Related
So, I am new in R and trying to implement a differential gene expression analysis.
I'm trying to store gene names as rownames so that I can create a DGEList object.
asthma <- read.csv("Asthma_3 groups-Our study gene expression.csv")
head(asthma, 10)
dim(asthma)
asthma <- na.omit(asthma)
distinct(asthma)
countdata <- asthma[,-1]
head(countdata)
rownames(countdata) <- asthma[,1]
'''
I am getting this error:
Error in `.rowNamesDF<-`(x, value = value) : duplicate 'row.names' are not allowed
The first column in asthma likely has duplicate values. Two options I can think of
Can the first column be combined with another column to generate a new column with unique values that can be used as the rownames?
If not, you can probably use make.names().
Here is a reproducible example.
df = data.frame(col1 = c('A', 'A', 'B'), col2 = c(1, 2, 3))
df
That defines a data.frame that looks like this
col1 col2
1 A 1
2 A 2
3 B 3
The data.frame by default has rownames 1, 2, 3. If you try this
rownames(df) = df[,1]
you get an error because df[,1] has 'A' twice, so it can't be used as a rowname without modification. You use make.names to create rownames with unique values like this
unique.col1 = make.names(df[,1], unique=T)
unique.col1
This results in
"A" "A.1" "B"
Note that the .1 was added to the second A to make it different from the first A. Then define the rownames as unique.col1:
rownames(df) = unique.col1
df
The data.frame df now looks like this
col1 col2
A A 1
A.1 A 2
B B 3
I know if I have a data frame with more than 1 column, then I can use
colnames(x) <- c("col1","col2")
to rename the columns. How to do this if it's just one column?
Meaning a vector or data frame with only one column.
Example:
trSamp <- data.frame(sample(trainer$index, 10000))
head(trSamp )
# sample.trainer.index..10000.
# 1 5907862
# 2 2181266
# 3 7368504
# 4 1949790
# 5 3475174
# 6 6062879
ncol(trSamp)
# [1] 1
class(trSamp)
# [1] "data.frame"
class(trSamp[1])
# [1] "data.frame"
class(trSamp[,1])
# [1] "numeric"
colnames(trSamp)[2] <- "newname2"
# Error in names(x) <- value :
# 'names' attribute [2] must be the same length as the vector [1]
This is a generalized way in which you do not have to remember the exact location of the variable:
# df = dataframe
# old.var.name = The name you don't like anymore
# new.var.name = The name you want to get
names(df)[names(df) == 'old.var.name'] <- 'new.var.name'
This code pretty much does the following:
names(df) looks into all the names in the df
[names(df) == old.var.name] extracts the variable name you want to check
<- 'new.var.name' assigns the new variable name.
colnames(trSamp)[2] <- "newname2"
attempts to set the second column's name. Your object only has one column, so the command throws an error. This should be sufficient:
colnames(trSamp) <- "newname2"
colnames(df)[colnames(df) == 'oldName'] <- 'newName'
This is an old question, but it is worth noting that you can now use setnames from the data.table package.
library(data.table)
setnames(DF, "oldName", "newName")
# or since the data.frame in question is just one column:
setnames(DF, "newName")
# And for reference's sake, in general (more than once column)
nms <- c("col1.name", "col2.name", etc...)
setnames(DF, nms)
This can also be done using Hadley's plyr package, and the rename function.
library(plyr)
df <- data.frame(foo=rnorm(1000))
df <- rename(df,c('foo'='samples'))
You can rename by the name (without knowing the position) and perform multiple renames at once. After doing a merge, for example, you might end up with:
letterid id.x id.y
1 70 2 1
2 116 6 5
3 116 6 4
4 116 6 3
5 766 14 9
6 766 14 13
Which you can then rename in one step using:
letters <- rename(letters,c("id.x" = "source", "id.y" = "target"))
letterid source target
1 70 2 1
2 116 6 5
3 116 6 4
4 116 6 3
5 766 14 9
6 766 14 13
I think the best way of renaming columns is by using the dplyr package like this:
require(dplyr)
df = rename(df, new_col01 = old_col01, new_col02 = old_col02, ...)
It works the same for renaming one or many columns in any dataset.
