7+ years after your video publication, and yet one of the most elucidating videos that a beginner like me would ever wish to watch and learn. Beautifully presented, thank you very much.
This primer on ggplot is far superior to anything I found so far. now that I understand the framework for using qplot and ggplot, I feel much more confident to explore more advanced features of the package. Thank you!
Hi Roger. This has got to be one of the best introductions to ggplot I've seen so far. Finally someone's explained the logic behind the variables. Thank you for that. Now I'm finally not "scared" of using ggplot2 anymore. Great stuff. Any more videos planed on other ggplot functions (boxplots etc.?)
Thanks for this video, and more generally for your ongoing efforts to share your knowledge with others in the R community. Whether it's the content here on You Tube, or the Not So Standard Deviations Podcast that you do with Hilary, you always keep things interesting. Kudos, Rog'!
Please is there a way to have the maacs data set. I am interested in sharing the tutorials with graduate students. Thank you Roger. Due o you I am progressing on my data skills
Hallo Roger. I tried to find the "maacs" table to work this tutorial with you but I only found the article. Could you tell me please how do I obtain the data? Thank you
Thanks for the nice video. Seeing that most of the points were far outside the confidence interval of the smoothers, made me wonder how to interpret this. Does this mean that if I´d repeat the experiment with the same number of observations, I ll have a 95% chance of having a regression within the confidence interval? What if I´d look at only one random Baltimore child (1 observation), would the probability that its NocturnalSymp would be in the confidence interval, still be 95%?
No. With smoothing you are sacrificing some statistical accuracy in order to get a trend line in form of a smoothed function (instead of points). The confidence intervals represent how sure you can be about this general trend based on some simplifying assumptions (these vary for each method) and the data. That is why the CI widens dramaticly when you have less observations.
Hi, I was wondering if anyone could help. I have made 8 (a1,...,a8) variables as various ggplot and I want to display them all on a 2x4 grid. I can't find a way to do this having used ggplot to make my plots. Any thought would be appreciated, thanks.
I want to draw a multifaceted diagram using "mpg" for the factors "cty" and "hey". Facet factor= dev 1) how to draw a multifaceted diagram with color 2) How to add multiple plot Syntex in vim file
7+ years after your video publication, and yet one of the most elucidating videos that a beginner like me would ever wish to watch and learn. Beautifully presented, thank you very much.
This primer on ggplot is far superior to anything I found so far. now that I understand the framework for using qplot and ggplot, I feel much more confident to explore more advanced features of the package. Thank you!
Hi Roger. This has got to be one of the best introductions to ggplot I've seen so far. Finally someone's explained the logic behind the variables. Thank you for that. Now I'm finally not "scared" of using ggplot2 anymore. Great stuff. Any more videos planed on other ggplot functions (boxplots etc.?)
i agree!
totally
One of the OG's of youtube Data Science! I salute you, man.
Extremely insightful and clear!!
THANK YOU Roger Peng from the bottom of my heart!
Thanks for this video, and more generally for your ongoing efforts to share your knowledge with others in the R community. Whether it's the content here on You Tube, or the Not So Standard Deviations Podcast that you do with Hilary, you always keep things interesting. Kudos, Rog'!
Wow. Never knew the difference between putting color in or outside of the aes. I would always just play with it. You're so profoundly good
Great tutorial. Exactly what I was looking for. Followed along and made a great plot, thanks!!
Both the ggplot2 videos are very helpful. Thanks a lot.
Very good video. Thanks for the comprehensive explanation and intro into the grammar of graphics paradigm 👍
Really excellent explanations. You think like a mathematician. Thank you!
Fantastic tutorials! Thank you so much!
Helped me a great deal in my bachelor thesis!
Thank you very much !! It's an awesome series !
Very useful lesson. Thanks.
Thank you.Great video on how to understand the ggplot in modular basis
Great job - very helpful. Are the default confidence bands 95% confidence intervals?
Great tutorial and a great start into the magic world of ggplot2!
Many thanks!
thanks, great introduction which motivates to learn more abot it!
Please is there a way to have the maacs data set. I am interested in sharing the tutorials with graduate students. Thank you Roger. Due o you I am progressing on my data skills
Hallo Roger. I tried to find the "maacs" table to work this tutorial with you but I only found the article. Could you tell me please how do I obtain the data? Thank you
Roger...you are the best! Thank you
Thanks for the nice video. Seeing that most of the points were far outside the confidence interval of the smoothers, made me wonder how to interpret this.
Does this mean that if I´d repeat the experiment with the same number of observations, I ll have a 95% chance of having a regression within the confidence interval? What if I´d look at only one random Baltimore child (1 observation), would the probability that its NocturnalSymp would be in the confidence interval, still be 95%?
No. With smoothing you are sacrificing some statistical accuracy in order to get a trend line in form of a smoothed function (instead of points). The confidence intervals represent how sure you can be about this general trend based on some simplifying assumptions (these vary for each method) and the data. That is why the CI widens dramaticly when you have less observations.
Thank you so much!
Excellent tutorial - thanks man.
great video...both part 1 & 2... is the code used for the presentation available
Outstanding intro to ggplot(). Well done! If it were possible I’d give you 10 likes.
Nice tutorial thanks. Learned something new.
Thank you Roger Peng, very helpful
Hi, I was wondering if anyone could help. I have made 8 (a1,...,a8) variables as various ggplot and I want to display them all on a 2x4 grid. I can't find a way to do this having used ggplot to make my plots. Any thought would be appreciated, thanks.
Thank you very much indeed :) Brilliant *****
Great tutorial, but where is the dataset for Part 2?
getwd()
dir.create("ZapocetSk")
fileURL = "slovakkhl.sk/index.php?page=kanadske-bodovanie"
library(XML)
temp = htmlParse(fileURL)
tabs = readHTMLTable(temp,stringAsFactor = TRUE, header = TRUE)
tabs
hraci = tabs[[1]][c(2:10),]
hraci
names(hraci)[4] = c("ttttm")
hraci
as.numeric(hraci$G) ## netusim vobec ci sa to zmenilo
hraci[order(hraci$G, decreasing = TRUE),]
Sir, it’s ok to subscript but if I want superscript in my labels then how can o do?
Thank you!
Thanks!
Congrats! Keep it up
Thanks !!!
Where can I download these slides??? Thank you
I want to draw a multifaceted diagram using "mpg" for the factors "cty" and "hey". Facet factor= dev
1) how to draw a multifaceted diagram with color
2) How to add multiple plot Syntex in vim file
This is a great tutorial, thanks
thank you, very helpful.
thanks for sharing the data Parvane.
Use Poisson regression, not simple linear regression for the analysis!
Thanks
Hi! How to get maacs data set?
Ditto. Can't follow along without it. Couldn't find on the course forums or via Google.
Its in the MASS package...
i cant see it in the Mass package, what is the exact name of the data set?
where in the Mass package
raw.githubusercontent.com/rdpeng/artofdatascience/master/manuscript/data/bmi_pm25_no2_sim.csv
The 6 people who hit thumbs down obviously misclicked.
Perfect.
11:02 "low ass smoother"
Sorry, I had to. Nice tutorial, though! :)
How do I get maacs data ?
raw.githubusercontent.com/rdpeng/artofdatascience/master/manuscript/data/bmi_pm25_no2_sim.csv
maacs
maacs file I have downloaded does not have these variables...can anyone please post the link
github.com/rdpeng/artofdatascience/blob/master/manuscript/data/bmi_pm25_no2_sim.csv
maacs
Data & the lecture is not easy to follow, need to spend time on how to get data & work with it
thank you very much!
Hi! How to get maacs data set?