如何将列的值除以另一列的每个值的值
我试图在R中弄清楚如何做到这一点，但真的很感谢对此的一些投入。假设我有两个dataFrames A和b：
dataframe a
a <- c("A", "A", "A", "B", "B", "B", "C", "C", "C")
b <- c(1, 5, 10, 2, 3, 8, 10, 28, 36)
c <- c(runif(9, min=5, max=99))
df_A <- data.frame(a,b,c)
names(df_A) <- c('name', 'trial', 'counts')
name trial counts
1 A 1 42.18785
2 A 5 17.17859
3 A 10 29.34961
4 B 2 23.20101
5 B 3 58.57507
6 B 8 28.94360
7 C 10 25.48171
8 C 28 55.67896
9 C 36 10.04799
dataframe b
e <- c("A", "A", "A", "B", "C", "C")
f <- c(1, 5, 10, 2, 3, 28)
g <- c(runif(6, min=5, max=99))
df_B <- data.frame(e,f,g)
names(df_B) <- c('name', 'trial', 'rate')
name trial rate
1 A 1 8.408579
2 A 5 28.029798
3 A 10 18.904179
4 B 2 20.577880
5 C 3 44.492629
6 C 28 81.408402
如您所见，这两个dataframes共享两个列，但长度有所不同。我需要做的是将计数列中的每个值除以RATE> RATE列的每个值 dataframe b 。这必须按名称为基础完成（即，group_by name列）。此后，正确的数据框将是这样的：
name trial counts
1 A 1 42.18785 / 8.408579
2 A 1 42.18785 / 28.029798
3 A 1 42.18785 / 18.904179
4 A 5 17.17859 / 8.408579
5 A 5 17.17859 / 28.029798
6 A 5 17.17859 / 18.904179
7 A 10 29.34961 / 8.408579
8 A 10 29.34961 / 28.029798
9 A 10 29.34961 / 18.904179
10 B 2 23.20101 / 20.577880
11 B 3 58.57507 / 20.577880
12 B 8 28.94360 / 20.577880
13 C 10 25.48171 / 44.492629
14 C 10 25.48171 / 81.408402
15 C 28 55.67896 / 44.492629
16 C 36 10.04799 / 81.408402
I am trying to figure out how to do this in R but would really appreciate some input on this. Let's say I have two dataframes, A and B:
dataframe A
a <- c("A", "A", "A", "B", "B", "B", "C", "C", "C")
b <- c(1, 5, 10, 2, 3, 8, 10, 28, 36)
c <- c(runif(9, min=5, max=99))
df_A <- data.frame(a,b,c)
names(df_A) <- c('name', 'trial', 'counts')
name trial counts
1 A 1 42.18785
2 A 5 17.17859
3 A 10 29.34961
4 B 2 23.20101
5 B 3 58.57507
6 B 8 28.94360
7 C 10 25.48171
8 C 28 55.67896
9 C 36 10.04799
dataframe B
e <- c("A", "A", "A", "B", "C", "C")
f <- c(1, 5, 10, 2, 3, 28)
g <- c(runif(6, min=5, max=99))
df_B <- data.frame(e,f,g)
names(df_B) <- c('name', 'trial', 'rate')
name trial rate
1 A 1 8.408579
2 A 5 28.029798
3 A 10 18.904179
4 B 2 20.577880
5 C 3 44.492629
6 C 28 81.408402
As you can see, these two dataframes share two columns but differ in length. What I need to do is to divide each value in the counts column by each value of the rate column in dataframe B. This has to be done on a name-by-name basis (i.e., group_by name column). A correct dataframe after this will look like this:
name trial counts
1 A 1 42.18785 / 8.408579
2 A 1 42.18785 / 28.029798
3 A 1 42.18785 / 18.904179
4 A 5 17.17859 / 8.408579
5 A 5 17.17859 / 28.029798
6 A 5 17.17859 / 18.904179
7 A 10 29.34961 / 8.408579
8 A 10 29.34961 / 28.029798
9 A 10 29.34961 / 18.904179
10 B 2 23.20101 / 20.577880
11 B 3 58.57507 / 20.577880
12 B 8 28.94360 / 20.577880
13 C 10 25.48171 / 44.492629
14 C 10 25.48171 / 81.408402
15 C 28 55.67896 / 44.492629
16 C 36 10.04799 / 81.408402
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这是基本R解决方案。
合并数据集并将结果列划分为计数速率。用r 4.2.0中引入的管道完成，以避免创建工作，临时data.frame。由
Here is a base R solution.
mergethe data sets and divide the result's columnscountsbyrate. Done with a pipe, introduced in R 4.2.0, to avoid the creation of a work, temporary data.frame.Created on 2022-06-21 by the reprex package (v2.0.1)
DPLYR方法：
A dplyr approach: