I have been trying to join my data for the last 4 days and finally! Thank you! I have been starting from the way beginning of your videos from 3 years ago. Thank you for sharing and being so detailed and adding extra functions and ideas that someone else may need to use.
pat i love hadley so much for making my hard learned SQL skills relevant again by bringing them into R. As you mentioned, i also like to be explicit and always use the "by" argument, but this is also why i always use left_join. I feel like inner_join hides missing records from me and I want to know things are missing so I can handle those missing entries right away. Obviously you could look for missing data further along in your code but i'd rather just deal with it now. maybe there's a better way that I'm not aware of....
Hi Peter - I'm sorry the link above wasn't working but it is now. You can find it in the original video from this series (ruclips.net/video/qaksmQabMUI/видео.html) or on the github repository at raw.githubusercontent.com/riffomonas/vaccination_attitudes/main/august_october_2020.csv
Would location %in% c(“Australia”, “Brazil”, …) not have worked here? I guess that is mute since you filter with a join later but still good to know that there is a short-cut.
![MISSING: SLIM SHADY [Expanded Mourner’s Edition Trailer]](http://i.ytimg.com/vi/xh8qgHrOO1g/mqdefault.jpg)
I have been trying to join my data for the last 4 days and finally! Thank you! I have been starting from the way beginning of your videos from 3 years ago. Thank you for sharing and being so detailed and adding extra functions and ideas that someone else may need to use.
Im so glad to hear they’ve been helpful!
Super useful explanation. The Anti-join function here is easier than that in SQL. Thanks for the video.
My pleasure! Thanks for watching Timmy
omg thank you!
Amazing explanation! Thank you!!
Thanks for watching Sohila! 🤓
Cool.
Always great.
pat i love hadley so much for making my hard learned SQL skills relevant again by bringing them into R. As you mentioned, i also like to be explicit and always use the "by" argument, but this is also why i always use left_join. I feel like inner_join hides missing records from me and I want to know things are missing so I can handle those missing entries right away. Obviously you could look for missing data further along in your code but i'd rather just deal with it now. maybe there's a better way that I'm not aware of....
Hi Daniel - thanks for watching and writing. I *love* the joins. I get a lot out of seeing how other people use them
Hey Pat I am lost on the way. I want to know where did you come up with the ipsos dataset? I followed the link, I was totally lost on the way.
Hi Peter - I'm sorry the link above wasn't working but it is now. You can find it in the original video from this series (ruclips.net/video/qaksmQabMUI/видео.html) or on the github repository at raw.githubusercontent.com/riffomonas/vaccination_attitudes/main/august_october_2020.csv
The joins are also the way to mimic Excel’s much-loved VLOOKUP function
I feel like I need to do a “Pat relearns Excel” series 😂
超喜欢你的讲解！！^_^
Cool video
Thanks dude
goatttttt
I remember really struggling to get merge to perform a left_join in my pre-tidyverse days
How do you combine two data frames with different column names with the union function
What is the difference between merge(all=TRUE) and full_join()?
The *_join functions are the same functionality as provided by merge, but with a cleaner syntax
Would location %in% c(“Australia”, “Brazil”, …) not have worked here? I guess that is mute since you filter with a join later but still good to know that there is a short-cut.
Both would work