按因子对数据排序并输出到矩阵（或df）R中

Question

I have looked through other posts and I think I have an idea of what I could do, but I want to be clear!

I have a very large data frame that contains 4 variables and a number of rows.

  Chain ResId ResNum    Energy
1     C   O17    500 -37.03670
2     A   ARG      8  -0.84560
3     A   LEU     24  -0.56739
4     A   ASP     25  -0.98583
5     B   ARG      8  -0.64880
6     B   LEU     24  -0.58380
7     B   ASP     25  -0.85930

Each row contains CHAIN (A, B, or C), ResID, ResNum, and Energy. I would like to sort this data so that all of the energy values belonging to a specific Resid and num in each chain are clustered together. By cluster I mean all of the values for "ARG 8" are grouped or all of the rows containing "ARG 8" are grouped. I don't know which is more efficient. Ideally, I would like the output for all residues to be

ARG 8
0.000
0.000
0.000

where the "0.000" are the energy values for ARG 8 or O17 and so on.

Sorry for the header breaks, I wanted the data to be clean, but I can't insert images.

data

structure(list(Chain = structure(c(3L, 1L, 1L, 1L, 2L, 2L, 2L
), .Label = c("A", "B", "C"), class = "factor"), ResId = structure(c(4L, 
1L, 3L, 2L, 1L, 3L, 2L), .Label = c("ARG", "ASP", "LEU", "O17"
), class = "factor"), ResNum = c(500L, 8L, 24L, 25L, 8L, 24L, 
25L), Energy = c(-37.0367, -0.8456, -0.56739, -0.98583, -0.6488, 
-0.5838, -0.8593)), .Names = c("Chain", "ResId", "ResNum", "Energy"
), class = "data.frame", row.names = c(NA, -7L))

Answer 1

After your edit, the output you are most likely looking for is:

library(reshape2)
dcast(df, ResId~Chain, value.var= 'Energy')
  ResId        A       B        C
1   ARG -0.84560 -0.6488       NA
2   ASP -0.98583 -0.8593       NA
3   LEU -0.56739 -0.5838       NA
4   O17       NA      NA -37.0367

This will put the values together. You can further specify based on your desired output.

df[order(df$ResId), ]
  Chain ResId ResNum    Energy
2     A   ARG      8  -0.84560
5     B   ARG      8  -0.64880
4     A   ASP     25  -0.98583
7     B   ASP     25  -0.85930
3     A   LEU     24  -0.56739
6     B   LEU     24  -0.58380
1     C   O17    500 -37.03670

#With dplyr
library(dplyr)
df %>%
  arrange(ResId)
  Chain ResId ResNum    Energy
1     A   ARG      8  -0.84560
2     B   ARG      8  -0.64880
3     A   ASP     25  -0.98583
4     B   ASP     25  -0.85930
5     A   LEU     24  -0.56739
6     B   LEU     24  -0.58380
7     C   O17    500 -37.03670

Data

df <- read.table(text = '
Chain ResId ResNum Energy

C O17 500 -37.0367

A ARG 8 -0.8456

A LEU 24 -0.56739

A ASP 25 -0.98583

B ARG 8 -0.6488

B LEU 24 -0.5838

B ASP 25 -0.8593', header=T)

Answer 2

If you want to convert to wide format

library(reshape2)
dcast(df, ResId+ResNum~paste0('Energy.',Chain), value.var='Energy')
#   ResId ResNum Energy.A Energy.B Energy.C
#1   ARG      8 -0.84560  -0.6488       NA
#2   ASP     25 -0.98583  -0.8593       NA
#3   LEU     24 -0.56739  -0.5838       NA
#4   O17    500       NA       NA -37.0367

Answer 3

Try this:

df <- df[order(df$Chain, df$ResId, df$ResNum),]

where df is the name of your dataframe. This should order it for you.