I think, therefore I R. William B. King (in his R tutorials)
R is known to be very flexible importing massive amounts of data from numerous different data sources and formats. The most popular data sources and formats are
Text Files: Files including text (ASCII), most commonly tabular
Excel Files: Microsoft Excel files (
Databases: Oracle, PostgreSQL SQLite, etc.
Internet: R as a Web Client
Other: XML, JSON, etc.
R and Excel: History
R has a rather awkward relationship with MS Excel throughout its history. Due to its open-source background the “best practice” approach interacting wich Excel files has long been to export the contents to comma-separated files (CSV). However, this approach requires manual interventions and is far from practical. The RODBC package also allows users to create ODBC connection to MS Excel files.
The complication with MS Excel files is not only their proprietary nature. Although the curent Excel data format is based on open technologies like XML (an Excel file is basically a compressed XML file) it comes with a lot of special cases attached.
Various R packages are able to interact with Excel files. Most of them use external libraries in C++, Java, etc. Especially Java based dependencies can be more difficult to install on specific platforms like in the case of the XLConnect.
A completely different category represents the RExcel package which allows Excel to connect to an R instance through a (DCOM) interface.
There are numerous to interact with Excel from R:
|Transfer through clipboard|
|readxl||Read excel files without external dependencies|
|writexl||Write xlsx files without external dependencies|
|XLConnect, xlsx (a)||Read/Write content through Java library|
|gdata (b)||Read contents through CSV|
|RODBC||Read data through ODBC|
|RExcel (c)||2-way transfer through (D)COM Server|
|openxlsx||Read, Write and Edit XLSX Files|
-(a): Uses on Apache POI Java library - (b): Uses perl bindings to read/write Excel files - (c): Requires external software installation / admin rights