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To add your package to this list, please [submit a Pull Request to The Raft](https://github.com/rdatatable-community/The-Raft/), making sure to follow the templated instructions.
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## Extension packages: Add to the internal functionality of `data.table`
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## Extension packages
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Adds to the internal functionality of `data.table`.
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-[nc](https://github.com/tdhock/nc): Named capture regular expressions for text parsing and data reshaping.
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## Application packages: Use `data.table` to accomplish a particular task or analysis.
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## Application packages
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Uses `data.table` to accomplish a particular task or analysis.
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-[mlr3](https://github.com/mlr-org/mlr3): A versatile machine learning framework built on data.table.
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## Bridge package: Translate data.table syntax to different syntax or provides helper functions for transitioning between `data.table` and another object type.
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## Bridge packages
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Translates `data.table` syntax to a different syntax, or provides helper functions for transitioning between `data.table` and another object type.
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-[tidyfast](https://github.com/TysonStanley/tidyfast): Fast and efficient alternatives to tidyr functions built on `data.table`.
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-[tidyfast](https://github.com/TysonStanley/tidyfast): Fast and efficient alternatives to tidyr functions built on data.table
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-[dtplyr](https://github.com/tidyverse/dtplyr): A `data.table` backend for `dplyr`.
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-[dtplyr](https://github.com/tidyverse/dtplyr): A `data.table` backend for `dplyr`
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## Partner packages
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## Partner package: Not necessarily directly connected to `data.table`, but deliberately follows the [core philosophies of `data.table`](https://github.com/Rdatatable/data.table/blob/master/GOVERNANCE.md#the-r-package).
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Not necessarily directly connected to `data.table`, but deliberately follows the [core philosophies of `data.table`](https://github.com/Rdatatable/data.table/blob/master/GOVERNANCE.md#the-r-package).
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-[collapse](https://github.com/SebKrantz/collapse): Advanced and Fast Data Transformation in R
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-[collapse](https://github.com/SebKrantz/collapse): Advanced and Fast Data Transformation in R.
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