我有两个数据框:
df1 <- data.frame(Values=c(0.01,0.05), row.names=c("X", "Y")) df1 Values X 0.01 Y 0.05 df2 <-data.frame(c(0,1,1), c(1,0,0), c(1,1,1)) colnames(df2) <- c("X","Y","Z") df2 X Y Z 1 0 1 1 2 1 0 1 3 1 0 1我希望在df2上执行横向操作,在每个列乘以列在df2中,其df1中的对应行,然后执行求和。
I wish to perform a rowwise operation on df2, where I multiply every column in df2 with its corresponding row in df1 and then perform a summation.
例如,对于df2的第1行,我想计算:
For example, for row 1 of df2, I wish to calculate:
df2 %>% rowwise %>% mutate(newVAL=(df1["X",]*df2[1,"X"])+(df1["Y",]*df2[1,"Y"])),同时排除不匹配的列(df1中的行)或具有NAs 。
while excluding columns that don't match (rows in df1) or have NAs.
df1中有几千行,df2中有数千行。
I have several thousands of rows in df1 and several thousands of rows and columns in df2.
任何帮助非常感谢!
PS。我已经在Perl中使用哈希实现了这一点,并且正在使用system()调用来在Rmarkdown文档中执行这些计算。为了保持完全可重现性,我正在尝试在R中重做。如果需要,快乐分享Perl代码。
PS. I have implemented this in Perl using hashes and was using the system() call to perform these calculations within an Rmarkdown document. In order to keep it completely reproducible, I am trying to redo it in R. Happy to share the Perl code if necessary.
谢谢。
推荐答案如果我理解正确,看起来您需要 sweep 。
If I understand correctly, it looks like you need sweep.
df3 <- sweep(df2[, rownames(df1)], 2, t(df1), '*') df3$total <- rowSums(df3)更多推荐
在一个数据帧中将行(带有行名称)乘以其他列中的匹配列名称
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