raveio (version 0.9.0)

safe_read_csv: Read comma separated value files with given column classes

Description

Read comma separated value files with given column classes

Usage

safe_read_csv(
  file,
  header = TRUE,
  sep = ",",
  colClasses = NA,
  skip = 0,
  quote = "\"",
  ...,
  stringsAsFactors = FALSE
)

Value

A data frame

Arguments

file, header, sep, colClasses, skip, quote, stringsAsFactors, ...

passed to read.csv

Details

Reading a comma separated value file using builtin function read.csv might result in some unexpected behavior. safe_read_csv does some preprocessing on the format so that it take cares of the following cases.

1. If skip exceeds the maximum rows of the data, return a blank data frame instead of raising error.

2. If row names are included in the file, colClasses automatically skip that column and starts from the second column

3. If length of colClasses does not equal to the number of columns, instead of cycling the class types, we set those columns to be NA type and let read.csv decide the default types.

4. stringsAsFactors is by default FALSE to be consistent with R 4.0, if the function is called in R 3.x.

Examples

f <- tempfile()
x <- data.frame(a = letters[1:10], b = 1:10, c = 2:11)

# ------------------ Auto-detect row names ------------------
# Write with rownames
utils::write.csv(x, f, row.names = LETTERS[2:11])

# read csv with base library utils
table1 <- utils::read.csv(f, colClasses = c('character', 'character'))

# 4 columns including row names
str(table1)

# read csv via safe_read_csv
table2 <- safe_read_csv(f, colClasses = c('character', 'character'))

# row names are automatically detected, hence 3 columns
# Only first columns are characters, the third column is auto
# detected as numeric
str(table2)

# read table without row names
utils::write.csv(x, f, row.names = FALSE)
table2 <- safe_read_csv(f, colClasses = c('character', 'character'))

# still 3 columns, and row names are 1:nrow
str(table2)

# --------------- Blank data frame when nrow too large ---------------
# instead of raising errors, return blank data frame
safe_read_csv(f, skip = 1000)