Thanks for the example code, it actually has me wondering whether using the pipes has any impact on performance. They are much easier to read than the nested fu

Thanks for the example code, it actually has me wondering whether using the pipes has any impact on performance. They are much easier to read than the nested function calls that would be used instead. However, I mean I just searched for an R script on kaggle and the first I found is this: https://www.kaggle.com/bpavlyshenko/grupo-bimbo-inventory-demand/bimbo-xgboost-r-script-lb-0-457/output https://www.kaggle.com/bpavlyshenko/grupo-bimbo-inventory-de... From my experience that is a typical example (data.table is very common, but not so much dplyr and the pipes). I looked through the recent/featured questions on stack overflow and cross validated and saw only "old school" R as well. For example: http://stats.stackexchange.com/questions/228800/ http://stats.stackexchange.com/questions/228800/