Basically, I have a dataframe, df
Beginning1 Protein2 Protein3 Protein4 Biomarker1
Pathway3 A G NA NA F
Pathway8 Z G NA NA E
Pathway9 A G Z H F
Pathway6 Y G Z H E
Pathway2 A G D NA F
Pathway5 Q G D NA E
Pathway1 A D K NA F
Pathway7 A B C D F
Pathway4 V B C D E
And I want to combine the dataframe so that those rows when are identical from "Protein2" to "Protein4" are condense, giving the following:
Beginning1 Protein2 Protein3 Protein4 Biomarker1
Pathway3 A,Z G NA NA F,E
Pathway9 A,Y G Z H F,E
Pathway2 A,Q G D NA F,E
Pathway1 A D K NA F
Pathway7 A,V B C D F,E
This is very similar to a question that I asked before ( Consolidating duplicate rows in a dataframe ), however the difference is that I am also consolidating the "Beginning1" row.
So far, I have tried:
library(dat.table)
dat<-data.table(df)
Total_collapse <- dat[, .(
Biomarker1 = paste0(Biomarker1, collapse = ", ")),
by = .(Beginning1, Protein1, Protein2, Protein3)]
Total_collapse <- dat[, .(
Beginning1 = paste0(Beginning1, collapse = ", ")),
by = .(Protein1, Protein2, Protein3)]
which gives the output:
Beginning1 Protein2 Protein3 Protein4 Biomarker1
Pathway3 G NA NA F,E
Pathway9 G Z H F,E
Pathway2 G D NA F,E
Pathway1 D K NA F
Pathway7 B C D F,E
Does anyone know how to fix this problem? I have also tried duplicating the solution from Collapse / concatenate / aggregate a column to a single comma separated string within each group , but have had no success.
I am sorry if it is a simple error- I am pretty new to R.
Using data.table
you can use .SD
to refer to all columns not specified in the by
argument. Then we can use lapply
to accomplish the paste()
with collapse
.
library(data.table)
dt <- read.table(text = "Beginning1 Protein2 Protein3 Biomarker1
A G NA NA F
Z G NA NA E
A G Z H F
Y G Z H E
A G D NA F
Q G D NA E
A D K NA F
A B C D F
V B C D E",header = T)
dt <- data.table(dt)
dt[,lapply(.SD, function(col) paste(col, collapse=", ")),
by=.(Protein2, Protein3, Protein4)]
Output
Protein2 Protein3 Protein4 Beginning1 Biomarker1
1: G NA NA A, Z F, E
2: G Z H A, Y F, E
3: G D NA A, Q F, E
4: D K NA A F
5: B C D A, V F, E
Here's a possible solution using dplyr
df %>% group_by_at(vars(Protein2:Protein4)) %>%
summarize_all(paste, collapse=",")
We can use aggregate
from base R
r1 <- aggregate(cbind(Beginning1, Biomarker1)~., replace(df,is.na(df), "NA"), FUN = toString)
r1
# Protein2 Protein3 Protein4 Beginning1 Biomarker1
#1 B C D A, V F, E
#2 G Z H A, Y F, E
#3 G D NA A, Q F, E
#4 D K NA A F
#5 G NA NA A, Z F, E
r1[r1=="NA"] <- NA
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