Error in function to normalize data applied to a data frame

Question

I have downloaded the bike-sharing-dataset from the UCI Machine learning repository and am trying to implement a multivariate linear regression in R. Here is the format of the data:

> head(data1)
  season mnth hr holiday weekday workingday weathersit temp  atemp  hum windspeed cnt
1      1    1  0       0       6          0          1 0.24 0.2879 0.81    0.0000  16
2      1    1  1       0       6          0          1 0.22 0.2727 0.80    0.0000  40
3      1    1  2       0       6          0          1 0.22 0.2727 0.80    0.0000  32
4      1    1  3       0       6          0          1 0.24 0.2879 0.75    0.0000  13
5      1    1  4       0       6          0          1 0.24 0.2879 0.75    0.0000   1
6      1    1  5       0       6          0          2 0.24 0.2576 0.75    0.0896   1

I am trying to normalize specific columns (that have not already been normalized) with the following function:

normalize <- function(x) {
  return ((x - min(x)) / (max(x) - min(x)))
}

The problem is that when I run:

 dfNorm <- as.data.frame(lapply(data1["season", "mnth", "hr", "weekday", "weathersit"], normalize)) 

I get the following error:

Error in [.data.frame (data1, "season", "month", "hour", "weekday", "weathersit") : unused arguments ("weekday", "weathersit")

Why am I getting this error and how can I fix it?

Answer 1

To modify in-place, I'd use dplyr::mutate . Something like this should work:

library(dplyr)
dfNorm <- data1 %>% 
  mutate_at(.vars = vars(season, mnth, hr, weekday, weathersit),
            .funs = funs(normalize))

Answer 2

Simply assign the lapply to new columns:

df[c("season_norm", "mnth_norm", "hr_norm", "weekday_norm", "weathersit_norm")] <-
   lapply(df[c("season", "mnth", "hr", "weekday", "weathersit")], normalize)