January 2017 1HaskellADay problems and solutions

• January 31th, 2017: For today's #haskell problem we look at #ephemeris data (double-precision triples) for EMbary (Earth/Moon) and Mars. We parse some big-Ds (double-precision numbers) to get Earth and Mars orbital #ephemeris data from the JPL.
• January 30th, 2017: This week we'll be looking at JPL Earth and Mars Ephemeris data sets. Today's #haskell problem reads in Julian dates. Today's solution uses Prolog Definite Clause Grammars (DCGs) - in #haskell - to read the date string.
  
• January 27th, 2017: Today's #haskell problem is a little word-guessing puzzle. Today's #haskell solution is another puzzle: To which band do witches band? Will we ever know?
• January 26th, 2017: Today's Haskell exercise tally the word-frequency of a file, so: tally-ho! Today's #haskell solution shows me 'County' is the most popular word in #haskell?!? but okay.  
• January 25th, 2017: For today's #haskell exercise, we see what Haskell files are in a directory, eh? Today's #haskell solution to find the Haskell files in a directory structure got me all Monad-y down low on the IO! 
• January 20th, 2017: For Today's #haskell problem we look at Merkle Trees of the #blockchain as Traversable. 
• January 19th, 2017: Lastly, today's #haskell problem looks at the Traversable function: lastest via @Jose_A_Alonso @yoeight. Today's #haskell solution shows the First shall be the lastest 
• January 18th, 2017: As sum is already defined for Traversibles, today's #haskell problem looks at average via @Jose_A_Alonso @yoeight. For today's #haskell solution we find the average of the elements of any Traversable type 
• January 17th, 2017: Today's #haskell problem continues Traversable exploration by @Jose_A_Alonso @yoeight with minAF and maxAF...in O(1). So, we have today's #haskell solution for minAF, minT, maxAF, and maxT. lolneat! 
• January 16th, 2017: Today's #haskell problem looks at find, any, and all as functions over Traversable types via @Jose_A_Alonso @yoeight. Today's #haskell solution not only defines anyAF and allAF but also the important gtfo, that is: find (> 5)-function.
• January 13th, 2017: Today's #haskell problem does 2 things: examines Applicative Functors (AF) and lets me say transpose...AF in a tweet. Today's #haskell solution shows a succinct applicative solution to transposeAF for matrices
• January 12th, 2017: Partial functions everywhere via @Jose_A_Alonso @bitemyapp! Today's #haskell exercise takes on maximum and minimum. We 'full-i-tize' the partial functions of minimal and maximal for all Foldable t in today's #haskell solution 
• January 11th, 2017: Today's #haskell exercise handles the next pitfall from @Jose_A_Alonso @bitemyapp: Prelude partial functions, particularly for the evil List! Today's #haskell solution TOTALly unpartializes some Prelude list functions ... geddit? TOTALly? GEDDIT? 
• January 10th, 2017: Continuing #haskell pitfalls review via @Jose_A_Alonso @bitemyapp we study Data.Text to process large text documents. Today's #haskell solution shows Dickens was ahead of his time, citing URLs in Christmas Carol LIKE A WEB GANGSTA! 
  
• Side note: I had no problem processing 200k size text document using String, but, hey: knock yourselves out with Text for text processing.
• January 9th, 2017: For today's #haskell exercise we take a leaf from @bitemyapp via @Jose_A_Alonso and look into Data.Aeson quasiquotes. Using Data.Aeson.QQ today's #haskell solution basically wrote itself.
• January 6th, 2017: Today we look at combined US State SAIPE/poverty and debt data, rescale those data, and cluster the results #Haskell 
• January 5th, 2017: For today's #haskell exercise we combine US State SAIPE/poverty data along with US State total and per capita debt. Today's #haskell solution on SAIPE/poverty data and US State debts has CHARTS! Never. Underestimate. Charts. 👌💯💯💯
• January 4th, 2017: Today's #haskell exercise we re-look SAIPE/poverty data, reorganizing by US State instead of by US County. We collate US State SAIPE/poverty data, then do a bit of analysis with a pensé about results thrown in at the end.
• January 2nd, 2017: For the beginning of AD 2017, today's #haskell exercise wishes you a less divisive year than the last. LITERALLY! 

December 2016 1HaskellADay 1Liners

• December 22nd, 2016:  f :: (Either a b, c) -> Either (a, c) (b, c), define f, snaps for elegance, e.g.: f (Left 4, "Hi") = Left (4, "Hi")
• bazzargh @bazzargh uncurry (flip (join bimap . (,) ))
• Denis Stoyanov @xgrommx need (Left 4, "Hi") = Left (4, "Hi") but your version Left ("Hi", 4)
• Thomas D @tthomasdd Do tuple sections count? do I have access to Data.Bifunctor?
• f (eab,c) = bimap (,c) (,c) eab
• SocialJusticeCleric @walkstherain uncurry $ either ((Left .).(,)) ((Right .).(,))
• Denis Stoyanov @xgrommx or f (e, a) = (join bimap (\x -> (x, a))) e
• Nickolay Kudasov @crazy_fizruk most elegant IMO:
  f (Left a, c) = Left (a, c)
  f (Right b, c) = Right (b, c)
• December 22nd, 2016: define a function that writes out an infinite, alternating stream of 1's and 0's as below. 
  
