Problem with Flat Boxplots (Height)

Hi! I need help for a little problem concerning boxplots. I'm trying to draw a boxplot for each column of this matrix:

0,611811812025304  NaN                  NaN
0,202012002233165  NaN                  NaN
0,121618028406950  NaN                  NaN
0,237524917985388  NaN                  NaN
0,422843308928793  NaN                  NaN
1,34805765717167  NaN                  NaN
0,407175451160424  NaN                  NaN
0,181795622494409  NaN                  NaN
0,872365832050369  NaN                  NaN
0,400678297953037  NaN                  NaN
0,460260710072307  NaN                  NaN
8,39873881367597  NaN                  NaN
0,606103338545742  NaN                  NaN
4,03831386379199  NaN                  NaN
1,36753038819243  NaN                  NaN
0,953634332672089  NaN                  NaN
0,141486467642448  NaN                  NaN
0,161911818419999  NaN                  NaN
2,17059425768484  NaN                  NaN
2,36664942803871  NaN                  NaN
2,53445480253044  NaN                  NaN
0,586500894555781  NaN                  NaN
1,54852352420527  NaN                  NaN
0,822402150988892  NaN                  NaN
0,128866124032608  NaN                  NaN
1,61899736876937  NaN                  NaN
1,31257864637621  NaN                  NaN
0,413476666915168  NaN                  NaN
0,353846288130247  NaN                  NaN
19,9164007184726  0,422522449090564  NaN
0,821951799072535  0,220331707234890  NaN
0,174829883747978  0,109043770014573  NaN
0,215984225044525  1,31248161051824  NaN
0,132624070899366  0,197591729850422  NaN
0,715060420607512  3,66411237140579  NaN
37,9756265539746  0,804492414052763  NaN
8,04621953389878  0,0835547017967292  NaN
62,1120347049725  1,85195846002136  NaN
0,527662025334865  0,431617889581757  NaN
5,05616171189133  0,154725905026987  NaN
6,09471077005657  19,2419162458918  NaN
1,05486253006966  0,775569626694653  NaN
1,77178376126561  0,294098924340488  NaN
76,8371633535447  0,170044560105851  NaN
0,262779856773621  10,6814671826124  NaN
6,34644533636596  0,222503274615019  NaN
0,398416944949906  0,258014846445284  NaN
0,541844064501460  1,60942779392956  NaN
1,13470266392566  4,45138332454159  NaN
0,311461585919655  0,509602957109919  NaN
0,736529543160809  0,180008207054924  NaN
0,215755150652812  0,598259260691424  NaN
0,658629847496683  0,179944924813846  NaN
3,12837015223708  1,23091286452402  NaN
17,1335986354163  0,305671121564177  NaN
55,3852855457813  0,274408034191056  NaN
0,947944849082426  2,84755681934467  NaN
1,26062073438588  0,682251600465320  NaN
14,8476598061371  4,30272663391816  NaN
0,335844703911900  1,04861419042058  NaN
5,75548455284785  1,12551791503430  NaN
0,345652067777950  1,49822450824455  NaN
9,81009098287847  0,676215562928618  NaN
2,68166082688514  1,23419161559456  NaN
0,251874526656245  12,4891194259660  NaN
2,99452626964836  2,59000896049364  NaN
1,96910272158643  3,82744629504532  NaN
23,9075399036276  0,240756274962680  NaN
0,445934742111256  2,69444721151977  NaN
0,0879075935922513  0,480390983790141  NaN
0,495895273705287  1,72850466210875  NaN
1,51920977118476  1,37019601640097  NaN
0,602591322238240  2,27173295273887  NaN
2,65016320831140  0,399306647283119  NaN
0,652919404656894  3,74784519948607  NaN
12,6636090880146  0,0453071186558230  NaN
31,7217052541265  0,959766702816410  NaN
0,932555998968833  2,24323371331513  NaN
0,574549599692967  0,0596835687308849  NaN
0,169795126370524  0,357063248105366  NaN
2,49952957587646  0,391616942075280  NaN
0,922328839293043  0,389099393998163  NaN
5,88431094473470  0,880863618935896  NaN
0,666373866087364  0,806129610025604  NaN
0,289110414109209  0,273296486342186  NaN
37,1372317864379  1,59916163168910  NaN
1,00399924776550  0,510404010539926  NaN
0,104415494057556  1,12535953418473  NaN
0,392168208154147  1,53352272352835  NaN
0,353195194949214  0,0638678812707424  NaN
1,65665838149233  0,465284527044651  NaN
0,407250835385937  1,43508698785990  NaN
25,2095009950367  333,458019738854  NaN
1,85521610411371  0,216399902105888  NaN
1,67215937780101  0,0465556138038966  NaN
2,50139935019729  0,330303879161160  NaN
16,9210477222438  2,25442899748870  NaN
0,108902911160233  1,01476955773043  NaN
0,285617177287497  0,355967087977850  NaN
0,0341936150247026  0,0942703964200585  NaN
52,2577945933913  0,719781498162715  NaN
0,0405834697865815  0,648447533429696  NaN
0,143978326584961  0,325906605184672  NaN
0,527529494811141  0,822849257847561  NaN
0,652697261435919  0,00263785304909766  NaN
0,586422176736425  2,23005636992619  NaN
4,20352160384643  33,6542983565242  NaN
1,39512312649093  3,03987274382649  NaN
0,219994166838996  2,03982910484300  NaN
10,1692748849028  0,0302461766890810  NaN
0,388498043776487  0,785475077490126  NaN
5,26350495914151  0,189247891011270  NaN
1906,03927674280  0,918401577958579  NaN
0,331353936654492  1,63277244005074  NaN
0,202452639682081  0,377153183542493  NaN
0,248792380035754  0,862012949125239  NaN
0,144058865750009  1,25594145603608  NaN
0,434251033937157  0,810081886927791  NaN
3,37853436605957  0,414531045492129  NaN
0,727301185322304  0,476504229495548  NaN
0,197237521214282  0,709467137164667  NaN
4,75011700302277  6,81872288106616  NaN
25,2390478012556  0,744903841635965  NaN
16,9054774733034  1,10790534950496  NaN
0,0778823656329089  0,606540914375345  NaN
3,28051400188373  1,14429027967013  NaN
1,55052769970343  2,76138142125145  NaN
116,136763025906  0,459868364331018  NaN
0,455767171342352  0,0269992560452722  0,108477959266486
14,3877215775941  4,02660150717863  0,580618593817879
1,30058050949341  167,482231797116  0,109967555854390
0,917949582829439  1,96001982822263  0,657385060568056
0,907566734216333  0,328046673063935  0,186265014929369
4,07517329715105  2,16459933566971  1,48105447232745
5,89372508366354  4,27673888332093  0,145926788783252
