It's obvious you have experience teaching! Organized and clear instructions. Thank you! I said I would use python next but your videos and something about R keep me wanting to stick with it. Do you use Python for any specific tasks?
great video! I am so grateful you have taken the time to put these videos together! love your approach. Thank you, this is really great! I am a fan (as you can probably tell by now)
I learned so much! Just started using dplyr a couple days ago and wanted something comprehensive on basics. So much to learn, it's not too difficult either.
Thank you so much!! it's so useful; Even I took stat course in my university, the professor never taught us how to wangle data! This video is so useful!🤩
I love your work. Thank you so much for your great videos. Please, keep up the great work and I would like to ask you if you can make a tutorial on the lubridate package and dealing with dates in R. It's so underrated package despite the great importance of dates variables in data science..
Hi, Do you have any plans on doing a video on best practices for R markdown? I'm trying to learn about chunks, blocks, knitr via other online resources and its kind of confusing me. PS really appreciate your time and effort for these, I'm going for a career change and its really giving me confidence that I can do this
Thank you! In addition I see nice feature. After changing a variable - we look at it by View() command... but if I do some changes one more time I can change a page were I've already call a variable and I can see new changes without calling View() once again.
@@EquitableEquations Exactly, I have fallen in love with R due to tidyverse. The tidyverse feels like another language on its own. More of a Python way of writing R code
You're awesome. I heard to come back here, having watched one of your videos; learning R in 39 minutes. I have a question please I'm doing the data analysis for my research titled; modeling of selected classification methods and comparison of their performance in the classification of anaemia patients among Nigerian children. Now, I've not been using much of R before this work. So I ran into an issue with my dataset. I have one on of my predictor variables to be continuous. When I declared its class in R as numeric, all values for that variable were overwritten as NAs. I can't start checking each cell because there are almost 11,000 observations. How do I fish out where the problem is?
You're awesome. I heard to come back here, having watched one of your videos; learning R in 39 minutes. I have a question please I'm doing the data analysis for my research titled; modeling of selected classification methods and comparison of their performance in the classification of anaemia patients among Nigerian children. Now, I've not been using much of R before this work. So I ran into an issue with my dataset. I have one on of my predictor variables to be continuous. When I declared its class in R as numeric, all values for that variable were overwritten as NAs. I can't start checking each cell because there are almost 11,000 observations. How do I fish out where the problem is?
You can find materials supporting this vid (and others) at github.com/equitable-equations/youtube.
Your instructions are very understandable and detailed. I have gained a great deal of knowledge from your lessons. Thank you very much 🙏
It's obvious you have experience teaching! Organized and clear instructions. Thank you! I said I would use python next but your videos and something about R keep me wanting to stick with it. Do you use Python for any specific tasks?
great video! I am so grateful you have taken the time to put these videos together! love your approach. Thank you, this is really great! I am a fan (as you can probably tell by now)
Thanks KK! Glad you're around.
Just wanted to say this was awesome. Great energy and instruction. You got yourself a new sub today!
I learned so much! Just started using dplyr a couple days ago and wanted something comprehensive on basics. So much to learn, it's not too difficult either.
Really enjoy your presentations. Being new to R this has been really helpful
as usual very amazing useful quick Revision
thank you so much sir
This has been really helpful. Thanks
Very clear and helpful. Thank you for taking the time to create great content!
Great video, really appreciate you making this!
Very clear and helpful videos. Thank you very much! Muchas gracias!!! 😊
Your content is amazing. Thank you so much,
Amazing vídeo, thanks!
Thank you so much!! it's so useful; Even I took stat course in my university, the professor never taught us how to wangle data! This video is so useful!🤩
I love your work. Thank you so much for your great videos. Please, keep up the great work and I would like to ask you if you can make a tutorial on the lubridate package and dealing with dates in R. It's so underrated package despite the great importance of dates variables in data science..
HI! This is definitely on my to-do list. Fabulous package.
Hi,
Do you have any plans on doing a video on best practices for R markdown? I'm trying to learn about chunks, blocks, knitr via other online resources and its kind of confusing me.
PS really appreciate your time and effort for these, I'm going for a career change and its really giving me confidence that I can do this
Yes! Here's my vid on R Markdown: th-cam.com/video/asHhuHRxhvo/w-d-xo.html.
Hope it helps!
Your content has really helped me transition from STATA to R! Any plans to do some SEM modelling?
Oooh good idea!
Thank you!
In addition I see nice feature.
After changing a variable - we look at it by View() command... but if I do some changes one more time I can change a page were I've already call a variable and I can see new changes without calling View() once again.
Yes! Also, when tidyverse is loaded, you don't actually need to capitalize view().
Excellent. Thank you
Thank you very informative and easy to understand the basics
for those who couldn't get arrange function done: library(dplyr)
df=diamonds_sm
df2%arrange(color)
view(df2)
i love your videos so much
thank you very much! very good material
Thank you for sharing this. 🙏
I didn't know that arrange is the tidyverse equivalent of sort. Thanks!
So much of dplyr is inspired by SQL.
@@EquitableEquations Exactly, I have fallen in love with R due to tidyverse. The tidyverse feels like another language on its own. More of a Python way of writing R code
How to get that diamond dataset
It becomes available to you as soon as you load tidyverse.
I did not find the diamonds file in your Github account.can you please tell me where can i find it?
Hi! It becomes available in R as soon as you load tidyverse. You don't need to download it separately.
Thanks
Amazing
group_by() is the SUMIF in spreadsheet..
Awesome.
👏👏👏👏👏👏👏
You're awesome.
I heard to come back here, having watched one of your videos; learning R in 39 minutes.
I have a question please
I'm doing the data analysis for my research titled; modeling of selected classification methods and comparison of their performance in the classification of anaemia patients among Nigerian children.
Now, I've not been using much of R before this work. So I ran into an issue with my dataset. I have one on of my predictor variables to be continuous. When I declared its class in R as numeric, all values for that variable were overwritten as NAs. I can't start checking each cell because there are almost 11,000 observations. How do I fish out where the problem is?
thank you
The way that the date shows by teachers is not learnable
You're awesome.
I heard to come back here, having watched one of your videos; learning R in 39 minutes.
I have a question please
I'm doing the data analysis for my research titled; modeling of selected classification methods and comparison of their performance in the classification of anaemia patients among Nigerian children.
Now, I've not been using much of R before this work. So I ran into an issue with my dataset. I have one on of my predictor variables to be continuous. When I declared its class in R as numeric, all values for that variable were overwritten as NAs. I can't start checking each cell because there are almost 11,000 observations. How do I fish out where the problem is?