data.table vs pandas
data.table
rdatatable.gitlab.iopandas
pandas.pydata.orgSide by side
| Figure | data.table | pandas |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 1 |
| Spec score · Data Transformation Tools | 8.5 (#11) | 7.6 (#26) |
| Dependencies | The project says it has no dependencies other than base R. | pandas requires NumPy and python-dateutil; tzdata is required on Windows and Pyodide. |
| Integrations | data.table is an R package and can use R functions from other packages in queries. | Optional dependencies add features for Excel, SQL databases, cloud storage such as Amazon S3 and Google Cloud Storage, plotting, and other tasks. |
| Support | The project directs users who need help to the data.table community on Stack Overflow. | The website directs users to ask questions on Stack Overflow and provides documentation and community tutorials. |
| Supported systems | The installation guide lists Linux, Mac, and Windows. | The documentation describes installation on Linux, macOS, and Windows. |
Plans
In their own words
data.table
data.table is a free R package providing a high-performance version of base R’s data.frame. Its code interface supports filtering, grouping, aggregation, ordered and rolling joins, overlapping and non-equi joins, reshaping with dcast and melt, and adding, updating, or deleting columns. fread() reads delimited text, including CSV, TSV, compressed .gz and .bz2 files, and can source web URLs or shell commands. fwrite() writes delimited files with an emphasis on speed for large files. Many operations use multiple CPU threads internally. Columns can be changed by reference without copies, and the project reports no external Imports, LinkingTo, or Depends dependencies. Queries can call R functions from other packages. data.table runs on Linux, macOS, and Windows and requires base R. It is self-hosted and licensed under MPL-2.0. The project’s stated scope excludes binary formats such as Parquet and data stored on disk or in remote SQL databases.