I find that the most convenient way to rename a single column is using dplyr::rename_at :
library(dplyr)
cars %>% rename_at("speed",~"new") %>% head
cars %>% rename_at(vars(speed),~"new") %>% head
cars %>% rename_at(1,~"new") %>% head
# new dist
# 1 4 2
# 2 4 10
# 3 7 4
# 4 7 22
# 5 8 16
# 6 9 10
works well in pipe chaines
convenient when names are stored in variables
works with a name or an column index
clear and compact
I like the next style for rename dataframe column names one by one.
colnames(df)[which(colnames(df) == 'old_colname')] <- 'new_colname'
where
which(colnames(df) == 'old_colname')
returns by the index of the specific column.
Let df be the dataframe you have with col names myDays and temp.
If you want to rename "myDays" to "Date",
library(plyr)
rename(df,c("myDays" = "Date"))
or with pipe, you can
dfNew <- df %>%
plyr::rename(c("myDays" = "Date"))
Try:
colnames(x)[2] <- 'newname2'
This is likely already out there, but I was playing with renaming fields while searching out a solution and tried this on a whim. Worked for my purposes.
Table1$FieldNewName <- Table1$FieldOldName
Table1$FieldOldName <- NULL
Edit begins here....
This works as well.
df <- rename(df, c("oldColName" = "newColName"))
You can use the rename.vars in the gdata package.
library(gdata)
df <- rename.vars(df, from = "oldname", to = "newname")
This is particularly useful where you have more than one variable name to change or you want to append or pre-pend some text to the variable names, then you can do something like:
df <- rename.vars(df, from = c("old1", "old2", "old3",
to = c("new1", "new2", "new3"))
For an example of appending text to a subset of variables names see:
https://stackoverflow.com/a/28870000/180892
You could also try 'upData' from 'Hmisc' package.
library(Hmisc)
trSamp = upData(trSamp, rename=c(sample.trainer.index..10000. = 'newname2'))
If you know that your dataframe has only one column, you can use:
names(trSamp) <- "newname2"
The OP's question has been well and truly answered. However, here's a trick that may be useful in some situations: partial matching of the column name, irrespective of its position in a dataframe:
Partial matching on the name:
d <- data.frame(name1 = NA, Reported.Cases..WHO..2011. = NA, name3 = NA)
## name1 Reported.Cases..WHO..2011. name3
## 1 NA NA NA
names(d)[grepl("Reported", names(d))] <- "name2"
## name1 name2 name3
## 1 NA NA NA
Another example: partial matching on the presence of "punctuation":
d <- data.frame(name1 = NA, Reported.Cases..WHO..2011. = NA, name3 = NA)
## name1 Reported.Cases..WHO..2011. name3
## 1 NA NA NA
names(d)[grepl("[[:punct:]]", names(d))] <- "name2"
## name1 name2 name3
## 1 NA NA NA
These were examples I had to deal with today, I thought might be worth sharing.
I would simply change a column name to the dataset with the new name I want with the following code:
names(dataset)[index_value] <- "new_col_name"
I found colnames() argument easier
https://www.rdocumentation.org/packages/base/versions/3.6.2/topics/row%2Bcolnames
select some column from the data frame
df <- data.frame(df[, c( "hhid","b1005", "b1012_imp", "b3004a")])
and rename the selected column in order,
colnames(df) <- c("hhid", "income", "cost", "credit")
check the names and the values to be sure
names(df);head(df)
I would simply add a new column to the data frame with the name I want and get the data for it from the existing column. like this:
dataf$value=dataf$Article1Order
then I remove the old column! like this:
dataf$Article1Order<-NULL
This code might seem silly! But it works perfectly...
We can use rename_with to rename columns with a function (stringr functions, for example).
Consider the following data df_1:
df_1 <- data.frame(
x = replicate(n = 3, expr = rnorm(n = 3, mean = 10, sd = 1)),
y = sample(x = 1:2, size = 10, replace = TRUE)
)
names(df_1)
#[1] "x.1" "x.2" "x.3" "y"
Rename all variables with dplyr::everything():
library(tidyverse)
df_1 %>%
rename_with(.data = ., .cols = everything(.),
.fn = str_replace, pattern = '.*',
replacement = str_c('var', seq_along(.), sep = '_')) %>%
names()
#[1] "var_1" "var_2" "var_3" "var_4"
Rename by name particle with some dplyr verbs (starts_with, ends_with, contains, matches, ...).
Example with . (x variables):
df_1 %>%
rename_with(.data = ., .cols = contains('.'),
.fn = str_replace, pattern = '.*',
replacement = str_c('var', seq_along(.), sep = '_')) %>%
names()
#[1] "var_1" "var_2" "var_3" "y"
Rename by class with many functions of class test, like is.integer, is.numeric, is.factor...
