I have a matrix where every item in the matrix has its own brackets that I do not want. How can I remove the brackets around each item?
7 Answers
Wrap the matrix rows with the the Flatten function
M = {{{1}, {2}, {3}, {4}}, {{5}, {6}, {7}, {8}}}
To save time you can wrap your whole matrix using: Map[Flatten, <yourmatrix> ]
Map[Flatten,{{{1}, {2}, {3}, {4}}, {{5}, {6}, {7}, {8}}}]
the outermost list contains two elements (the rows). the Map function wraps these elements with the Flatten function
{{1, 2, 3, 4}, {5, 6, 7, 8}}
In Mathematica this is known as "nested" Lists. Flatten removes all wrappings of the List function until only one remains
To understand what the Map function does: Below is the "manual" approach without the Map function.
{
Flatten[{{1}, {2}, {3}, {4}}],
Flatten[{{5}, {6}, {7}, {7}}]
}
As you are talking to an awesome machine called the Mathematica kernel you don't have to waste time writing things in long hand to make them readable (like you would for a slow-to-understand human reader of an essay or your future self reading your code).
hence Map[Flatten, Matrix] has the terse shorthand form Flatten /@ matrix
mentioned by @garej , @jjc385 and @Mr.Wizard below
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1As this answer is clearly geared for new users, I think this answer would be somewhat improved by mentioning the syntactic sugar
Flatten /@ <matrix>. – jjc385 Feb 08 '16 at 13:18 -
(Is it polite/conventional to delete a comment such as mine above after the edit has been made?) – jjc385 Feb 08 '16 at 14:01
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@jjc385 I have not observed a specific convention in that regard. The comments can serve as minor credit for the source of an edit, and I don't see anything wrong with that. However since you are mentioned by (nick)name in the answer now the comments seems redundant and I would probably delete it if it where mine. – Mr.Wizard Feb 16 '16 at 13:57
Lots of solutions. Time for a benchmark. My own contribution is Part:
m = {{{1}, {2}, {3}}, {{2}, {4}, {6}}};
m[[All, All, 1]];
{{1, 2, 3}, {2, 4, 6}}
Update: I made a complete mess of my earlier attempt at benchmarking. Here is a rewrite.
methods = Hold[Flatten /@ m, ArrayReshape[m, Most@Dimensions@m],
ArrayReshape[m, Dimensions[m][[1 ;; 2]]], Flatten[m, {Depth[m] - 1, 1}],
Apply[Sequence, m, {2}], Apply[Sequence, m, {-2}], Join @@@ m, m[[All, All, 1]],
Catenate /@ m];
names = {"Map[Flatten]", "ArrayReshape 1", "ArrayReshape 2", "Flatten w/ Depth",
"Sequence {2}", "Sequence {-2}", "Join", "Part", "Map[Catenate]"};
upk[{x_, y_}] := Table[{ToString[i*j]}, {i, x}, {j, y}];
pkd[{x_, y_}] := RandomReal[1, {x, y, 1}];
tab =
Table[
List @@ First /@ RepeatedTiming /@ methods,
{fn, {upk, pkd}},
{shape, {{10, 100000}, {1000, 1000}, {100000, 10}}},
{m, {fn[shape]}}
];
TableForm[
Append[names] /@ (tab //. {x_List} :> x),
TableHeadings -> {{"Unpacked", "Packed"}, {{10, 100000}, {1000, 1000}, {100000, 10}}},
TableSpacing -> {5, 1, 0.5}
]

(Benchmark timings in 10.1.0 under Windows 7 x64.)
It seems that in most instances Part wins, but a few times Catenate edges it out.
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I don't mean to question the infinite wisdom of Mr.Wizard, but as a relatively new user who just spent a few minutes trying to understand this code, I think it would be immensely helpful (and not terribly time consuming) if you somehow paired each column of output for the tests with a description of that test. For example, you could include a line
{"Flatten-Map", "ArrayShape-Most", "ArrayShape", "Flatten-Depth","Apply-Sequence","Apply-Sequence-Backward","Join","Part-All"}each of the three sets of output. It might also be helpful to sort somehow, but I can imagine arguing either way. – jjc385 Feb 08 '16 at 13:12 -
I'm sure a wizard like you can work this into the definition of the tests themselves! – jjc385 Feb 08 '16 at 13:13
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1@jjc385 Sorry, I was just being lazy. Actually really lazy as if the code I copied is actually what I ran the second test is a total mess. Earlier I had a comment "where's my coffee" -- I guess I really needed it! – Mr.Wizard Feb 08 '16 at 14:15
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1@jjc385 I rewrote the benchmark and got a different result. I hope I got it right this time but I am not certain I am still thinking clearly. Please let me know if you notice any stupid mistakes. – Mr.Wizard Feb 08 '16 at 15:01
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1It looks good to me, but then again I'm running on 2 hours of sleep and a can of soda at 7am ;)
By the way, and I'm not suggesting you implement this here, do you know of a slick way to do something like highlighting the elements of a list, with the highlighting color changing based on their values? It would be a good way to instantly see the winner for tests like these. (I admit I ask more out of curiosity than practicality.)
