@Arun在评论中提到的那样
lapply(.SD, frankv, order=-1L, ties.method="dense")
You can also do this in base R: 您也可以在R基础上执行此操作:
cbind("..." = df[,1], data.frame(do.call(cbind,
lapply(df[,-1], order, decreasing = T))))
... Analysis1 Analysis2 Analysis3 Analysis4 Analysis5
1 Chem_1 1 1 1 1 1
2 Chem_2 2 2 2 2 12
3 Chem_3 3 3 3 3 3
4 Chem_4 7 7 4 7 2
5 Chem_5 11 9 5 11 13
6 Chem_6 13 5 6 13 11
7 Chem_7 5 11 7 12 7
8 Chem_8 9 6 8 10 10
9 Chem_9 12 13 9 6 5
10 Chem_10 10 10 10 9 9
11 Chem_11 6 4 11 5 6
12 Chem_12 4 12 12 8 4
13 Chem_13 8 8 13 4 8
If I'm not mistaken, you want to have the column-wise rank of your table. 如果我没有弄错的话,你想拥有你的表的列级排名。 Here is my solution:
这是我的解决方案:
m=data.matrix(df) # converts data frame to matrix, convert your data to matrix accordingly
apply(m, 2, function(c) rank(c)) # increasingly
apply(m, 2, function(c) rank(-c)) # decreasingly
However, I believe you could solve it by yourself with the help of the answers to this question Get rank of matrix entries? 但是,我相信你可以借助这个问题的答案自己解决它获得矩阵条目的排名?
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