Dataframes – Julia, R, Python
ajkl.github.io
Dataframes – Julia, R, Python
1–10 of 39 posts
Re: Dataframes – Julia, R, Python
#2In Julia, you can create symbols with e.g. :user_id as in Ruby, which looks a lot nicer than symbol("user_id") and doesn't require mapping over an array of strings.
Re: Dataframes – Julia, R, Python
#3There was a very interesting design discussion by JMW on the julia-dev forum about nullable arrays, and column dtypes:
https://groups.google.com/forum/#!topic/julia-dev/hS1DAUciv3...
Even so - right now Pandas is miles ahead of the Julia equivalent. Pandas was the brain child of Wes McKinney - an amazing coder, who really, really cared about speed (who recently also made a lot of money selling his start up to Cloudera - good for him!). The things you can do in Pandas with multi-index selects, joining dataframes on multiple axis, etc, are outright incredible.
Re: Dataframes – Julia, R, Python
#4In Julia, you can create symbols with e.g. :user_id as in Ruby, which looks a lot nicer than symbol("user_id") and doesn't require mapping over an array of strings.
Ofcourse you can! I dont know why I didnt think of that
Re: Dataframes – Julia, R, Python
#5Good showing of what are three good data languages. Strange I was a Python guy for a long time. Pandas just looks strange to me now since I switched to R two years ago.
Seems like I need to dive into Julia again. Haven't for over a year.
Re: Dataframes – Julia, R, Python
#6Good showing of what are three good data languages. Strange I was a Python guy for a long time. Pandas just looks strange to me now since I switched to R two years ago. Seems like I need to dive into Julia again. Haven't for over a year.
[deleted]
Re: Dataframes – Julia, R, Python
#7For dataframe-like operations, I've started wondering why more languages don't take the dplyr approach and simply default to using something like SQLite under the hood. Granted, I are no super data genius, but every time I start cracking a little into the internals of a dataframe implementation, I get the sinking feeling that SQL databases have already done the hard work of indexes and efficient data structures.
Re: Dataframes – Julia, R, Python
#8Interesting. Although after spwnding a lot of time on data frames, I have grown to like the csv parsers in postgres where I can do a lot of the same things as data frames, but with clean sql instead of the sometimes odd data frame syntax.
R also stands out because it is so easy to run a wide variety of statistical methods easily on a data frame.
Re: Dataframes – Julia, R, Python
#9For dataframe-like operations, I've started wondering why more languages don't take the dplyr approach and simply default to using something like SQLite under the hood. Granted, I are no super data genius, but every time I start cracking a little into the internals of a dataframe implementation, I get the sinking feeling that SQL databases have already done the hard work of indexes and efficient data structures.
You often want to:
* add or remove columns from a frame
* perform vector operations on columns in a frame
This would be awkward in SQLite. However, maybe a Column Oriented DBMS exists that would be workable.
Re: Dataframes – Julia, R, Python
#10I've seen a lot about Julia on the last months, it seems like a good language (performance and kind of a nice syntax), For me, what makes R a very good choice is because of RStudio. Being able to play there with your data and save it all for later is one of the biggest reasons to use RLang. The Python equivalent would be emacs org-mode, which is great, but not as graphical as RStudio.
Julia seems like a good language, maybe someday i will jump on it, but for the evil mind out there planning to write another language. Please stop, we already have great languages! I can't keep up with the learning! and is so damn difficult to even start a project with so many choices!