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disregarding
2024 Apr 10
2
Exceptional slowness with read.csv
...[i]]
Unbalanced <- gregexpr('"', y) |>
sapply(\(x) attr(x, "match.length") |> length()) |>
{\(x) (x %% 2L) == 1L}() |>
which()
data.frame(Col = i, Unbalanced = Unbalanced)
}) |>
do.call(rbind, args = _)
}
# read the data disregardin g quoted strings
df1 <- read.csv(fl, quote = "")
# determine which strings have unbalanced quotes and
# where
unbalanced_dquotes(df1)
Hope this helps,
Rui Barradas
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2024 Apr 10
1
Exceptional slowness with read.csv
...39;"', y) |>
> ????? sapply(\(x) attr(x, "match.length") |> length()) |>
> ????? {\(x) (x %% 2L) == 1L}() |>
> ????? which()
> ??? data.frame(Col = i, Unbalanced = Unbalanced)
> ? }) |>
> ? do.call(rbind, args = _)
> }
>
> # read the data disregardin g quoted strings
> df1 <- read.csv(fl, quote = "")
> # determine which strings have unbalanced quotes and
> # where
> unbalanced_dquotes(df1)
>
>
> Hope this helps,
>
> Rui Barradas
>
>
2024 Apr 08
4
Exceptional slowness with read.csv
Greetings,
I have a csv file of 76 fields and about 4 million records. I know that
some of the records have errors - unmatched quotes, specifically.?
Reading the file with readLines and parsing the lines with read.csv(text
= ...) is really slow. I know that the first 2459465 records are good.
So I try this:
> startTime <- Sys.time()
> first_records <- read.csv(file_name, nrows