Side by side
csvkit vs data.table
Both stand on data transformation tools. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
Free plan LinuxMacWindows
csvkit offers a broad set of command-line operations for CSV conversion, processing and analysis without a paid tier. Its memory use on some commands and fallible type inference are worth considering with large or varied data.
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Free plan LinuxMacWindows
data.table combines tabular transformations and delimited-file handling in an R package with memory-conscious column updates. Its stated scope makes it a fit for in-memory R workflows rather than binary-file or remote-database manipulation.
Visit data.tableThe facts
| csvkit | data.table | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Not published |
| Runs on | Linux, Mac, Windows | Linux, Mac, Windows |
| Lowest paid plan | Free or on request | Free or on request |
| Plans published | 1 | 1 |
| Maker | Not published | Not published |
| Website | csvkit.readthedocs.io | rdatatable.gitlab.io |
| On data transformation tools | #7 of 37 | #11 of 37 |
csvkit: what it does well
- Free command-line toolkit under the MIT License
- Converts Excel, JSON and fixed-width files to CSV
- Supports CSV queries and PostgreSQL imports
- Available on Linux, macOS and Windows
- Installation documented for pip and Homebrew
What to know first
- Current metadata requires Python 3.10 or newer
- Some tools buffer entire files in memory
- Type inference can occasionally be erroneous
data.table: what it does well
- Supports multiple join types and reshaping
- Reads delimited files from URLs or shell commands
- Writes delimited files with fwrite()
- Changes columns by reference without copies
- Runs on Linux, macOS, and Windows
What to know first
- Requires base R
- Binary formats such as Parquet are out of scope
- On-disk and remote SQL data are out of scope
Alternatives to csvkit Alternatives to data.table The whole list