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As a data scientist who has been using the language for 5 years now, Julia is by far the best programming language for analyzing and processing data. That said,

As a data scientist who has been using the language for 5 years now, Julia is by far the best programming language for analyzing and processing data. That said, it’s common to find many Julia packages that are only half-maintained and don’t really work anymore. (I still don’t know how to connect to Postgres in a bug-free way using Julia.) And you’d be hard pressed to find teams of data scientists that use Julia. So in that sense, Python has much more mature and stable libraries, and it’s used everywhere. (But I really hope Julia overtakes it in the next couple of years because it’s such a well-designed language.) Aside from programming languages, Jupyter notebooks and interactive workflows are invaluable, along with maintaining reproducible coding environments using Docker. I think memorizing basic stats knowledge is not as useful as understanding deeper concepts like information theory, because most statistical tests can easily be performed nowadays using a library call. No one asks people to program in assembler to prove they can program anymore, so why would you memorize 30 different frequentist statistical tests and all of the assumptions that go along with each? Concepts like algorithmic complexity, minimum description length, and model selection are much more valuable.

chubot 9y ago
Has Julia converged on a solution for data frames? I watched some JuliaCon videos and got the impression that they hadn't. There seem to be a lot of different overlapping efforts.
- 0kto 9y ago
  Well, only the DataFrames.jl package comes to my mind. However, there exist a few packages that extend this package (DataFramesMeta.jl or Query.jl; these overlap to some extend, but the newer Query package seems to go beyond DataFrames and offers some piping capabilities to interface with plotting packages). In general: During the three years of my PhD some language / package upgrades broke some of my scripts (during 0.4 -> 0.5 and -> 0.6), but the language (and its extensive documentation, online and from the source code of the packages) is very pleasant to use - the deprecation warnings usually help you to adjust your code in time. I have been relaying heavily on said DataFrame package, and am quite happy - the community is usually responsive and helpful in case of problems or questions.
jballanc 9y ago
> That said, it’s common to find many Julia packages that are only half-maintained and don’t really work anymore. On this specific point, it's worth noting that up until now there's been a single massive repository of every Julia package ever published, regardless of its current state or utility. Starting with the upcoming 0.7 release, Julia will introduce the concept of "curated" repositories so that, going forward, if you stick just with the default curated repository of packages you should have much less chance of running into a broken or unmaintained package.

chubot 9y ago

Has Julia converged on a solution for data frames? I watched some JuliaCon videos and got the impression that they hadn't. There seem to be a lot of different overlapping efforts.

0kto 9y ago
Well, only the DataFrames.jl package comes to my mind. However, there exist a few packages that extend this package (DataFramesMeta.jl or Query.jl; these overlap to some extend, but the newer Query package seems to go beyond DataFrames and offers some piping capabilities to interface with plotting packages). In general: During the three years of my PhD some language / package upgrades broke some of my scripts (during 0.4 -> 0.5 and -> 0.6), but the language (and its extensive documentation, online and from the source code of the packages) is very pleasant to use - the deprecation warnings usually help you to adjust your code in time. I have been relaying heavily on said DataFrame package, and am quite happy - the community is usually responsive and helpful in case of problems or questions.

jballanc 9y ago

> That said, it’s common to find many Julia packages that are only half-maintained and don’t really work anymore. On this specific point, it's worth noting that up until now there's been a single massive repository of every Julia package ever published, regardless of its current state or utility. Starting with the upcoming 0.7 release, Julia will introduce the concept of "curated" repositories so that, going forward, if you stick just with the default curated repository of packages you should have much less chance of running into a broken or unmaintained package.