Hello, As far as I know, there is no such automatic way. But you can define data_id variables per dataset before combining them. Here is an example: #define data id variables iris$dt_id
Hi Himani, missing data is usually not a problem for cbind/rbind. You can merge your data with cbind/rbind, even when it contains missing values. However, if you want to lean more about the treatment of missing values in your data frame you can have a look at the following tutorials: statistical-programming.com/complete-cases-in-r-example/ ; statistical-programming.com/predictive-mean-matching-imputation-method/
Thank you. You explain clearly so a novice understands.
Thank you very much for your kind comment! 🙂
i'm subscribing to anyone that produces good help vids like this one. the basics are really good to have explained so clearly
Thanks a lot for this wonderful feedback Alex, and for subscribing! :)
You are doing a great job ...👍
Thank you so much Sudhir, I'm very happy about your constant positive feedback! :)
Thank so much! your video is extremely useful, especially the Rbind.fill function explanation.
Thank you! Glad it was helpful!
Thank you!
Thanks for the kind comment, glad you like it!
is it possible to automatically create a new variable in the merged data that indicates witch data each row came from originally?
Hello,
As far as I know, there is no such automatic way. But you can define data_id variables per dataset before combining them. Here is an example:
#define data id variables
iris$dt_id
Helpful! :)
Glad you think so! :)
Please make some video with data and live example
This is definitely planned for the future, I cannot promise when I will find the time for it, but I'll keep you updated :)
@@StatisticsGlobe thanks
Thank you for the great video!
It was helpful.
Thank you Laszlo, nice to hear that
Good lesson. Good english, relatively poor mine. I don't know deutsch, but diction sounds like deutsch from Hessen Frankfurt.
Haha yes, I was born about 1.5 hours away from Frankfurt :) Glad to hear that you liked the video!
Thanks
Thanks for the kind comments Vincenzo!
here are your like and comment, but wouldnt you mind next time to be shorter?
Hey Vadim, thanks for the like! Would you mind explaining what you mean with shorter? Regards, Joachim
How can i handle missing data frame in cbind/rbind
Hi Himani, missing data is usually not a problem for cbind/rbind. You can merge your data with cbind/rbind, even when it contains missing values. However, if you want to lean more about the treatment of missing values in your data frame you can have a look at the following tutorials: statistical-programming.com/complete-cases-in-r-example/ ; statistical-programming.com/predictive-mean-matching-imputation-method/