This question already has answers here:
Select rows from a data frame based on values in a vector
(3 answers)
Closed 5 years ago.
How can I avoid using a loop to subset a dataframe based on multiple factor levels?
In the following example my desired output is a dataframe. The dataframe should contain the rows of the original dataframe where the value in "Code" equals one of the values in "selected".
Working example:
#sample data
Code<-c("A","B","C","D","C","D","A","A")
Value<-c(1, 2, 3, 4, 1, 2, 3, 4)
data<-data.frame(cbind(Code, Value))
selected<-c("A","B") #want rows that contain A and B
#Begin subsetting
result<-data[which(data$Code==selected[1]),]
s1<-2
while(s1<length(selected)+1)
{
result<-rbind(result,data[which(data$Code==selected[s1]),])
s1<-s1+1
}
This is a toy example of a much larger dataset, so "selected" may contain a great number of elements and the data a great number of rows. Therefore I would like to avoid the loop.
You can use %in%
data[data$Code %in% selected,]
Code Value
1 A 1
2 B 2
7 A 3
8 A 4
Here's another:
data[data$Code == "A" | data$Code == "B", ]
It's also worth mentioning that the subsetting factor doesn't have to be part of the data frame if it matches the data frame rows in length and order. In this case we made our data frame from this factor anyway. So,
data[Code == "A" | Code == "B", ]
also works, which is one of the really useful things about R.
Try this:
> data[match(as.character(data$Code), selected, nomatch = FALSE), ]
Code Value
1 A 1
2 B 2
1.1 A 1
1.2 A 1
Related
This question already has answers here:
R Create column which holds column name of maximum value for each row
(4 answers)
Closed 1 year ago.
Say we have the following matrix,
x <- matrix(1:9, nrow = 3, dimnames = list(c("X","Y","Z"), c("A","B","C")))
What I'm trying to do is:
1- Find the maximum value of each row. For this part, I'm doing the following,
df <- apply(X=x, MARGIN=1, FUN=max)
2- Then, I want to extract the column names of the maximum values and put them next to the values. Following the reproducible example, it would be "C" for the three rows.
Any assistance would be wonderful.
You can use apply like
maxColumnNames <- apply(x,1,function(row) colnames(x)[which.max(row)])
Since you have a numeric matrix, you can't add the names as an extra column (it would become converted to a character-matrix).
You can choose a data.frame and do
resDf <- cbind(data.frame(x),data.frame(maxColumnNames = maxColumnNames))
resulting in
resDf
A B C maxColumnNames
X 1 4 7 C
Y 2 5 8 C
Z 3 6 9 C
This question already has answers here:
What is about the first column in R's dataset mtcars?
(4 answers)
Closed 3 years ago.
I have xy data for gene expression in multiple samples. I wish to subset the first column so I can order the genes alphabetically and perform some other filtering.
> setwd("C:/Users/Will/Desktop/BIOL3063/R code assignment");
> df = read.csv('R-assignments-dataset.csv', stringsAsFactors = FALSE);
Here is a simplified example of the dataset I'm working with, it has 270 columns (tissue samples) and 7065 rows (gene names).
The first column is a list of gene names (A2M, AAAS, AACS etc.) and each column is a different tissue sample, thus showing the gene expression in each tissue sample.
The question being asked is "Sort the gene names alpahabetically (A-Z) and print out the first 20 gene names"
My thought process would be to subset the first column (gene names) and then perform order() to sort alphabetically, after which I can use head() to print the first 20.
However when I try
> genes <- df[1]
It simply subsets the first column that has data in it (TCGA-A6-2672_TissueA) rather than the one to its left.
Also
> genes <- df[,df$col1];
> genes;
data frame with 0 columns and 7065 rows
> order(genes);
integer(0)
Appears to create a list of gene names in R studio's viewer but I cannot perform any manipulation on it.
I am unable to correctly locate the first column in the data.frame, since it does not have a column header, and I also have the same problem when doing the same thing with row 1 (sample names) as well.
I'm a complete novice at R and this is part of an assignment I'm working on, it seems I'm missing something fundamental but I can not figure out what.
Cheers guys
Please include a sample of your text file as text instead of an image.
I have created a dataset similar to yours:
X Y
1 a b
2 c d
3 d g
Note that your tissue columns have a header but your gene names do not. Therefore these will be interpreted as rownames, see ?read.table:
If row.names is not specified and the header line has one less entry
than the number of columns, the first column is taken to be the row
names.
Reading it in R:
df <- read.table(text = ' X Y
1 a b
2 c d
3 d g')
So your gene names are not at df[1] but instead in rownames(df), so to get these genes <- rownames(df) or to add these to the existing df you can use df$gene <- rownames(df)
There are numerous ways to convert your row names to a column see for example this question.