– jjc385 Feb 08 '16 at 15:43 -
1@Mr.Wizard, would you mind to check this method:
Catenate /@ m. It will not beatPartbut I'm not sure about other options. – garej Feb 08 '16 at 16:52 -
I get slightly different results with your benchmarking: http://i.stack.imgur.com/MlcPo.png, but in both yours & mine,
ArrayReshapehas roughly constant timing on 10^6 elements in all three shapes, esp. on packed arrays.Joinseems quite different on my system on packed arrays (Mac/Intel i7). – Michael E2 Feb 09 '16 at 04:03 -
@MichaelE2, at my machine
Catenate /@ mwins in many categories (Win, i5, 8Gb). – garej Feb 09 '16 at 05:34 -
1@garej Added to benchmark, along with a note of the system I am performing the benchmarking on. – Mr.Wizard Feb 09 '16 at 07:14
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2@garej What I found interesting was that relative performance seemed to vary by system so much. It's nice to see a new function (
Catenate) be an improvement once in a while. My last row is very different: 0.0044, 0.0063, 0.11. Note though thatCatenateis not compilable, which is why it loses out toFlattenon longer lists; it also why mapping it unpacks the list (to level 1 only), making further processing less efficient (unless repacked).Joinunpacks to level 2;Sequenceunpacks the whole array. Not sure why a difference in timing is not reflected on Mr.Wizard's computer. – Michael E2 Feb 09 '16 at 13:52 -
@MichaelE2, I have results similar with yours (on Win machine). Thank you for pointing out the packing issue. – garej Feb 11 '16 at 08:19
You can use ArrayReshape.
Either
ArrayReshape[mat, Most@Dimensions@mat]
or
ArrayReshape[mat, Dimensions[mat][[1 ;; 2]]]
It will keep a packed array packed, too.

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Readers of this answer can find some further discussion of using
ArrayReshapeto remove unwanted singleton list wrappings, e.g.,{a]or{{a, b, c}}in this answer – m_goldberg Aug 02 '16 at 12:51
Edit With m = RandomInteger[9, {3, 6, 1}]
Just for completeness:
Catenate /@ m
Just for diversity reasons
Apply[#&, m, {2}]
Apply[Sequence, m, {-2}]
Map[First, m, {2}]
Using @Mr.Wizard code I have updated the benchmark.
@MichaelE2 also noticed in comments that Catenate is not compilable.
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1I get similar results, to within a scaling factor for my slow CPU. Interesting that
Joinis much worse on packed arrays! – Simon Woods Feb 15 '16 at 20:22 -
@SimonWoods, MichaelE2 in a comment says "that
Joinunpacks to level 2.Sequenceunpacks the whole array". He gets similar results. I'm surprized thatCatenatebehaves so different within packed group. – garej Feb 15 '16 at 21:12
You can also Apply Join at level 1 to your list:
m = RandomInteger[9, {2, 4, 1}]
{{{0}, {6}, {7}, {5}}, {{1}, {3}, {8}, {8}}}
Join @@@ m
{{0, 6, 7, 5}, {1, 3, 8, 8}}
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I suggest Flatten[m, {Depth[m] - 1, 1}], where m is the matrix in question.
For example,
SeedRandom[1]; m = RandomInteger[99, {4, 5, 1}]
{{{80}, {14}, {0}, {67}, {3}}, {{65}, {23}, {97}, {68}, {74}}, {{15},{24}, {4}, {90}, {83}}, {{70}, {1}, {30}, {48}, {25}}}
Flatten[m, {Depth[m] - 1, 1}]
{{80, 14, 0, 67, 3}, {65, 23, 97, 68, 74}, {15, 24, 4, 90, 83}, {70, 1, 30, 48, 25}}
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...and of course, there's always Transpose[]:
Transpose[{{{1}, {2}, {3}}, {{2}, {4}, {6}}}, {2, 3, 1}] // First
{{1, 2, 3}, {2, 4, 6}}
The Flatten[] equivalent is then
Flatten[{{{1}, {2}, {3}}, {{2}, {4}, {6}}}, {{1}, {3, 2}}]
{{1, 2, 3}, {2, 4, 6}}
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mat /. List[x__] /; Length[List[x]] == 1 :> xwherematis your matrix (I can't read which letter you're using in this image). – IPoiler Feb 07 '16 at 20:34Catenate /@ mis also a fast option. – garej Feb 08 '16 at 17:27