CODEWITHSUNDEEP
rdataframe
lisanne
lisanne

Reputation: 75

replace in data.frame by matrix

I couldn't find a solution for this problem online, as simple as it seems. Here's it is: I have a dataframe like this names df1: 

                   PIM       WDR       MYC       OBX                           
ILMN_1651282  0.555764  0.675233 0.5908629 0.4897703                           
ILMN_1651354 0.6963458 0.8588675 0.9216328   0.88705                           
ILMN_1651358 0.7501548 0.6766059 0.8157319 0.9373666                           
ILMN_1652716 0.5505098 0.5802357 0.7342341 0.5953167                           
ILMN_1654324 0.9294231 0.9311051 0.8424824  0.888825                           
ILMN_1654639 0.9197155 0.4687101  0.678938 0.4309232                           
ILMN_1655418  0.690068 0.6345875 0.9595042 0.6132203

and a dataframefile like this names df2: 

            PIM WDR MYC OBX                                               
ILMN_1651282  -1  -1  -1  -1                                               
ILMN_1651354  -1   1   1   1                                               
ILMN_1651358   1   1   1   1                                               
ILMN_1652716  -1  -1  -1  -1                                               
ILMN_1654324  -1  -1  -1  -1                                               
ILMN_1654639  -1  -1  -1  -1                                               
ILMN_1655418   1   1  -1   1

I have an cutoff value of 0.8. In df1 every value higher than 0.8 changed in 0. All values under 0.8 must be replaced by the values in df2 (1 & -1)

created df2:

PIMvsEV<-list()
for (x in 1:nrow(df1)) {
t<-(if (mean(PIM[,x]) > mean(EV[,x])) {print(1)} else
if (mean(PIM[,x]) < mean(EV[,x])) {print(-1)} )
PIMvsEV[[x]]<-matrix(t)
}

WDRvsEV<-list()
for (x in 1:nrow(df1)) {
t<-(if (mean(WDR[,x]) > mean(EV[,x])) {print(1)} else
if (mean(WDR[,x]) < mean(EV[,x])) {print(-1)} )
WDRvsEV[[x]]<-matrix(t)
}

OBXvsEV<-list()
for (x in 1:nrow(cdf1)) {
t<-(if (mean(OBX[,x]) > mean(EV[,x])) {print(1)} else
if (mean(OBX[,x]) < mean(EV[,x])) {print(-1)} )
OBXvsEV[[x]]<-matrix(t)
}

MYCvsEV<-list()
for (x in 1:nrow(df1)) {
t<-(if (mean(MYC[,x]) > mean(EV[,x])) {print(1)} else
if (mean(MYC[,x]) < mean(EV[,x])) {print(-1)} )
MYCvsEV[[x]]<-matrix(t)
}

dataframe<-as.data.frame(cbind(as.matrix(PIMvsEV), as.matrix(WDRvsEV)))
dataframe<-as.data.frame(cbind(as.matrix(dataframe), as.matrix(MYCvsEV)))
dataframe<-as.data.frame(cbind(as.matrix(dataframe), as.matrix(OBXvsEV)))
row.names(dataframe)<-colnames(ttest)
colnames(dataframe)<-c("PIM","WDR","MYC","OBX")

Any thoughts? Many thanks in advance,

Lisanne

Upvotes: 0

Views: 689

Answers (2)

Sacha Epskamp
Sacha Epskamp

Reputation: 47562

This should do what you want right?

Some data:

df1 <- as.data.frame(matrix(rnorm(100),10,10))
df2 <- matrix(sample(c(-1,1),100,T),10,10)

Vectorized use of ifelse :

 ifelse( as.matrix(df1) > 0.8, 0, df2)

      V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
 [1,]  0  0  1 -1  1  1 -1 -1  1  -1
 [2,] -1  1  1 -1 -1 -1 -1 -1  1  -1
 [3,] -1 -1 -1  0  0 -1  1  0  1  -1
 [4,]  0 -1 -1  1 -1  1 -1  1  1   1
 [5,] -1 -1 -1 -1  0  1 -1  1  0   0
 [6,] -1  1  1  1 -1  1  0  0  1   1
 [7,] -1  1  1  0 -1 -1 -1 -1 -1  -1
 [8,]  1  1  1  0 -1 -1  1 -1  0  -1
 [9,]  1  0  0  1  1  0 -1 -1  0  -1
[10,] -1 -1 -1 -1  1 -1 -1 -1 -1   1

Or we can do

 (df1<= 0.8)*df2

Upvotes: 1

Wojciech Sobala
Wojciech Sobala

Reputation: 7561

Example data:

df1 <- as.data.frame(matrix(rnorm(100),10,10))
df2 <- as.data.frame(matrix(sample(c(-1,1),100,T),10,10))

Code for data.frames

res <- df1 
res[df1>0.8] <- 0
res[df1<=0.8] <- df2[df1<=0.8]

Upvotes: 1

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