Great videos by the way. I like these project-oriented lectures rather than all the other R "gadget" shows that overflow on TH-cam. I suppose it shows the difference between a scientist (one with an actual domain) and all those so-called "Data" Scientists out there (I am still puzzled by the notion that one could be a scientist in data - unless you are simply a statistician). Thanks
Hah! Thanks for watching. I really have no interest in doing function specific episodes 🤓 if you have ideas for other projects I’m very open to ideas that might have a broad interest.
What questions did you still have? R's read functions are nice because they'll allow you to read files directly from the web or from your local computer
Awesome as usual. I have a special request. The plots are based on a relative difference against a specific mean (1951-1980). It would be interesting to see if choosing a different reference period changes things or not and if it does what is the impact. Unfortunately, I haven't been able to find a suitable dataset for that. Do you know any?
Two biggies for me: You can double click on the file and it will open Rstudio to be in the correct working directory and it will save project wide settings
Awesome new playlist, have been looking for such complete project for so long, specifically related to climate data. Thank you Prof
Wonderful - thanks for watching!
Excellent video as always. Many thanks
My pleasure! Thanks for watching 🤓
Great videos by the way. I like these project-oriented lectures rather than all the other R "gadget" shows that overflow on TH-cam. I suppose it shows the difference between a scientist (one with an actual domain) and all those so-called "Data" Scientists out there (I am still puzzled by the notion that one could be a scientist in data - unless you are simply a statistician).
Thanks
Hah! Thanks for watching. I really have no interest in doing function specific episodes 🤓 if you have ideas for other projects I’m very open to ideas that might have a broad interest.
Awesome 😍 Thank you very much
My pleasure! 🤓
Would you please explain some more about 9:33? Ty
What questions did you still have? R's read functions are nice because they'll allow you to read files directly from the web or from your local computer
Hi ! good tutorial. Graphics can be enabled to interactive?
thanks for this project.
Yep! I have a couple videos that use rgl and plotly to make interactive figures.
9:14 why? What would you consider a "too big" file?
I think 50MB is when GitHub starts to complain
Awesome as usual. I have a special request. The plots are based on a relative difference against a specific mean (1951-1980). It would be interesting to see if choosing a different reference period changes things or not and if it does what is the impact. Unfortunately, I haven't been able to find a suitable dataset for that. Do you know any?
I don’t but will keep looking. This group uses 1971-2000 showyourstripes.info/b/globe/. The difference isn’t very remarkable
This is very cool.
🤓
Thanks for the video. What's the point of a Rstudio project other than facilitating version control? Does it provide any additional feature?
Two biggies for me: You can double click on the file and it will open Rstudio to be in the correct working directory and it will save project wide settings
Can you teach us how to do this analysis with the netCDF files which are commonly used for climate data.
Hi is it possible to make same visualization using matplotlib in python?
I assume this work is amazing.
Thanks so much.
Sorry but I don’t know Python
The NASA GISS site looks like it has not been updated for years (or decades)!
Hah! But the data has 😂