'Duplicated dataframe rows returned by for loop in R programming
I'm currently working with adding new columns based on a calculation. This is the sample data
REC = c(237, 1781, NA, 3710, 2099)
S = c(2509, 25616, NaN, 19224, 6569)
Industry = c("ABC", "ABC", "ABC", "CDE", "CDE")
data = data.frame(REC, S, Industry)
I want to apply unit length scaling to newly added columns. For that sake I have written this piece of code
data2 = data.frame()
foreach(i = unique(data$Industry)) %do% {
foreach(j = fnames) %do% {
dataOrg = data
# Calculate unit length per feature
dataFin = dataOrg[dataOrg[,"Industry"] == i & is.finite(dataOrg[,j]), ] #Filtering only finite data
data1 = dplyr::filter(dataOrg[!is.finite(dataOrg[,j]), ]) # Filtering the non finite data
dataFin[ , sprintf("%s_uLen", j)] = dataFin[, j] / sqrt(sum(dataFin[, j]^2)) # Calculation
data2 = data2 %>%
dplyr::bind_rows(data1, dataFin)
}
}
This is the output after each iteration
[[1]]
[[1]][[1]]
REC S Industry REC_uLen
1 NA NaN ABC NA
2 237 2509 ABC 0.1319085
3 1781 25616 ABC 0.9912619
[[1]][[2]]
REC S Industry REC_uLen S_uLen
1 NA NaN ABC NA NA
2 237 2509 ABC 0.1319085 NA
3 1781 25616 ABC 0.9912619 NA
4 NA NaN ABC NA NA
5 237 2509 ABC NA 0.09748012
6 1781 25616 ABC NA 0.99523747
[[2]]
[[2]][[1]]
REC S Industry REC_uLen S_uLen
1 NA NaN ABC NA NA
2 237 2509 ABC 0.1319085 NA
3 1781 25616 ABC 0.9912619 NA
4 NA NaN ABC NA NA
5 237 2509 ABC NA 0.09748012
6 1781 25616 ABC NA 0.99523747
7 NA NaN ABC NA NA
8 3710 19224 CDE 0.8703574 NA
9 2099 6569 CDE 0.4924205 NA
[[2]][[2]]
REC S Industry REC_uLen S_uLen
1 NA NaN ABC NA NA
2 237 2509 ABC 0.1319085 NA
3 1781 25616 ABC 0.9912619 NA
4 NA NaN ABC NA NA
5 237 2509 ABC NA 0.09748012
6 1781 25616 ABC NA 0.99523747
7 NA NaN ABC NA NA
8 3710 19224 CDE 0.8703574 NA
9 2099 6569 CDE 0.4924205 NA
10 NA NaN ABC NA NA
11 3710 19224 CDE NA 0.94627897
12 2099 6569 CDE NA 0.32335136
At each step 3 news are getting added. I want my output to contain the same 5 rows of data but with newly added columns.
This is the expected output
REC S Industry REC_uLen S_uLen
1 237 2509 ABC 0.1319085 0.09748012
2 1781 25616 ABC 0.9912619 0.99523747
3 NA NaN ABC NA NA
4 3710 19224 CDE 0.8703574 0.94627897
5 2099 6569 CDE 0.4924205 0.32335136
Sources
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Source: Stack Overflow
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