1,17243130736479  2,09482619639844  2,05139562859070
0,150431893777696  4,12520498464090  1,16672568163949
1,27127321111770  0,249209655582009  0,551352741345712
0,421515007134110  0,813236871384940  6,93595108199714
2,39776839934303  21,7233201600435  0,224599930151125
3,23163317706398  1,08391432192602  0,0375514422352337
0,280183053311817  0,389555215732463  0,666250151564336
0,557136642154887  1,74024452149903  0,215507695972955
0,581095819685200  0,0602910798188294  2,14035599403875
0,902606066380205  0,543779008208623  0,668593262023713
2,84667877076861  0,0824001253545941  2,78532443234326
0,474272341996740  0,490666675987195  58,3743050253014
17,6589568584233  1,82629473679662  12,0949341817428
4,51843087637085  0,559198911464602  19,7433084438693
0,286942399893278  0,799615601479297  38,2516683910076
0,0635411640388297  0,933168819705902  62,0323888759710
0,373770135823154  7,63160924593722  3,36880920960204
0,563547852405034  3,68150603426219  0,0844051475750177
0,563763718691636  0,0858077433835352  2,45028563543351
0,779552515162068  1,22315362811170  0,678039626325907
7,82373898608818  9,99535926564456  0,176492746852374
3,11942262000012  0,702810142190048  0,0756689516764759
0,781279512824197  0,0831345789614009  1,46972691941447
1,78208880662340  0,745959059811934  1,18651049070498
2,21848413658943  0,115866176117972  0,804979261195900
1,21345604403708  1,62858356641623  2,41580365700995
1,64644841106322  1,78179443729634  8,88767783141012
0,866359534441569  2,68929960486374  1,70843950960183
1,65142606738816  1,96981177600291  9,83702182737424
3,24656232543207  0,206836574377629  2,87778276347558
1,56757280883254  5,35106858203508  1,58184057455379
1,13803487923058  20,9302010940674  1,29797674401709
0,537073372958349  0,352625874880865  0,557473446682534
0,101268495490836  0,255114887300310  0,620754248879394
0,169732961095946  0,480591406706194  0,531899464302346
3,95353169833155  0,181757764639465  0,0676101361048398
0,628911193190644  5,07640286243587  1,33427492167882
8,34266300258284  0,787008795332508  1,74339506641752
0,241551417112647  0,348954306984497  0,261139991961441
0,394989356707522  2,32569753764232  74,2557408010191
3,97629154977883  4,21453165827416  0,803558409300759
4,73713124292154  1,62087473984893  0,208091911978794
1,43684059663986  0,201979954621152  0,978437731776309
0,357776891903100  0,171357526531867  1,36250343378713
0,343472087499293  0,238167798496773  1,38553113234027
23,4826052809145  0,0577722909160037  1,33278007099429
0,479185255512544  0,410992491184793  3,42361567370143
1,29094718535058  0,116956701267027  0,328210754855321
0,912047740693493  2,26672064038048  2,39906776515951
0,880638449665181  0,199189755717506  22,1356580707882
0,356269197116918  0,439941803460157  0,435971423557942
3,36915231819955  1,96819973668821  6,60631969775426
0,118708730997220  2,65103656865232  0,267134368761076
0,144495091427304  0,293748408826842  7,12625186996259
2,70315356299488  0,385466511817921  1,79667136405767
0,409883794505140  0,466725611629881  0,0969082504124401
1,57195592669153  0,643103493531410  8,14396357908239
0,802482807472588  0,123248809258017  1,77394443302385
1,65553063610964  0,581028469932234  0,480106523373763
0,675613230098678  2,72379433822909  5,40506759023240
0,293441290289647  8,70701348375728  0,208341628400055
1,33958529483061  23,3850824619601  0,718198674715083
0,450626370633081  1,39268623785671  0,712788119554715
3,08900992439309  4,99982779973861  0,523741599431052
0,158662208958495  0,146821367890122  0,763979090005738
0,295988133413464  0,173795795808288  1,66291950201127
0,922017633136439  2,21691238284418  1,12792380826903
1,86238923403107  0,0762825556010607  0,491601515010430
18,0274937762162  0,291480897972595  13,1989384183348
0,330069951421628  1,48827380449194  3,71634874689128
0,0252990135485904  0,586104492388254  3,05559942555915
1,11612364407442  0,137824685169174  1,80117681228964
0,670598579421409  1,32761810062705  0,145430562683680
0,751095711556071  0,276332177656771  4,69238553086906
3,96756723799240  0,314019702887346  0,593045172932841
0,204978435727257  0,208242999011504  0,578988330716101
1,35246394712653  31,1998950104185  1,28669178943098
0,653381710864904  0,691611082115290  0,361612670677013
3,24250603344809  1,00533460010805  1,12812764185352
5,66346563841242  1,28434561942083  0,844991589980579
0,133445794251030  0,484108927269186  0,706772020799121
0,0961723467572176  1,36243735147102  3,91772817517976
0,220438340174641  0,234608471815911  2,33230152259361
0,732200176929252  0,455211478964844  0,132579883523120
0,606558509369120  43,2599958505976  0,690370550127751
2,87359734798277  0,351428436424998  0,419749775819546
1,81450232735005  6,65455309622865  2,16351906740400
3,58189071237147  0,435839901189409  0,363232837143702
2,09872798627613  3,35229219306922  1,01086210051098
27,0400417894414  1,11269434573208  0,898991073163114
8,41447311721747  0,116669929459443  0,351041330254094
18,5188230998014  0,849367217994179  0,108398076473373
0,130132960084386  5,48402293287256  1,57276810504462
67,0307317599186  1,16499120704080  0,0287235024061312
3,06403657220549  5,68652235769979  1,99853971602729
0,0612193919983093  1,32477083043251  44,2793732703085
0,477022914759577  8,48488944218403  0,978163259223186
0,350457765692137  0,544564562108746  0,519084244554332
0,456937915344642  0,583380758907430  3,02571174415551
0,405426435244366  0,751889866489825  0,511221033646454
31,8788766823986  7,87373704787610  14,2293180752816
0,501063368897439  3,02272328499824  0,234580448750740
2,42956890216784  0,921982575312160  0,725393774953451
1,25913721816711  0,126118232007005  9,20261166156716
32,1220486552959  5,47472300011537  0,321716081841228
1,16357040080161  2,60582053175120  0,348507697024575
0,975609629164045  3,62676528718201  15,5679968609625
30,5483775362479  0,208326133880049  0,851270626885559

