Chain Operations: An Interesting Feature in dplyr Package

[This article was first published on Yet Another Blog in Statistical Computing » S+/R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.


library(data.table)
library(dplyr)

data1 <- fread('/home/liuwensui/Downloads/2008.csv', header = T, sep = ',')
dim(data1)
# [1] 7009728      29

data2 <- data1 %.%
           filter(Year = 2008, Month %in% c(1, 2, 3, 4, 5, 6)) %.%
           select(Year, Month, AirTime) %.%
           group_by(Year, Month) %.%
           summarize(avg_time = mean(AirTime, na.rm = TRUE)) %.%
           arrange(desc(avg_time))

print(data2)
#   Year Month avg_time
# 1 2008     3 106.1939
# 2 2008     2 105.3185
# 3 2008     6 104.7604
# 4 2008     1 104.6181
# 5 2008     5 104.3720
# 6 2008     4 104.2694


To leave a comment for the author, please follow the link and comment on their blog: Yet Another Blog in Statistical Computing » S+/R.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)