Hello,

I'm seeing two obvious errors, those are not csv files and the columns spec is wrong, you have a spec of 6 columns but the posted data only has 4 and of different classes.

If the data is in comma separated values (CSV) files the following worked without errors.


library(readr)

col_spec <- cols(
  d1 = col_double(),
  d2 = col_double(),
  d3 = col_double(),
  d4 = col_double()
)

list.files(pattern = "*\\.csv$") |>
  lapply(read_csv, col_types = col_spec) |>
  dplyr::bind_rows()


If the data is like in the question, try instead


list.files(pattern = "*\\.csv$") |>
  lapply(read_delim, delim = " ", col_types = col_spec) |>
  dplyr::bind_rows()


Hope this helps,

Rui Barradas

Às 00:17 de 02/06/2022, Bhaskar Mitra escreveu:
Hello Everyone,

I have a bunch of csv files, all with common headers (d1, d2, d3, d4).
When I am trying to join the csv files together, with the following code
(shown below),
I am getting a warning  when the files are joined. The values under columns
d3 and d4 are not joined properly.

The code and the error are given below. I would really appreciate some help
in this regard.

regards,
bhaskar


#---code--------------------------------

df <- list.files(pattern = "*.csv") %>%
   lapply(read_csv) %>%
   bind_rows

#---code--------------------------------

Header of each file:

d1  d2  d3  d4
3   4    NA   NA
4   5   NA   7
5   6   8   8
6   7   8   NA

#--------------------------------------------------------

#Warning when the codes run --------------------------------------

Column specification
─────────────────────────────────────────────────────────────────────────────────────────────────────────────────
cols(
   .default = col_double(),
   name = col_character(),
   d1 = col_datetime(format = ""),
   d2 = col_character(),
   d3 = col_logical(),
   d4 = col_logical()
)

Warning: 48766 parsing failures.
* row*    *col*          * expected  *                         *actual*
      *file*
3529   d3           1/0/T/F/TRUE/FALSE       100             'file1.csv'
3529   d4            1/0/T/F/TRUE/FALSE      100             'file1.csv'

.... ..... .................. ...... ................................

        [[alternative HTML version deleted]]

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