I put together a quick comparison of supported features between CSVFiles.jl & CSV.jl:
| CSV.jl | CSVFiles.jl | |
|---|---|---|
Char delimiters |
 |
|
String delimiters |
|
|
| Space delimiter | |
|
| Ignoring any repeated delimiter (fix-width files) | |
|
Char quote characters |
|
|
| Separate open/close quote characters | |
|
| escape characters | |
|
| skip rows to parse | |
|
| limit rows to parse | |
|
| handle files without header row | |
|
| manually provide column names | |
|
| specify arbitrary row or range of rows for column headers | |
|
| specify # of rows to use for type inference | |
|
| automatically sample entire file for type inference | |
|
| manually specify column types by index or name | |
|
| parse all columns of one type as another | |
|
| specify arbitrary missing value strings | |
|
| transform column names into valid julia identifiers | |
|
| specify arbitrary row where “data” begins | |
|
| skip parsing # of rows at end of file | |
|
| specify comment character/string to ignore commented rows | |
|
| read a file transposed (rows as columns, columns as rows) | |
|
support alternative decimal separator characters (3.14 vs. 3,14) |
|
|
specify arbitrary values to parse as true or false Bool values |
|
|
auto detect and parse columns as CategoricalArray
|
|
|
option to ignore invalid values (replaced with missing) |
|
|
| ability to selectively parse specific columns | |
|
| ability to apply arbitrary scalar transform functions while parsing | |
CSV.jl has been around for a long time now (started May 2015) vs. CSVFiles.jl (June 2017), and developed a ton of requested features. Please chime in if there’s anything missing!