根据另一个数据框中的值替换数据框中的行元素 [英] Replacing row elements in a dataframe based on values from another dataframe
问题描述
我对R还是很陌生，所以我希望有人可以帮助我.我的脚本之一中的输出表是下面的averagetable，它显示了三个不同群集中事件Standing的不同比例:
I'm fairly new to R so I hope somebody can help me. An output table in one of my scripts is the averagetable below showing different proportions of the event Standing in three different clusters:
> print(averagetable)
Group.1 Standing
1 cluster1 0.5642857
2 cluster2 0.7795848
3 cluster3 0.7922980
请注意，每次我运行脚本时，R可以为averagetable$Standing上的值分配不同的群集名称(cluster1，cluster2或cluster3).另一个输出可以是:
Note that R can assign different cluster names (cluster1, cluster2 or cluster3) to the values on averagetable$Standing each time I'm running the scrip. Another output can be:
> print(averagetable)
Group.1 Standing
1 cluster1 0.7795848
2 cluster2 0.5642857
3 cluster3 0.7922980
另一方面，我的脚本生成tableresults数据帧.请在下面找到一个head()示例:
On the other hand, my script produces the tableresults dataframe. Please find a head() sample below:
> head(tableresults)
ACTIVITY_X ACTIVITY_Y ACTIVITY_Z winning_cluster
1 19 21 28 cluster3
2 20 14 24 cluster3
3 34 35 49 cluster3
4 18 5 19 cluster2
5 23 27 35 cluster3
6 33 20 39 cluster3
我的问题很简单.我想根据以下三个规则来更改tableresults中的数据，从而更改winning_cluster列中的字符串:
My question is fairly simple. I would like to transform the data in tableresults changing the string in the column winning_cluster based on three rules:
1)在tableresults$wining_cluster中写入Standing，将其替换为averagetable中具有最高Standing值的群集名称.
1) Write Standing in tableresults$wining_cluster replacing it by the cluster name having the highest Standing value in averagetable.
2)在tableresults$wining_cluster中写入Moving/Feeding，将其替换为averagetable中具有第二高Standing值的群集名称.
2) Write Moving/Feeding in tableresults$wining_cluster replacing it by the cluster name having the second highest Standing value in averagetable.
3)在tableresults$wining_cluster中写入Feeding/Moving，将其替换为averagetable中具有第三高Standing值的群集名称.
3) Write Feeding/Moving in tableresults$wining_cluster replacing it by the cluster name having the third highest Standing value in averagetable.
换句话说，这是所需的输出:
In other words, this is the output desired:
> head(tableresults_output)
ACTIVITY_X ACTIVITY_Y ACTIVITY_Z winning_cluster
1 19 21 28 Standing
2 20 14 24 Standing
3 34 35 49 Standing
4 18 5 19 Moving/Feeding
5 23 27 35 Standing
6 33 20 39 Standing
请注意，具有一个基于值的层次结构组件将非常重要，该组件将根据averagetable值分配条件1)2)或3).使用以下方法无法解决此问题:
Note that it is very important to have a value-based, hierarchical component that will assign conditions 1) 2) or 3) depending on averagetable values. This is not solved by using:
averagetable$classification <- factor(x = as.character(sort(averagetable$Standing)),
labels = c('Feeding/Moving', 'Moving/Feeding','Standing'))
使用此命令，Standing将始终链接到cluster1，Moving/Feeding链接到cluster2，并且Feeding/Moving链接到cluster3，并且在重新生成averagetable时不一定是正确的.
With this command Standing will be always linked to cluster1, Moving/Feeding to cluster2 and Feeding/Moving to cluster3 and that is not necessarily true when averagetable is regenerated.
无论如何，我们将不胜感激，希望我的问题对论坛足够有趣.
Anyways, any help is appreciated and I hope my question was interesting enough for the forum.
推荐答案
这是一个刺路:
tableresults <- read.table(header=TRUE, stringsAsFactors=FALSE, text="
ACTIVITY_X ACTIVITY_Y ACTIVITY_Z winning_cluster
1 19 21 28 cluster3
2 20 14 24 cluster3
3 34 35 49 cluster3
4 18 5 19 cluster2
5 23 27 35 cluster3
6 33 20 39 cluster3")
averagetable <- read.table(header=TRUE, stringsAsFactors=FALSE, text="
Group.1 Standing
1 cluster1 0.5642857
2 cluster2 0.7795848
3 cluster3 0.7922980")
averagetable$x <- c("Standing", "Moving/Feeding", "Feeding/Moving")[ rank(-averagetable$Standing) ]
merge(tableresults, averagetable[,c(1,3)], by.x="winning_cluster", by.y="Group.1")
# winning_cluster ACTIVITY_X ACTIVITY_Y ACTIVITY_Z x
# 1 cluster2 18 5 19 Moving/Feeding
# 2 cluster3 19 21 28 Standing
# 3 cluster3 20 14 24 Standing
# 4 cluster3 34 35 49 Standing
# 5 cluster3 23 27 35 Standing
# 6 cluster3 33 20 39 Standing
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