6 ms·

Haskell Data Analysis and Machine Learning Cookbook

181 points by e19293001 10y ago

zelos 10y ago
It definitely seems like there's a lack of intermediate-to-advanced Haskell books. This looks like it contains a lot of canonical Haskell coding examples and might be useful: any Haskell experts that can weigh in? The other Packt Haskell book is apparently terrible, so I'm a bit cautious.
- 15155 10y ago
  This is my favorite resource: http://haskellbook.com/ http://haskellbook.com/ It covers beginner topics through arguably advanced topics (monad transformers, etc.) "Advanced" is subjective, but I don't believe the current version covers GADTs, type families, or other more esoteric extensions. (No affiliation to the authors)
  - cies 10y ago
    > I don't believe the current version covers GADTs, type families Indeed it does not currently cover that.
  - cm3 10y ago
    I've seen GADTs as a feature that Haskell devs complained about, similar to Template Haskell. I know the issues with TH, but what's the limitation of GADTs as implemented in Haskell, and are there languages with less problematic implementations?
    - tel 10y ago
      Maybe some people think they're a little complex, but there's nothing particularly wrong with them in Haskell. They can be extended further in a dependently-typed context, but that's really another thing completely.
dschiptsov 10y ago
BTW, one might notice how a language with type-tagged data (a value has a type, not a variable, there are no box-like variables, but bindings) is much more suitable for data exploration and analysis (python + pandas is a good example). Also homogeneous lists and especially conditionals is kind of awkward - tuples aren't as flexible as lists. Defining a type for each possible row and then pattern-match on will result in a lot of useless boilerplate, almost as bad as Java. Common Lisp, it seems, is a better choice for such problems.
- reuben364 10y ago
  The dependently-typed-ish features of haskell can provide a sweet spot of both untagged data along with the flexibility of heterogeneous lists.
  - nine_k 10y ago
    An example / reference would be nice.
IanCal 10y ago
I like seeing more things come out helping people with data analysis in various languages, but this put me off: > isWhitespace x = elem x " \t\r\n" This is the kind of thing that makes me concerned about using this resource for real-world data. In real-world data you're going to get all kinds of crazy things coming in, and if you're assuming nobody will ever have something like a zero width non-breaking space, or a form feed, you're going to have a problem. It's the kind of thing I see with people starting out when dealing with data, similarly the punctuation detection here: https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook/blob/master/Ch02/Code02_punctuation/Main.hs https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook/bl... If you rely on these things, you will have problems. Text is hard and weird and terribly more complicated than people usually expect. Does haskell have good libraries for dealing with the more awkward parts? Can I easily remove all characters marked as whitespace in unicode, for example? Detecting and managing mangled encodings?
- ocharles 10y ago
  For more realistic stuff, I generally use https://hackage.haskell.org/package/text-icu https://hackage.haskell.org/package/text-icu. For example, in an old project we had a type called `Texty`, which was roughly non-empty normalized text: mkTexty :: Text -> Maybe Texty mkTexty = \a -> let a' = T.dropAround Char.isSpace (ICU.normalize ICU.NFC a) in if T.null a' then Nothing else Just (Texty a') {-# INLINE mkTexty #-}
  - IanCal 10y ago
    Great, thanks for the link.
- unhammer 10y ago
  Yeah, that doesn't give high hopes for this book teaching best practices :/ If you don't want to depend on text-icu, there is support for more Unicode space characters in https://hackage.haskell.org/package/base-4.8.2.0/docs/Data-Char.html#v:isSpace https://hackage.haskell.org/package/base-4.8.2.0/docs/Data-C... import Data.Char (isAlpha, isLower, isSpace) import qualified Data.Text as T giving you e.g. textIsAllSpace t = T.all isSpace t
edgordon 10y ago
This is a repost of a book we published in 2014. It's well reviewed, and the author kept the Github repo for the code up to date with feedback (https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook). If anyone wants to try it, you can pick it up in the Packt sale currently for $10 @ packtpub.com
eggy 10y ago
I might have a look, but the page seems to be a big ad with animated buy buttons at top? I posted a link for a free online kdb training class 3 months ago for students that normally goes for $1300 with no affiliation to the company, and it was flagged. What's the difference?
mark_l_watson 10y ago
I bought this book a couple of years ago and never read through it. It does provide convenient recipes that you can look up in the table of contents. I like recipe books like this, but be warned that there is not much depth. I recently bought another book by the same author that is also useful.
blubb-fish 10y ago
Serious question: Is there any reason why somebody would use Haskell for data analysis when there is also R and Python - which are perfect for that job - except for that the respective person happens to be a Haskell expert anyway?
- gh02t 10y ago
  I use all three, depending on the task. Haskell is compiled and relatively speedy, as well as being great for writing custom parsers (plus in a lot of situations it parallelizes very easily). One thing I find Haskell to be really useful for is coercing large unstructured datasets into a format that is easier to feed into Python. For instance, I once had to write a parser for the data coming off of a digitizer being fed by a rather complicated radiation detector array. It's in an obscure and somewhat bizarre binary format that is pretty tedious to work with because it involves a lot of state in the parser, plus the files are pretty enormous (they describe every radioactive particle hitting every detector in the array over several hours of measurement). My colleague wrote a horribly tedious script in Python to parse it that was complicated and agonizingly slow, but I was able to write a very natural 80-line Haskell program in a few hours that was several orders of magnitude faster as well as much more robust. I was just massaging the data to feed into Python, but it was far far easier to do in Haskell. So I find for some tasks I want to reach for Haskell, because it's natural to express the solution in Haskell. Other stuff I wouldn't even consider it, especially for stuff like data processing and plotting Haskell is not as elegant. Right tool for the job and all.
  - hellofunk 10y ago
    This 80-line solution sounds very interesting. I'd love to see more examples of this particular strength of Haskell. Are there similar parsing projects that you can point to that are open source and worth looking at to better understand this use case of Haskell?
    - PinkyThePiggy 10y ago
      Here is an example from Real World Haskell (pretty good intermediate book, although it is a bit dated): http://book.realworldhaskell.org/read/using-parsec.html#csv http://book.realworldhaskell.org/read/using-parsec.html#csv A fully featured CSV parser in 20-30 [depending on how you count] lines of non-golf code.
sdx23 10y ago
I have bought that book some years ago and wouldn't do so again. It was very disappointing to see neither a focus on Haskell nor on data analysis. It scratches both topics but covers only very elementary things. The content is mostly short receipts that were to me of no value at the time. For people interested in the topics I'd recommend to buy some other good books, on Haskell and data analysis separately. If, however, receipts are to your liking and you're only starting out with Haskell / data science maybe this is something for you (or maybe not).

