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list =
 {{"aar", "usa", "aer", "NYSE:AIR"}, {"aar", "bel", "sto","F:AIR"}, {"activision", "usa", "sof", "NASDAQ:ATVI"}, {"adidas", "deu", "sto", "F:ADS"}};

AssociationThread[list[[All, 1]] -> Map[Rest, list]]

<|"aar" -> {"bel", "sto", "F:AIR"}, "activision" -> {"usa", "sof", "NASDAQ:ATVI"}, "adidas" -> {"deu", "sto", "F:ADS"}|>

Almost perfect, but two questions remain:

How would you write this?

Why do I lose the first entry of my list?

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  • $\begingroup$ What is an expected result? $\endgroup$
    – Kuba ♦
    Apr 9, 2015 at 18:57
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    $\begingroup$ Right. "Almost perfect" means nothing to us unless you tell us what is perfect. $\endgroup$
    – David G. Stork
    Apr 9, 2015 at 18:57
  • $\begingroup$ Perfect means that the missing first entry should be "aar" -> {"usa", "aer", "NYSE:AIR"} $\endgroup$
    – eldo
    Apr 9, 2015 at 19:13
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    $\begingroup$ from AssociationThread>>Details: If any of the keys are repeated, later instances replace earlier ones $\endgroup$
    – kglr
    Apr 9, 2015 at 19:17
  • $\begingroup$ @kguler So I can't work with duplicate / multiple keys ? $\endgroup$
    – eldo
    Apr 9, 2015 at 19:21

2 Answers 2

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From the docs AssociationThread>>Details:

If any of the keys are repeated, later instances replace earlier ones.

And Association >> Details:

If there are multiple elements with the same key, all but the last of these elements are dropped. Merge yields instead a list of values for repeated keys.

Merge[Thread[list[[All, 1]] -> Map[Rest, list]], Identity]
(* <|aar->{{usa,aer,NYSE:AIR},{bel,sto,F:AIR}},
     activision->{{usa,sof,NASDAQ:ATVI}},
     adidas->{{deu,sto,F:ADS}}|> *)
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If you know you are going to get duplicate keys you should consider having a full set of keys for your association.

list = {{"aar", "usa", "aer", "NYSE:AIR"}, {"aar", "bel", "sto", 
"F:AIR"}, {"activision", "usa", "sof", "NASDAQ:ATVI"}, {"adidas", 
"deu", "sto", "F:ADS"}};

header = {"company", "country", "stock type", "ticker"};

AssociationThread[header -> #] & /@ list

Then if you can pull keys and values far more flexibly - also consider turning it into a Dataset for more flexible querying.

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