Memory used by read_xlsx

tidyverse
1

I have 4 xlsx files that I imported into R using read_xlsx, but they left something on the memory and I don't know if it is a known problem or am I doing something wrong. My code is simple

library(readxl)
list <- list(
  file1 = read_xlsx("file1.xlsx"),
  file2 = read_xlsx("file2.xlsx"),
  file3 = read_xlsx("file3.xlsx"),
  file4 = read_xlsx("file4.xlsx")
)

The files are small (60.8MB, 0.8MB, 1.1MB and 61.1MB) but look at the memory report before and after the execution:

memory
memory573×524 60.9 KB

Here is my sessionInfo():

> sessionInfo()
R version 4.1.1 (2021-08-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.3 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=pt_BR.UTF-8       LC_NUMERIC=C               LC_TIME=pt_BR.UTF-8       
 [4] LC_COLLATE=en_US.UTF-8     LC_MONETARY=pt_BR.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=pt_BR.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
[10] LC_TELEPHONE=C             LC_MEASUREMENT=pt_BR.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] readxl_1.3.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.7       fansi_0.5.0      utf8_1.2.2       crayon_1.4.1     cellranger_1.1.0
 [6] lifecycle_1.0.1  magrittr_2.0.1   pillar_1.6.2     rlang_0.4.11     stringi_1.7.4   
[11] rematch_1.0.1    vctrs_0.3.8      ellipsis_0.3.2   tools_4.1.1      stringr_1.4.0   
[16] compiler_4.1.1   pkgconfig_2.0.3  tibble_3.1.4    
``
2

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