September 2015 1HaskellADay Problems and Solutions

• September 30th, 2015: Now, not only DLists are Functors, for today's #haskell problem we make them Applicative! http://lpaste.net/4112595477009006592 Come to find that Applied Applicative DLists taste like Apples http://lpaste.net/792542463930662912
• September 29th, 2015: For today's #haskell problem we look at DLists as Functors! I know! Exciting! http://lpaste.net/8043489210054737920 and we enfunctorfy DLists ... which are already functions ... http://lpaste.net/2809553771506434048 ... hmmm ... That sounds like DLists are APPLICATIVE!
• September 28th, 2015: So we indexed a set of rows last week, let's re(re)cluster them, AGAIN! http://lpaste.net/5440430731631263744 for today's #haskell problem. And now we re(re)clustered the data, now with colors! http://lpaste.net/3487731800489328640
• September 24th, 2015: Okay, yesterday we indexed rows, so, for today's #haskell problem, let's save and load those rows as CSV http://lpaste.net/2517275148160073728 The solution to this problem has no title (oh, well!) http://lpaste.net/6580653869074743296
• September 23rd, 2015: Data Row, o, Data Row: wherefore art thoust identity? Today's #haskell problem adds unique ids for rows of data http://lpaste.net/348288308305985536 Simply by using Data.Array we get our data in (uniquely-identified) rows http://lpaste.net/2095758966012248064
• September 22nd, 2015: For today's #haskell problem we go To Infinity ... and Beyond. Yes: we're coding Haskell-on-the-web, yo! http://lpaste.net/1872496352533938176 simpleHTTP makes HTTP GET-requests, ... well: simple! http://lpaste.net/1054132180147503104
• September 21st, 2015: For today's #haskell problem, we'll fade a circle to black http://lpaste.net/1617260331761926144
• September 17th, 2015: For today's #haskell problem, we receive data one way, but want to see it in another way. What to do? http://lpaste.net/4132020892534308864 Data. EnCSVified. (that's a word, now) http://lpaste.net/6250288158647255040
• September 16th, 2015: Today's #haskell problem asks 'why JSONify when you can represent clusters yourself?' Why, indeed! http://lpaste.net/9129398633454632960
• September 15th, 2015: For today's #haskell problem we 'unJSONify' some, well, JSON http://lpaste.net/2687400576576126976
• September 14th, 2015: For today's #haskell problem, we relook and recenterclusters from the cluster center http://lpaste.net/8570863670190407680 So, re-en-cluster-i-fied ... uh: clusters! YAY! (with, ooh! pics!) http://lpaste.net/8152035196972040192 
  
• September 11th, 2015: Yesterday we displayed one cluster. For today's #haskell problem, let's display them all! http://lpaste.net/6049110928429940736
• September 10th, 2015: This past week we've been clustering data, for today's #Haskell problem we look at visualizing one of these clustershttp://lpaste.net/6385518627050749952 Cluster: shone! ('Schön'? sure!) http://lpaste.net/6270301353331916800 
• September 9th, 2015: Okay, yesterday we clustered some data. For today's #haskell problem: let's see some clustered results, then! http://lpaste.net/4070941204840185856 It don't mean a thing, ... If it ain't got the (spreadsheet/CSV) schwing. http://lpaste.net/8321027338137501696
• September 8th, 2015: Today we get to do what all those other peeps do in other programming languages. Today we get to WRITE A PROGRAM!http://lpaste.net/4909208397410205696 wow. I'M K-MEANSIN' ON FIRE TODAY!(okay, geophf, calm down now) A program in Haskellhttp://lpaste.net/8770140562062835712
• September 7th, 2015: Happy Labor Day in the U.S.A. Today's #haskell problem is to look at recentering clusters for the K-Means algorithm http://lpaste.net/4755592492567494656 SEMIGROUPOID! (not 'monoid') is the key the solution for today's #haskell problem http://lpaste.net/9124358884469768192 (ScoreCard has no valid 'zero')
• September 4th, 2015: Today's #haskell problem we store color-coding for score cards we obtain from rows of data http://lpaste.net/6316202708206354432 And, color-coded score cards ... SAVED! (makes me wanna scream 'SAIL!') http://lpaste.net/1760010119669612544
  
• September 3rd, 2015: For today's #haskell problem we look at reclustering the rows of data using K-Means clustering http://lpaste.net/5001877831559413760 K-Means clustering in #haskell (well, for 1 epoch. Something's not right with step 3: recentered) http://lpaste.net/87582513538531328 (and it's DOG-slow)
• September 2nd, 2015: Drawing information from #BigData is magical, or so says today's #haskell problem http://lpaste.net/8551081789559406592 Ooh! Big Data is o-so-pretty! http://lpaste.net/2956050488883150848 But what does it mean? Stay tuned! 
  
• September 1st, 2015: For today's #haskell problem we look (obliquely) at the problem of 'indices as identity' http://lpaste.net/2039451038523588608 What is identity, anyway? 100+ clusters for 3,000 rows? Sounds legit. http://lpaste.net/4068559039884165120