181 points by e19293001 10y ago

zelos 10y ago

It definitely seems like there's a lack of intermediate-to-advanced Haskell books. This looks like it contains a lot of canonical Haskell coding examples and might be useful: any Haskell experts that can weigh in? The other Packt Haskell book is apparently terrible, so I'm a bit cautious.

15155 10y ago
This is my favorite resource: http://haskellbook.com/ http://haskellbook.com/ It covers beginner topics through arguably advanced topics (monad transformers, etc.) "Advanced" is subjective, but I don't believe the current version covers GADTs, type families, or other more esoteric extensions. (No affiliation to the authors)
- cies 10y ago
  > I don't believe the current version covers GADTs, type families Indeed it does not currently cover that.
- cm3 10y ago
  I've seen GADTs as a feature that Haskell devs complained about, similar to Template Haskell. I know the issues with TH, but what's the limitation of GADTs as implemented in Haskell, and are there languages with less problematic implementations?
  - tel 10y ago
    Maybe some people think they're a little complex, but there's nothing particularly wrong with them in Haskell. They can be extended further in a dependently-typed context, but that's really another thing completely.

dschiptsov 10y ago

BTW, one might notice how a language with type-tagged data (a value has a type, not a variable, there are no box-like variables, but bindings) is much more suitable for data exploration and analysis (python + pandas is a good example). Also homogeneous lists and especially conditionals is kind of awkward - tuples aren't as flexible as lists. Defining a type for each possible row and then pattern-match on will result in a lot of useless boilerplate, almost as bad as Java. Common Lisp, it seems, is a better choice for such problems.

reuben364 10y ago
The dependently-typed-ish features of haskell can provide a sweet spot of both untagged data along with the flexibility of heterogeneous lists.
- nine_k 10y ago
  An example / reference would be nice.

