Efficiently transform multiple columns of a data frame

Question

I have a data frame, and I want to transform all columns (say, take the logs or whatever) with columns that match a certain name. So in the example below, I want to take the

Answer 1

df <- data.frame(
Y = sample(0:1, 10, replace = TRUE),
X.1 = sample(1:10),
X.2 = sample(1:10),
Z.1 = sample(151:160)
)
df

assuming that you know those variables which requires conversions in the real dataframe (2 and 3 refers to the 2nd and 3rd variables in df which are X.1 and X.2)

df2=log10(df[c(2:3)])
df2

if the variables are far a part in the dataframe you can select them like c(1,3,6,8:10,13) for 1st, 3rd, 6th 8 through 10 and 13th.this works only for numerical variables.

Answer 2

vars <- c("X.1", "X.2")

df[vars] <- lapply(df[vars], log)

Answer 3

In the case of functions that will return a data.frame:

cols <- c("X.1","X.2")
df[cols] <- log(df[cols])

Otherwise you will need to use lapply or a loop over the columns. These solutions will be slower than the solution above, so only use them if you must.

df[cols] <- lapply(df[cols], function(x) c(NA,diff(x)))
for(col in cols) {
  df[col] <- c(NA,diff(df[col]))
}