Add 1 to all numerical values in a dataframe-CodePudding

I am trying to increase the value of all the numbers in a table similar to the one below. Is there any way to do this in R? I am aware this is a very simple task in python.

if(!require(tidyverse)){install.packages("tidyverse");library('tidyverse')}

Gene = sprintf("Gene_%s", rep(10:39))
Cell = sprintf("Cell_%s", rep(10:19))

mat <- matrix(rnorm(10), ncol = 10, nrow = 30)
df <- as.data.frame(mat)
colnames(df) <- Cell
row.names(df) <- Gene
df <- rownames_to_column(df,var = "Gene")
df

I have tried df 1 and get an error:

Error in FUN(left, right): non-numeric argument to binary operator
Traceback:

1. Ops.data.frame(df, 1)
2. eval(f)
3. eval(f)

My desired output is something like this...

example <- df$Cell_10   1
example

However I need to do this for the whole dataframe

CodePudding user response：

The first column is character.

> str(df)
'data.frame':   30 obs. of  11 variables:
 $ Gene   : chr  "Gene_10" "Gene_11" "Gene_12" "Gene_13" ...
 $ Cell_10: num  0.409 1.689 1.587 -0.331 -2.285 ...
 $ Cell_11: num  0.409 1.689 1.587 -0.331 -2.285 ...
 $ Cell_12: num  0.409 1.689 1.587 -0.331 -2.285 ...
 $ Cell_13: num  0.409 1.689 1.587 -0.331 -2.285 ...
 $ Cell_14: num  0.409 1.689 1.587 -0.331 -2.285 ...
 $ Cell_15: num  0.409 1.689 1.587 -0.331 -2.285 ...
 $ Cell_16: num  0.409 1.689 1.587 -0.331 -2.285 ...
 $ Cell_17: num  0.409 1.689 1.587 -0.331 -2.285 ...
 $ Cell_18: num  0.409 1.689 1.587 -0.331 -2.285 ...
 $ Cell_19: num  0.409 1.689 1.587 -0.331 -2.285 ...

So, exclude that while adding

df[-1] <- df[-1]   1

Or programmatically find the index of numeric columns

i1 <- which(sapply(df, is.numeric))
df[i1] <- df[i1]   1

Or in tidyverse, we can check the column type while adding

library(dplyr)
df <- df %>%
       mutate(across(where(is.numeric), ~ .x   1))