Example with is.integer (y):
df_1 %>%
rename_with(.data = ., .cols = is.integer,
.fn = str_replace, pattern = '.*',
replacement = str_c('var', seq_along(.), sep = '_')) %>%
names()
#[1] "x.1" "x.2" "x.3" "var_1"
The warning:
Warning messages:
1: In stri_replace_first_regex(string, pattern, fix_replacement(replacement), :
longer object length is not a multiple of shorter object length
2: In names[cols] <- .fn(names[cols], ...) :
number of items to replace is not a multiple of replacement length
It is not relevant, as it is just an inconsistency of seq_along(.) with the replace function.
library(dplyr)
rename(data, de=de.y)
I have a data frame that looks like this:
> mydf
val1 val2
hsa-let-7a 2.139890 -0.03477569
hsa-let-7b 2.102590 0.04108795
hsa-let-7c 2.061705 0.02375882
hsa-let-7d 1.938950 -0.04364545
hsa-let-7e 1.889000 -0.10575235
hsa-let-7f 2.264296 0.08465690
Note that from 3 columns only 2nd and 3rd are names.
What I want to do is to name the first column (plus rename the 2nd and 3rd).
But why this command failed?
colnames(mydf) <- c("COL1","VAL1","VAL2");
What's the right way to do it?
It gave me:
Error in `colnames<-`(`*tmp*`, value = c("COL1", "VAL1", "VAL2" :
'names' attribute [3] must be the same length as the vector [2]
You could join the row names to the dataframe, like this:
mydf <- cbind(rownames(mydf), mydf)
rownames(mydf) <- NULL
colnames(mydf) <- c("COL1","VAL1","VAL2")
Or, in one step:
setNames(cbind(rownames(mydf), mydf, row.names = NULL),
c("COL1", "VAL1", "VAL2"))
# COL1 VAL1 VAL2
# 1 hsa-let-7a 2.139890 -0.03477569
# 2 hsa-let-7b 2.102590 0.04108795
# 3 hsa-let-7c 2.061705 0.02375882
# 4 hsa-let-7d 1.938950 -0.04364545
# 5 hsa-let-7e 1.889000 -0.10575235
# 6 hsa-let-7f 2.264296 0.08465690
this may also work in your case,
mydf <- cbind(rownames(mydf),mydf)
rownames(mydf) <- NULL
colnames(mydf) <- c(names(mydf)) #to not write all the column names
colnames(mydf)[1] <- "name.of.the.first.column"
names(mydf)
If one wants to use a tidyverse solution within his/her pipeline, this works
rownames_to_column(mydf, var = "var_name")
The function is contained in the tibble package
I'm working from this answer trying to optimize the second argument in the plyr:rename, as suggested by Jared.
In short they are renaming some columns in a data frame using plyr like this,
df <- data.frame(col1=1:3,col2=3:5,col3=6:8)
df
newNames <- c("new_col1", "new_col2", "new_col3")
oldNames <- names(df)
require(plyr)
df <- rename(df, c("col1"="new_col1", "col2"="new_col2", "col3"="new_col3"))
df
In passing Jared writes '[a]nd you can be creative in making that second argument to rename so that it is not so manual.'
I've tried being creative like this,
df <- data.frame(col1=1:3,col2=3:5,col3=6:8)
df
secondArgument <- paste0('"', oldNames, '"','=', '"',newNames, '"',collapse = ',')
df <- rename(df, secondArgument)
df
But it does not work, can anyone help me automates this?
Thanks!
Update Sun Sep 9 11:55:42PM
I realized I should have been more specific in my question.
I'm using plyr::rename because I, in my real life example, have other variables and I don't always know the position of the variables I want to rename. I'll add an update to my question
My case look like this, but with 100+ variables
df2 <- data.frame(col1=1:3,col2=3:5,col3=6:8)
df2
df2 <- rename(df2, c("col1"="new_col1", "col3"="new_col3"))
df2
df2 <- data.frame(col1=1:3,col2=3:5,col3=6:8)
df2
newNames <- c("new_col1", "new_col3")
oldNames <- names(df[,c('col1', 'col3')])
secondArgument <- paste0('"', oldNames, '"','=', '"',newNames, '"',collapse = ',')
df2 <- rename(df2, secondArgument)
df2
Please add an comment if there is anything I need to clarify.
Solution to modified question:
df2 <- data.frame(col1=1:3,col2=3:5,col3=6:8)
df2
newNames <- c("new_col1", "new_col3")
oldNames <- names(df2[,c('col1', 'col3')])
(Isn't oldNames equal toc('col1','col3') by definition?)