Each column correspond to a year: [2010 2011 2012], so:

boxplot(myAx,myMatrix,[2010 2011 2012],'Notch','on','Symbol','k.');

Plot is being created but there is a big problem:

The data spread is too wide and the boxplots are flattened soo much that they become flat. Is there any way to solve this issue?

Answer 1

[the cyclist]

There are (at least) three straightforward solutions.

First, you could just limit the extent of the y-axis:

ylim([0 10])

Second, you could plot the y-axis on a log scale:

set(myAx,'YScale','log')

Third, you could just plot log(myMatrix):

boxplot(myAx,log(myMatrix),[2010 2011 2012],'Notch','on','Symbol','k.');

or

boxplot(myAx,log10(myMatrix),[2010 2011 2012],'Notch','on','Symbol','k.');

These have advantages and disadvantages. In first case, you don't plot the very large outliers. This may or may not be OK, depending on what you are trying to convey. You could add some kind of annotation to plot to indicate this.

In the second and third cases, it might be misleading to show your data a log scale. Again, it depends on what you are trying to convey.

[the cyclist]

Comment from Tommaso moved here from an "answer":

Both solutions are working fine. But I can't chose the best one. The data I'm plotting represents annual losses. If I chose the first solution, I lost the outliers but it's not a tragedy because other plots are already showing minimum/maximum values. If I chose the other solutions, Y axis becomes meaningless.