CODEWITHSUNDEEP
r
jypst2003
jypst2003

Reputation: 131

Error in mutate_impl(.data, dots) : binding not found

I would like to combine several of my files into one file. I found the codes from one of the post in the website and adapted it to my own use as followed:

library(dplyr)
library(readr)

df2 <- list.files(pattern = "test_.*\\.csv",full.names = TRUE) %>% 
  lapply(read_csv) %>% 
  bind_rows %>% 
  transmute(Isolate=Iso,
            Condit=Condit,
            rep=rep,
            set=set,
            hpi=hpi,
            OD=OD)

But I get this error:

Error in mutate_impl(.data, dots) : binding not found: 'Iso'

I don't understand why. Could somebody help me?

Thanks a lot!

The input file 1: test_.1.csv

    Iso rep set Condit  hpi OD
1   A22.1   1   3   T27 84  0.232
2   A22.1   2   3   T27 84  0.23
3   A22.1   3   3   T27 84  0.214
4   D2.1    1   3   T27 84  0.049
5   D2.1    2   3   T27 84  0.054
6   D2.1    3   3   T27 84  0.049

The input file 2: test_.2.csv

    Iso rep set Condit  hpi OD
1   A22.1   1   3   T27 72  0.191
2   A22.1   2   3   T27 72  0.186
3   A22.1   3   3   T27 72  0.179
4   D2.1    1   3   T27 72  0.048
5   D2.1    2   3   T27 72  0.053

Upvotes: 3

Views: 10655

Answers (1)

Uwe
Uwe

Reputation: 42544

I've run your code and got the same error message

Error: binding not found: 'Iso'

Reason for this seems to be read_csv from the readr package. When used to read a single file, 

read_csv("test_.1.csv")

returns:

Parsed with column specification:
cols(
  `Iso   rep set Condit  hpi OD` = col_character()
)
# A tibble: 6 × 1
  `Iso   rep set Condit  hpi OD`
                           <chr>
1  A22.1   1   3   T27 84  0.232
2   A22.1   2   3   T27 84  0.23
3  A22.1   3   3   T27 84  0.214
4  D2.1    1   3   T27 84  0.049
5  D2.1    2   3   T27 84  0.054
6  D2.1    3   3   T27 84  0.049

So, read_csv apparently doesn't know how to split the lines into columns.

The code below using fread() and rbindlist() from the data.table package works for me. It changes the name of the Iso column as requested by the OP. In addition, it adds a column indicating the origin of each row.

file_names <- list.files(pattern = "test_.*\\.csv", full.names = TRUE)
library(data.table)
df2 <- 
  rbindlist(
    lapply(file_names, fread), idcol = "file_id"
  )[, file_id := basename(file_names)[file_id] # add origin
    ][, setnames(.SD, "Iso", "Isolate")] # rename one column

df2
#        file_id Isolate rep set Condit hpi    OD
# 1: test_.1.csv   A22.1   1   3    T27  84 0.232
# 2: test_.1.csv   A22.1   2   3    T27  84 0.230
# 3: test_.1.csv   A22.1   3   3    T27  84 0.214
# 4: test_.1.csv    D2.1   1   3    T27  84 0.049
# 5: test_.1.csv    D2.1   2   3    T27  84 0.054
# 6: test_.1.csv    D2.1   3   3    T27  84 0.049
# 7: test_.2.csv   A22.1   1   3    T27  72 0.191
# 8: test_.2.csv   A22.1   2   3    T27  72 0.186
# 9: test_.2.csv   A22.1   3   3    T27  72 0.179
#10: test_.2.csv    D2.1   1   3    T27  72 0.048
#11: test_.2.csv    D2.1   2   3    T27  72 0.053

Upvotes: 2

Related Questions