  • Philipp Maier @AkiiZedd mapM putStrLn $ join $ repeat ["0","1"]
  • Eyal Lotem @EyalL join . repeat = cycle?
  • mavant @mavant f = putStr "10" >> f
  • Eyal Lotem @EyalL mapM putStrLn $ cycle ["0","1"]
• December 10th, 2016:
  startsWith :: [String] -> String
  points-free so that:
  startsWith ["ΜΗΛΟΝ", "ΗΔΟΝΗ"] = "ΛΟ"
  That is: (length list)+1 Char of each word
• SocialJusticeCleric @walkstherain 
• I prefer `uncurry (!!) . (Data.List.transpose &&& length)`
• but `map . flip (!!) . length =<< id` only uses the Prelude
• Nick @crazy_fizruk zipWith (!!) <*> repeat . length

December 2016 1HaskellADay Problems and Solutions

• December 27th, 2016: For today's #haskell exercise we expand our inquiry of SAIPE/poverty data by analyzing by US State. 
• December 26th, 2016: Today's #haskell exercise looks at partitioning data by each unit's 'size'; then we visualize the partitioned data. Today's #haskell solution shows we can cluster and analyze US counties by their relative sizes 
  
• December 23rd, 2016: There are many (3000+) US Counties. Today's #haskell exercise visualizes them clustered by SAIPE/poverty data. Today's #haskell solution shows the US Counties clustered by SAIPE/poverty data visualized in @neo4j. 
  
• December 22nd, 2016: For today's #haskell exercise we shift focus from SAIPE/poverty data to debt by US State, total and per capita. Today's #haskell solution shows US State debt, totals and per capital, with a caution about the IO monad in a REPL. 
  
   
• December 21st, 2016: For today's #haskell exercise we look at clustering SAIPE/poverty data and looking at patterns in the clusters. Today's #haskell solution shows US counties fall in 4 clusters using SAIPE/poverty data with Los Angeles a stand out. 
  
• December 20th, 2016: Today we look at enumerating US Counties from SAIPE/poverty data then determining their US State, deterministically. We find in today's #haskell solution that there a a lot of Counties of the US, so we index and enumerate them. 
• December 19th, 2016: For today's #haskell exercise we make a set of (static) String values enumerable and indexible. On the shoulders of our previous parsing work, today's #haskell solution parses SAIPE data to index US State names.
• December 16th, 2016: Today's #haskell Exercise looks at score-cards for US Census data
• December 15th, 2016: For today's #haskell exercise, we're back looking at US Census data: SAIPE/poverty by State and county #DataAnalytics. Today's #haskell solution shows how to parse by-line whilst carrying-over structure-context from prior lines 
• December 14th, 2016: Today's #haskell exercise we begin to look at qubits and pauli rotations on qubits. Today's #haskell solution represents Qubits and rotates |0> and |1> through the Pauli X operator. 
• December 13th, 2016: Today's #haskell exercise looks at the US Census data and asks some by-State questions around incomes. Today's #haskell solution uses Network.HTTP and Applicative Functors to examine populations and mean/median incomes.
• December 12th, 2016: For today's #haskell exercise we observe a dinner-table conversation of a math professor and her husband. Today's #haskell solution shows us happiness for children is having a parent as a math professor. I know this.
• December 9th, 2016: Today is #FF on @1HaskellADay. I mean, that's today's #haskell exercise: Examine Twitter JSON for #FF-analytics. Today's #haskell solution shows us who NOT to #FF if you want the follow back. Doesn't it. 
  
• December 8th, 2016: Today's #haskell exercise comes to you all the way from Smyrna! Construct a word-square. And from 2000 common English words we have #haskell solutions for the 3x3 and 4x4 word-squares
  
  
  
  
• December 6th, 2016: Today's #haskell exercise will look at EMA/Exponential Moving Averages to analyze trends of, e.g. #BitCoin. Today's #haskell solution inlines state into the EMA-recursive function to analyze #BitCoin price history. 
  
  
  
  
• December 5th, 2016: Today's #haskell exercise we look at the SMA/Simple Moving Average as a trend-estimator for, e.g.: #BitCoin price. Today's #haskell solution uses the SMA-function as a Comonad. Below are 1 year and 3 months of #BitCoin SMA-analyses. 
  
  
  
  
  CORRECTION! SMA 15 and SMA 50 are industry norms in the markets. Corrected (and generalized) #haskell solution here. 
  
  
  
  
• December 1st, 2016: For today's #haskell exercise we look at a larger data set with a year's worth of BitCoin price history. 
  
  I love the #haskell standard library. I love that you can write today's solution: #BitCoin prices in one line of code.