Write a data frame to CSV with base R, readr, or data.table, read it back with the same package, and each one destroys values in at least four of eleven columns, even when the reader is allowed to know the original schema. Leading zeros, the last digits of 18 digit IDs, the Namibian country code, the final bits of most doubles, milliseconds, and an hour on the night the clocks go back all go missing somewhere. Parquet written with arrow came back identical in every column, and pandas read the same file exactly. data.table was still the fastest, so the case for Parquet is correctness rather than speed.