I demonstrate how to use dplyr for data manipulation in R (R code and data on GitHub ). I had heard of the package before and finally gave it a try after attending Hadley Wickham's presentation at useR! in LA a couple of months ago. dplyr will change your life as it relates to data manipulation!
There are plenty of other R blogs out there, but I wanted to cover practical statistics topics in video format. Video lectures got me through my dissertation and I want to repay some of the favor. If you have a good idea for a video or need some help, let me know!
nice intro
ReplyDeleteNice job! I didn't catch if you used the minus sign on a numeric variable or not, but it might only work on numeric. The desc() function would arrange the variable in descending order regardless of variable type (ascending is the default).
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Keep up the good work!
Nice. Thanks.
ReplyDeleteGreat video! I have been using sqldf to do this type of data manipulation but maybe I should switch to dplyr.
ReplyDeleteThanks, Paul! Yeah, this is way better than sqldf. How could I forget to mention the joins? Check out ?left_join and you'll never need to use merge() or the sqldf package again.
DeleteGreat overview of a fantastic package. Love dplyr. And your succinct and super-short explanation belies just what a game changer this is. thanks. well done.
ReplyDeleteThat was great. Appreciate the effort, nice and concise.
ReplyDeleteThanks, very nice video.
ReplyDeleteI didn't see how, in your example, using dplyr helped with ggplot. However, you could have used the "pipe" operator %>% instead of + (but I'm not sure why it would be "better").
I was trying to make the ggplot work without dplyr, but I wasn't able to do so. One of the main reasons I prefer dplyr is to have the flexibility of storing the summary data in a data frame - after the object has been created, you could make a table, a bar graph, or a line graph to present the data minimal extra work.
DeleteYeah, dplyr has been super hot in the R blogosphere lately! I haven't watched that yet but I'll check it out - looks very in depth.
ReplyDeleteThis comment has been removed by the author.
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