The tidyverse as a function of understanding how to apply R is a START; if you think that (29) R packages in R is all that you need to fully utilize its power, or that you "know" R if you are actively familiar with the tidyverse, you are grossly misinformed. The tidyverse is a droplet in the ocean of possibility of what R has to offer. My solution to better applying an understanding of the full range of possibility that R has to offer, from the perspective of ML, software engineering, and data science proper is a knowledge tool I built that contains selected functions from 264 R packages - that''s my tidyverse (and it's constantly evolving). The fact that such an idea as an implementable solution is possible shows the incredible range of possibility and power that exists in R. When compared to Python - Python is a joke.
It will be awesome to have the tidy solution to interactive graphics. Plotly is really helpful but I just constantly need to adapt to their plotting syntax. Hope we could have something like that in the future major updates of ggplot2!
And what about highcharter? I still struggle to choose between these two. They both lack of facets, but highcharts solution with having a list of plots ad than providing it to the hc_grid function for me is more intuitive than plotly's solution with "do function. Wich, as we've just heard, will go away soon. Also there is an attempt to make interactive ggplot with "ggiraph" package, but i somehow just dont like it.
![[DSC 4.0] What Makes a Good Function - Hadley Wickham keynote](http://i.ytimg.com/vi/Qne86lxjgtg/mqdefault.jpg)
Thanks for fading the video of the speaker in and out to make it easier to read the slides. It's really helped.
enquo !! and was a real pain to explain to my peers. thanks for the {{}}. makes life simpler
That man is my hero
Imagine being taught data science by this guy 😀
The tidyverse as a function of understanding how to apply R is a START; if you think that (29) R packages in R is all that you need to fully utilize its power, or that you "know" R if you are actively familiar with the tidyverse, you are grossly misinformed. The tidyverse is a droplet in the ocean of possibility of what R has to offer. My solution to better applying an understanding of the full range of possibility that R has to offer, from the perspective of ML, software engineering, and data science proper is a knowledge tool I built that contains selected functions from 264 R packages - that''s my tidyverse (and it's constantly evolving). The fact that such an idea as an implementable solution is possible shows the incredible range of possibility and power that exists in R. When compared to Python - Python is a joke.
It will be awesome to have the tidy solution to interactive graphics. Plotly is really helpful but I just constantly need to adapt to their plotting syntax. Hope we could have something like that in the future major updates of ggplot2!
And what about highcharter? I still struggle to choose between these two. They both lack of facets, but highcharts solution with having a list of plots ad than providing it to the hc_grid function for me is more intuitive than plotly's solution with "do function. Wich, as we've just heard, will go away soon. Also there is an attempt to make interactive ggplot with "ggiraph" package, but i somehow just dont like it.
Didn't work for you to use ggplot and then use ggplotly?
Thank you for sharing this and thank you all for your hard work !
Thank you Hadley,,,
Your sounds and voice very friendly...
you need a lot of disc space for tidyverse, bcs you need to use packrat all the time
I need tidyvert for time series...
@@englianhu can't you just use xts and quantmod?
With your tidyverse and pipe %>% you are destroying langage R and get it not understandable
come on man! its just a package, you can use base R alternatives as well. I hear there is a native pipe operator in base r in development.
How is that, tidyverse does not modify anything in the base R language, so how is it destroying R language?
Base R developers should learn from the tidyverse.
Destroying? I find it actually more readible
Pipes make it way more readable than base R