tidyverse is more than a pandas analogue. It’s more like Pandas (and a little more sugar) + Expression + Altair (or matplotlib) and a few others less used. It’s very beautiful. It aligns well with R and is quite functional stylistically and is usually pretty clean syntactically.
The books are really good, but the docs(tidyverse and R) are kinda poor compared to Python (and Rs documentation tools are very limited — PDFs mostly). R package management is much worse than Python’s.
It’s certainly powerful, it’s certainly elegant, and Wickham is an incredible technical writer.
There’s lots of really incredible research done in the R ecosystem.
Caution: Lots of docs are affiliated with Posit, including Wickham’s. Posit wants to sell their cloud offerings. This often leads to over-optimism in documentation.
The language is definitely capable of serious work, and is pretty good at dataviz, psych, and gis.
I highly recommend giving it a try, if you like functional programming or want to see some cool data science ideas and statistics research.
I have to use a lot of R for masters, but I use python/pandas for everything using the jupyter magic for R, but have never used tidyverse and had no mark of reference to compare with.
How R and tidyverse compares with python pandas?
tidyverse is more than a pandas analogue. It’s more like Pandas (and a little more sugar) + Expression + Altair (or matplotlib) and a few others less used. It’s very beautiful. It aligns well with R and is quite functional stylistically and is usually pretty clean syntactically.
The books are really good, but the docs(tidyverse and R) are kinda poor compared to Python (and Rs documentation tools are very limited — PDFs mostly). R package management is much worse than Python’s.
It’s certainly powerful, it’s certainly elegant, and Wickham is an incredible technical writer.
There’s lots of really incredible research done in the R ecosystem.
Caution: Lots of docs are affiliated with Posit, including Wickham’s. Posit wants to sell their cloud offerings. This often leads to over-optimism in documentation.
The language is definitely capable of serious work, and is pretty good at dataviz, psych, and gis.
I highly recommend giving it a try, if you like functional programming or want to see some cool data science ideas and statistics research.
I have to use a lot of R for masters, but I use python/pandas for everything using the jupyter magic for R, but have never used tidyverse and had no mark of reference to compare with.