IanCal 10y ago

I like seeing more things come out helping people with data analysis in various languages, but this put me off: > isWhitespace x = elem x " \t\r\n" This is the kind of thing that makes me concerned about using this resource for real-world data. In real-world data you're going to get all kinds of crazy things coming in, and if you're assuming nobody will ever have something like a zero width non-breaking space, or a form feed, you're going to have a problem. It's the kind of thing I see with people starting out when dealing with data, similarly the punctuation detection here: https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook/blob/master/Ch02/Code02_punctuation/Main.hs https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook/bl... If you rely on these things, you will have problems. Text is hard and weird and terribly more complicated than people usually expect. Does haskell have good libraries for dealing with the more awkward parts? Can I easily remove all characters marked as whitespace in unicode, for example? Detecting and managing mangled encodings?

ocharles 10y ago
For more realistic stuff, I generally use https://hackage.haskell.org/package/text-icu https://hackage.haskell.org/package/text-icu. For example, in an old project we had a type called `Texty`, which was roughly non-empty normalized text: mkTexty :: Text -> Maybe Texty mkTexty = \a -> let a' = T.dropAround Char.isSpace (ICU.normalize ICU.NFC a) in if T.null a' then Nothing else Just (Texty a') {-# INLINE mkTexty #-}
- IanCal 10y ago
  Great, thanks for the link.
unhammer 10y ago
Yeah, that doesn't give high hopes for this book teaching best practices :/ If you don't want to depend on text-icu, there is support for more Unicode space characters in https://hackage.haskell.org/package/base-4.8.2.0/docs/Data-Char.html#v:isSpace https://hackage.haskell.org/package/base-4.8.2.0/docs/Data-C... import Data.Char (isAlpha, isLower, isSpace) import qualified Data.Text as T giving you e.g. textIsAllSpace t = T.all isSpace t

edgordon 10y ago

This is a repost of a book we published in 2014. It's well reviewed, and the author kept the Github repo for the code up to date with feedback (https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook). If anyone wants to try it, you can pick it up in the Packt sale currently for $10 @ packtpub.com

eggy 10y ago

I might have a look, but the page seems to be a big ad with animated buy buttons at top? I posted a link for a free online kdb training class 3 months ago for students that normally goes for $1300 with no affiliation to the company, and it was flagged. What's the difference?

mark_l_watson 10y ago

I bought this book a couple of years ago and never read through it. It does provide convenient recipes that you can look up in the table of contents. I like recipe books like this, but be warned that there is not much depth. I recently bought another book by the same author that is also useful.

blubb-fish 10y ago

Serious question: Is there any reason why somebody would use Haskell for data analysis when there is also R and Python - which are perfect for that job - except for that the respective person happens to be a Haskell expert anyway?

gh02t 10y ago
I use all three, depending on the task. Haskell is compiled and relatively speedy, as well as being great for writing custom parsers (plus in a lot of situations it parallelizes very easily). One thing I find Haskell to be really useful for is coercing large unstructured datasets into a format that is easier to feed into Python. For instance, I once had to write a parser for the data coming off of a digitizer being fed by a rather complicated radiation detector array. It's in an obscure and somewhat bizarre binary format that is pretty tedious to work with because it involves a lot of state in the parser, plus the files are pretty enormous (they describe every radioactive particle hitting every detector in the array over several hours of measurement). My colleague wrote a horribly tedious script in Python to parse it that was complicated and agonizingly slow, but I was able to write a very natural 80-line Haskell program in a few hours that was several orders of magnitude faster as well as much more robust. I was just massaging the data to feed into Python, but it was far far easier to do in Haskell. So I find for some tasks I want to reach for Haskell, because it's natural to express the solution in Haskell. Other stuff I wouldn't even consider it, especially for stuff like data processing and plotting Haskell is not as elegant. Right tool for the job and all.
- hellofunk 10y ago
  This 80-line solution sounds very interesting. I'd love to see more examples of this particular strength of Haskell. Are there similar parsing projects that you can point to that are open source and worth looking at to better understand this use case of Haskell?
  - PinkyThePiggy 10y ago
    Here is an example from Real World Haskell (pretty good intermediate book, although it is a bit dated): http://book.realworldhaskell.org/read/using-parsec.html#csv http://book.realworldhaskell.org/read/using-parsec.html#csv A fully featured CSV parser in 20-30 [depending on how you count] lines of non-golf code.

sdx23 10y ago

I have bought that book some years ago and wouldn't do so again. It was very disappointing to see neither a focus on Haskell nor on data analysis. It scratches both topics but covers only very elementary things. The content is mostly short receipts that were to me of no value at the time. For people interested in the topics I'd recommend to buy some other good books, on Haskell and data analysis separately. If, however, receipts are to your liking and you're only starting out with Haskell / data science maybe this is something for you (or maybe not).