data.table：像神一样操作数据

data.table 是目前圈内最受关注的软件包，提供了便捷的数据处理逻辑以及高效的数据运算性能，尤其是对于处理较大规模的数据，data.table 具有明显的优势。

这是 data.table 的开发主页，可以看出，这个在 10 年前创建的软件包，目前依然处理十分活跃的开发与改进阶段，而且历次的更新均带来更加优秀的处理能力。我直接从项目网页摘取以下几个特征，以管窥豹

优秀特征

• 快速读取数据文件 👉 fast and friendly delimited file reader: ?fread, see also convenience features for small data
• 快速写入数据文件 👉 fast and feature rich delimited file writer: ?fwrite
• 底层支持并行运算(隐式并行) 👉 low-level parallelism: many common operations are internally parallelized to use multiple CPU threads
• 支持大内存数据处理 👉 fast and scalable aggregations; e.g. 100GB in RAM (see benchmarks on up to two billion rows)
• 方便使用 join(这点对于数据分析尤其重要) 👉 fast and feature rich joins: ordered joins (e.g. rolling forwards, backwards, nearest and limited staleness), overlapping range joins (similar to IRanges::findOverlaps), non-equi joins (i.e. joins using operators >, >=, <, <=), aggregate on join (by=.EACHI), update on join
• 使用引用，避免在内存的拷贝消耗 👉 fast add/update/delete columns by reference by group using no copies at all
• fast and feature rich reshaping data: ?dcast (pivot/wider/spread) and ?melt (unpivot/longer/gather)
• any R function from any R package can be used in queries not just the subset of functions made available by a database backend, also columns of type list are supported
• 兼容原生的 data.frame，因此适用所有的软件包 👉 has no dependencies at all other than base R itself, for simpler production/maintenance
• the R dependency is as old as possible for as long as possible and we continuously test against that version; e.g. v1.11.0 released on 5 May 2018 bumped the dependency up from 5 year old R 3.0.0 to 4 year old R 3.1.0