CODEWITHSUNDEEP
r
salhin
salhin

Reputation: 2652

Add rows from the same data frame

I have the following dataset:

structure(list(A = c(451.566484133459, 454.92869750881, 451.114252202941, 
454.996314529852, 453.465382452704, 465.331269330636, 454.538567597461, 
463.783172091384, 453.730115277698, 463.72438695636), b = c(-14.205718016514, 
-14.2131358081788, -14.3200642093762, -14.5132647005539, -14.4081200637958, 
-14.1349670121477, -14.507593447239, -14.1254822281233, -14.4903035105664, 
-14.1928692151528), C = c(1469.46452712632, 1469.47892277398, 
1469.69489134056, 1469.86771190593, 1470.21347499657, 1475.25989161757, 
1475.12931967036, 1474.70874502286, 1474.14352261336, 1473.72350981991
), D = c(-10.6169715976949, -10.6421074258488, -10.6542208233633, 
-10.6392491241976, -10.6712321191186, -10.6552464239492, -10.431683014845, 
-10.7029234738311, -10.6610298766338, -10.607892938997), E = c(1025.04527283288, 
1021.64525752271, 1017.15603173527, 1020.63728592133, 1015.14597799164, 
1019.04943069105, 1019.71447994562, 1020.01958437602, 1013.27388793191, 
1021.95151861996), F = c(-11.4656040580594, -11.1989433248374, 
-11.7060300364731, -11.0700075928725, -11.5005713690914, -11.5228159566521, 
-11.1757111501258, -11.2753143566779, -11.6646430517701, -11.5531222045509
)), .Names = c("A", "b", "C", "D", "E", "F"), row.names = c(NA, 
10L), class = "data.frame")

The data frame(df) looks like:

      A         b        C         D        E         F
1  451.5665 -14.20572 1469.465 -10.61697 1025.045 -11.46560
2  454.9287 -14.21314 1469.479 -10.64211 1021.645 -11.19894
3  451.1143 -14.32006 1469.695 -10.65422 1017.156 -11.70603
4  454.9963 -14.51326 1469.868 -10.63925 1020.637 -11.07001
5  453.4654 -14.40812 1470.213 -10.67123 1015.146 -11.50057
6  465.3313 -14.13497 1475.260 -10.65525 1019.049 -11.52282
7  454.5386 -14.50759 1475.129 -10.43168 1019.714 -11.17571
8  463.7832 -14.12548 1474.709 -10.70292 1020.020 -11.27531
9  453.7301 -14.49030 1474.144 -10.66103 1013.274 -11.66464
10 463.7244 -14.19287 1473.724 -10.60789 1021.952 -11.55312

Lets say that I need to cut C and D columns and paste them to A and B starting from row 11. The same for E and F.

I used rbind but it only transpose the data frame not adding the the C and D [1:10,] to A and B

I aim at getting the following:

     A         b           
1  451.5665 -14.20572 
2  454.9287 -14.21314 
3  451.1143 -14.32006 
4  454.9963 -14.51326 
5  453.4654 -14.40812 
6  465.3313 -14.13497 
7  454.5386 -14.50759 
8  463.7832 -14.12548 
9  453.7301 -14.49030 
10 463.7244 -14.19287 
11 1469.465 -10.61697
12 1469.479 -10.64211
13 1469.695 -10.65422
.    .         .
.    .         .
.    .         .
.    .         .
30   .         .

The rows from 11-20 represents df$C[1:10,] and df$D[1:10,] The rows from 21-30 represents df$E[1:10,] and df$F[1:10,]

Upvotes: 1

Views: 87

Answers (1)

akrun
akrun

Reputation: 887951

Try:

Here, the idea is to create a logical index to get alternate columns that recycles to the entire dataset.

 indx <- c(TRUE, FALSE)

 head(df[indx],2) #it subsets the column `A`, `C`, and `E`
 #       A        C        E
 #1 451.5665 1469.465 1025.045
 #2 454.9287 1469.479 1021.645

By doing df[!indx] you get columns b, D, and F. Using unlist on this code gives you a vector. So, basically, you are getting two vectors, which is then used for creating data.frame. 

 df1 <- data.frame(A1=unlist(df[indx]), B1=unlist(df[!indx]))
 row.names(df1) <- 1:nrow(df1)

  df1
  #         A1        B1
  #1   451.5665 -14.20572
  #2   454.9287 -14.21314
  #3   451.1143 -14.32006
  #4   454.9963 -14.51326
  #5   453.4654 -14.40812
  #6   465.3313 -14.13497
  #7   454.5386 -14.50759
  #8   463.7832 -14.12548
  #9   453.7301 -14.49030
  #10  463.7244 -14.19287
  #11 1469.4645 -10.61697
  #12 1469.4789 -10.64211
  #13 1469.6949 -10.65422
  #14 1469.8677 -10.63925
  #15 1470.2135 -10.67123
  #16 1475.2599 -10.65525
  #17 1475.1293 -10.43168
  #18 1474.7087 -10.70292
  #19 1474.1435 -10.66103
  #20 1473.7235 -10.60789
  #21 1025.0453 -11.46560
  #22 1021.6453 -11.19894
  #23 1017.1560 -11.70603
  #24 1020.6373 -11.07001    
  #25 1015.1460 -11.50057
  #26 1019.0494 -11.52282
  #27 1019.7145 -11.17571
  #28 1020.0196 -11.27531
  #29 1013.2739 -11.66464
  #30 1021.9515 -11.55312

Or you could create an array

 m1 <- as.matrix(df)
 dim(m1) <- c(10,2,3)
 do.call(`rbind`,lapply(seq_len(dim(m1)[3]), function(i) m1[,,i]))

Upvotes: 3

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