Add a Prefix to Column Names

Add a prefix to column names

You have misread the help file. Here's the argument to look at:

do.NULL: logical. If FALSE and names are NULL, names are created.

Notice the and in that description. Your names are no longer NULL, so using prefix won't work.

Instead, use something like this:

> m2 <- cbind(1,1:4)
> colnames(m2) <- c("x","Y")
> colnames(m2) <- paste("Sub", colnames(m2), sep = "_")
> m2
     Sub_x Sub_Y
[1,]     1     1
[2,]     1     2
[3,]     1     3
[4,]     1     4

How to add a suffix (or prefix) to each column name?

You can use a list comprehension:

df.columns = [str(col) + '_x' for col in df.columns]

There are also built-in methods like .add_suffix() and .add_prefix() as mentioned in another answer.

How to add prefix to column names except some columns?

Another option, use list comprehension on the dataframe column header object, this way you aren't manipulating nor copying the entire dataframe:

df.columns = [f'new_{i}' if i not in ['Name', 'Id'] else f'{i}' for i in df.columns]

df

Output:

   Id    Name  new_Age new_Status
0   1    Alex       22     single
1   2     Bob       32    married
2   3  Clarke       23     single

How to add prefix to column name according to data in another column

Try this:

import pandas as pd

data = {
    'ID': [1, 2, 3, 4, 5, 6, 7, 8],
    'LABEL': ['text', 'logo', 'logo', 'person', 'text', 'text', 'person', 'logo'],
    'cluster_label': ['c_0', 'c_0', 'c_0', 'c_1', 'c_1', 'c_2', 'c_2', 'c_3']
}

df = pd.DataFrame(data)

pd.get_dummies(df,columns=['cluster_label'])



df['dummy'] = df.apply (lambda row: row['LABEL']+'_'+row['cluster_label'], axis=1)

pd.get_dummies(df['dummy'])

## If you want to keep ['ID','LABEL','cluster_label'] in your df :
df = df.join(pd.get_dummies(df['dummy']))

Add prefix to the columns in a slice of the dataframe

You cannot directly assign a prefix as you are currently doing it, given that indices do not support mutable operations. So you would have to reassign all columns again. Here's one way to do it with a list comprehension:

df.columns = ['f_' + i if ix < 15 else i for ix, i in enumerate(df.columns)]

Adding a prefix to certain column names

Try this:

colnames(m2)[1] <- paste0("Sub", "_", colnames(m2)[1])
# or if you prefer paste
#colnames(m2)[1] <- paste("Sub", colnames(m2)[1], sep = "_")

Adding prefix to specific R columns

You aren't obliged to use grepl(). It's possible to use gsub() instead. Since gsub() if no match found, returns unchanged values, you can change your column names on the fly, without intermediate indexing step:

Example data set

sed.seed(66248086) 

(
  dat <- data.frame(
    ID         = 1:3,
    EXPFRQ     = runif(3),
    EXPMETADAT = sample(c(T, F), 3, T),
    .EXPGRP    = sample(LETTERS[1:3], 3, T),
    EXPOUT     = sample(c('*', '**', '***'), 3, T),
    NOTES      = c("Bad project...", "What is in this tube?", "Blot, blot western baby")
    )
  )

#   ID       EXPFRQ EXPMETADAT .EXPGRP EXPOUT                   NOTES
# 1  1 0.5483680151      FALSE       C      *          Bad project...
# 2  2 0.0628816469      FALSE       B     **   What is in this tube?
# 3  3 0.0001267055       TRUE       B    *** Blot, blot western baby

Actually where renaming takes place

Just give to gsub() your pattern, and call the chunk it found using back-reference (\\1):

colnames(dat) <- gsub('^(EXP[A-Z]{3})$', 'New_\\1', colnames(dat))

Result

dat

#   ID   New_EXPFRQ EXPMETADAT .EXPGRP New_EXPOUT                   NOTES
# 1  1 0.5483680151      FALSE       C          *          Bad project...
# 2  2 0.0628816469      FALSE       B         **   What is in this tube?
# 3  3 0.0001267055       TRUE       B        *** Blot, blot western baby

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Note: Please, reade the note written by @akrun under his answer!

Adding a numbered prefix to column names in a for loop

Put them in a list and use their name (df1, df2, etc...)to catch the prefix, i.e.

l1 <- mget(grep(pattern = "df[0-9]+", x = ls(), value = TRUE))
Map(function(x, y) setNames(x, paste0('MTH', gsub('\\D+', '', y), '_', names(x))), 
    l1, names(l1))

$df1
  MTH1_v1 MTH1_v2
1       5       9
2       6      10
3       7      11

$df2
  MTH2_v1 MTH2_v2
1      15      19
2      16     110
3      17     111

To change all names except the first one then,

Map(function(x, y) data.frame(x[1], setNames(x[-1], paste0('MTH', gsub('\\D+', '', y), '_', names(x)[-1]))), l1, names(l1))

$df1
  v1 MTH1_v2
1  5       9
2  6      10
3  7      11

$df2
  v1 MTH2_v2
1 15      19
2 16     110
3 17     111

DATA

dput(df1)
structure(list(v1 = c(5, 6, 7), v2 = c(9, 10, 11)), class = "data.frame", row.names = c(NA, 
-3L))
dput(df2)
structure(list(v1 = c(15, 16, 17), v2 = c(19, 110, 111)), class = "data.frame", row.names = c(NA, 
-3L))

Adding a suffix to a selection of column names in tidyverse

You may select columns in rename_with -

library(dplyr)

df %>% rename_with(~paste0("a", .x), c(x, y))

#  ax ay z
#1  1  3 5
#2  2  4 6

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