Solution with plyr:
secondArgument <- setNames(newNames,oldNames)
library(plyr)
df2 <- rename(df2, secondArgument)
df2
Or in base R you could do:
names(df2)[match(oldNames,names(df2))] <- newNames
Set the names on newNames to the names from oldNames:
R> names(newNames) <- oldNames
R> newNames
col1 col2 col3
"new_col1" "new_col2" "new_col3"
R> df <- rename(df, newNames)
R> df
new_col1 new_col2 new_col3
1 1 3 6
2 2 4 7
3 3 5 8
plyr::rename requires a named character vector, with new names as values, and old names as names.
This should work:
names(newNames) <- oldNames
df <- rename(df, newNames)
df
new_col1 new_col2 new_col3
1 1 3 6
2 2 4 7
3 3 5 8
I know if I have a data frame with more than 1 column, then I can use
colnames(x) <- c("col1","col2")
to rename the columns. How to do this if it's just one column?
Meaning a vector or data frame with only one column.
Example:
trSamp <- data.frame(sample(trainer$index, 10000))
head(trSamp )
# sample.trainer.index..10000.
# 1 5907862
# 2 2181266
# 3 7368504
# 4 1949790
# 5 3475174
# 6 6062879
ncol(trSamp)
# [1] 1
class(trSamp)
# [1] "data.frame"
class(trSamp[1])
# [1] "data.frame"
class(trSamp[,1])
# [1] "numeric"
colnames(trSamp)[2] <- "newname2"
# Error in names(x) <- value :
# 'names' attribute [2] must be the same length as the vector [1]
This is a generalized way in which you do not have to remember the exact location of the variable:
# df = dataframe
# old.var.name = The name you don't like anymore
# new.var.name = The name you want to get
names(df)[names(df) == 'old.var.name'] <- 'new.var.name'
This code pretty much does the following:
names(df) looks into all the names in the df
[names(df) == old.var.name] extracts the variable name you want to check
<- 'new.var.name' assigns the new variable name.
colnames(trSamp)[2] <- "newname2"
attempts to set the second column's name. Your object only has one column, so the command throws an error. This should be sufficient:
colnames(trSamp) <- "newname2"
colnames(df)[colnames(df) == 'oldName'] <- 'newName'
This is an old question, but it is worth noting that you can now use setnames from the data.table package.
library(data.table)
setnames(DF, "oldName", "newName")
# or since the data.frame in question is just one column:
setnames(DF, "newName")
# And for reference's sake, in general (more than once column)
nms <- c("col1.name", "col2.name", etc...)
setnames(DF, nms)
This can also be done using Hadley's plyr package, and the rename function.
library(plyr)
df <- data.frame(foo=rnorm(1000))
df <- rename(df,c('foo'='samples'))
You can rename by the name (without knowing the position) and perform multiple renames at once. After doing a merge, for example, you might end up with:
letterid id.x id.y
1 70 2 1
2 116 6 5
3 116 6 4
4 116 6 3
5 766 14 9
6 766 14 13
Which you can then rename in one step using:
letters <- rename(letters,c("id.x" = "source", "id.y" = "target"))
letterid source target
1 70 2 1
2 116 6 5
3 116 6 4
4 116 6 3
5 766 14 9
6 766 14 13
I think the best way of renaming columns is by using the dplyr package like this:
require(dplyr)
df = rename(df, new_col01 = old_col01, new_col02 = old_col02, ...)
It works the same for renaming one or many columns in any dataset.
I find that the most convenient way to rename a single column is using dplyr::rename_at :
library(dplyr)
cars %>% rename_at("speed",~"new") %>% head
cars %>% rename_at(vars(speed),~"new") %>% head
cars %>% rename_at(1,~"new") %>% head
# new dist
# 1 4 2
# 2 4 10
# 3 7 4
# 4 7 22
# 5 8 16
# 6 9 10
works well in pipe chaines
convenient when names are stored in variables
works with a name or an column index
clear and compact
I like the next style for rename dataframe column names one by one.
colnames(df)[which(colnames(df) == 'old_colname')] <- 'new_colname'
where
which(colnames(df) == 'old_colname')
returns by the index of the specific column.
Let df be the dataframe you have with col names myDays and temp.
If you want to rename "myDays" to "Date",
library(plyr)
rename(df,c("myDays" = "Date"))
or with pipe, you can
dfNew <- df %>%
plyr::rename(c("myDays" = "Date"))
Try:
colnames(x)[2] <- 'newname2'
This is likely already out there, but I was playing with renaming fields while searching out a solution and tried this on a whim. Worked for my purposes.