If you are asking what I think you are asking, you just need to subset inside the as.data.frame function, which will auto-generate a "header", as you call it. It will be called V1, the first variable of your new data frame.
genes <- as.data.frame(df[,1])
genes$V1
1 A
2 C
3 A
4 B
5 C
6 D
7 A
8 B
As per the comment below, the issue could be avoided if you remove the comma from your subsetting syntax. When you select columns from a data.frame, you only need to index the column, not the rows.
genes <- df[1]
This question already has answers here:
Select rows from a data frame based on values in a vector
(3 answers)
Closed 5 years ago.
How can I avoid using a loop to subset a dataframe based on multiple factor levels?
In the following example my desired output is a dataframe. The dataframe should contain the rows of the original dataframe where the value in "Code" equals one of the values in "selected".
Working example:
#sample data
Code<-c("A","B","C","D","C","D","A","A")
Value<-c(1, 2, 3, 4, 1, 2, 3, 4)
data<-data.frame(cbind(Code, Value))
selected<-c("A","B") #want rows that contain A and B
#Begin subsetting
result<-data[which(data$Code==selected[1]),]
s1<-2
while(s1<length(selected)+1)
{
result<-rbind(result,data[which(data$Code==selected[s1]),])
s1<-s1+1
}
This is a toy example of a much larger dataset, so "selected" may contain a great number of elements and the data a great number of rows. Therefore I would like to avoid the loop.
You can use %in%
data[data$Code %in% selected,]
Code Value
1 A 1
2 B 2
7 A 3
8 A 4
Here's another:
data[data$Code == "A" | data$Code == "B", ]
It's also worth mentioning that the subsetting factor doesn't have to be part of the data frame if it matches the data frame rows in length and order. In this case we made our data frame from this factor anyway. So,
data[Code == "A" | Code == "B", ]
also works, which is one of the really useful things about R.
Try this:
> data[match(as.character(data$Code), selected, nomatch = FALSE), ]
Code Value
1 A 1
2 B 2
1.1 A 1
1.2 A 1
This question already has answers here:
Find complement of a data frame (anti - join)
(7 answers)
Closed 7 years ago.
I would like to remove rows that have specific values for columns that match values in another data frame.
a<-c(1,1,2,2,2,4,5,5,5,5)
b<-c(10,10,22,30,30,30,40,40,40,40)
c<-c(1,2,1,2,2,2,2,1,1,2)
d<-rnorm(1:10)
data<-data.frame(a,b,c,d)
a<-c(2,5)
b<-c(30,40)
c<-c(2,1)
x<-data.frame(a,b,c)
So that y can become:
a b c d
1 10 1 -0.2509255
1 10 2 0.4142277
2 22 1 -0.1340514
4 30 2 -1.5372009
5 40 2 1.9001932
5 40 2 -1.2825212
I tried the following, which did not work:
y<-data[!data$a==a & !data$b==b & !data$c==c,]
y<-subset(data, !data$a==x$a & !data$b==x$b & !data$c==x$c)
I also tried to just flag the ones that should be removed in order to subset in a second step, but this did not work either:
y<-data
y$rm<-ifelse(y$a==x$a & y$b==x$b & y$c==x$c, 1, 0)
The real "data" and "x" are much longer, and there are variable number of rows in data that match each row in x.
We can use anti_join from dplyr. It will return all rows from 'data' that are not matching values in 'x'. We specify the variables to be considered in the by argument.
library(dplyr)
anti_join(data, x, by=c('a', 'b', 'c'))
I have a a variable in a dataframe whose observations are a mix of numeric and character values (due to faulty data entry). How can I subset in only the observations which are numeric? Suppose the values of filename$varname are (1, 2, 1, 5, 3, a, 3, d, 1), I would like subset out "a" and "d" and keep only the rest of the values which are numeric.
You can make use of the fact that as.numeric will convert character strings to NA whilst keeping numeric data:
x <- c(1, 2, 1, 5, 3, "a", 3, "d", 1)
as.numeric(x)
[1] 1 2 1 5 3 NA 3 NA 1
Warning message:
NAs introduced by coercion
Now use is.na to test for NA values and exclude these using vector subsetting:
y <- as.numeric(x)
y[!is.na(y)]
[1] 1 2 1 5 3 3 1
Without a reproducible example it is hard to see what your data actually looks like. For instance, is the column of your data frame a factor or just strings? If it is just strings then Andrie's answer works (just use as.numeric()), and if the data is a factor you first need to convert that to strings with as.character(x):
as.numeric(as.character(filename$varname))
You will get some NAs but that is absolutely fine as those values are indeed missing.
EDIT: To clarify abit more. You have a data frame, so you don't want to take values out of the data frame as then it wouldn't be a dataframe anymore (equal rows). You want to correctly assign NA for missing values instead as most statistical functions in R can handle them.