Table1$FieldNewName <- Table1$FieldOldName
Table1$FieldOldName <- NULL
Edit begins here....
This works as well.
df <- rename(df, c("oldColName" = "newColName"))
You can use the rename.vars in the gdata package.
library(gdata)
df <- rename.vars(df, from = "oldname", to = "newname")
This is particularly useful where you have more than one variable name to change or you want to append or pre-pend some text to the variable names, then you can do something like:
df <- rename.vars(df, from = c("old1", "old2", "old3",
to = c("new1", "new2", "new3"))
For an example of appending text to a subset of variables names see:
https://stackoverflow.com/a/28870000/180892
You could also try 'upData' from 'Hmisc' package.
library(Hmisc)
trSamp = upData(trSamp, rename=c(sample.trainer.index..10000. = 'newname2'))
If you know that your dataframe has only one column, you can use:
names(trSamp) <- "newname2"
The OP's question has been well and truly answered. However, here's a trick that may be useful in some situations: partial matching of the column name, irrespective of its position in a dataframe:
Partial matching on the name:
d <- data.frame(name1 = NA, Reported.Cases..WHO..2011. = NA, name3 = NA)
## name1 Reported.Cases..WHO..2011. name3
## 1 NA NA NA
names(d)[grepl("Reported", names(d))] <- "name2"
## name1 name2 name3
## 1 NA NA NA
Another example: partial matching on the presence of "punctuation":
d <- data.frame(name1 = NA, Reported.Cases..WHO..2011. = NA, name3 = NA)
## name1 Reported.Cases..WHO..2011. name3
## 1 NA NA NA
names(d)[grepl("[[:punct:]]", names(d))] <- "name2"
## name1 name2 name3
## 1 NA NA NA
These were examples I had to deal with today, I thought might be worth sharing.
I would simply change a column name to the dataset with the new name I want with the following code:
names(dataset)[index_value] <- "new_col_name"
I found colnames() argument easier
https://www.rdocumentation.org/packages/base/versions/3.6.2/topics/row%2Bcolnames
select some column from the data frame
df <- data.frame(df[, c( "hhid","b1005", "b1012_imp", "b3004a")])
and rename the selected column in order,
colnames(df) <- c("hhid", "income", "cost", "credit")
check the names and the values to be sure
names(df);head(df)
I would simply add a new column to the data frame with the name I want and get the data for it from the existing column. like this:
dataf$value=dataf$Article1Order
then I remove the old column! like this:
dataf$Article1Order<-NULL
This code might seem silly! But it works perfectly...
We can use rename_with to rename columns with a function (stringr functions, for example).
Consider the following data df_1:
df_1 <- data.frame(
x = replicate(n = 3, expr = rnorm(n = 3, mean = 10, sd = 1)),
y = sample(x = 1:2, size = 10, replace = TRUE)
)
names(df_1)
#[1] "x.1" "x.2" "x.3" "y"
Rename all variables with dplyr::everything():
library(tidyverse)
df_1 %>%
rename_with(.data = ., .cols = everything(.),
.fn = str_replace, pattern = '.*',
replacement = str_c('var', seq_along(.), sep = '_')) %>%
names()
#[1] "var_1" "var_2" "var_3" "var_4"
Rename by name particle with some dplyr verbs (starts_with, ends_with, contains, matches, ...).
Example with . (x variables):
df_1 %>%
rename_with(.data = ., .cols = contains('.'),
.fn = str_replace, pattern = '.*',
replacement = str_c('var', seq_along(.), sep = '_')) %>%
names()
#[1] "var_1" "var_2" "var_3" "y"
Rename by class with many functions of class test, like is.integer, is.numeric, is.factor...
Example with is.integer (y):
df_1 %>%
rename_with(.data = ., .cols = is.integer,
.fn = str_replace, pattern = '.*',
replacement = str_c('var', seq_along(.), sep = '_')) %>%
names()
#[1] "x.1" "x.2" "x.3" "var_1"
The warning:
Warning messages:
1: In stri_replace_first_regex(string, pattern, fix_replacement(replacement), :
longer object length is not a multiple of shorter object length
2: In names[cols] <- .fn(names[cols], ...) :
number of items to replace is not a multiple of replacement length
It is not relevant, as it is just an inconsistency of seq_along(.) with the replace function.
library(dplyr)
rename(data, de=de.y)