python - Why does numpy.concatenate work along axis=1 for small one dimensional arrays, but not larger ones? -

i couldn't 4 arrays of year, day of year, hour, , minute concatenate way wanted, decided test several variations on shorter arrays data.

i found worked using method "t" test code:

import numpy np  a=np.array([[1, 2, 3, 4, 5, 6]]) b=np.array([[11, 12, 13, 14, 15, 16]]) c=np.array([[21, 22, 23, 24, 25, 26]]) d=np.array([[31, 32, 33, 34, 35, 36]])  print print b print c print d  q=np.concatenate((a, b, c, d), axis=0) #concatenation along 1st axis print q  t=np.concatenate((a.t, b.t, c.t, d.t), axis=1) #transpose each array before concatenation along 2nd axis print t  x=np.concatenate((a, b, c, d), axis=1) #concatenation along 2nd axis print x 

but when tried larger arrays behaved same method "q".

i found alternative approach of using vstack over here did wanted, trying figure out why concatenation works this, not always.

thanks insights.

also, here outputs of code:

q:

[[ 1  2  3  4  5  6]      [11 12 13 14 15 16]      [21 22 23 24 25 26]  [31 32 33 34 35 36]] 

t:

[[ 1 11 21 31]  [ 2 12 22 32]  [ 3 13 23 33]  [ 4 14 24 34]  [ 5 15 25 35]  [ 6 16 26 36]] 

x:

[[ 1  2  3  4  5  6 11 12 13 14 15 16 21 22 23 24 25 26 31 32 33 34 35 36]] 

edit: added method t end of section of code fixed vstack, can compare how vstack work data not concatenate. again, clarify, found workaround already, don't know why concatenate method doesn't seem consistent.

here code:

import numpy np   bao10m=np.genfromtxt('bao_010_2015176.dat', delimiter=",", usecols=range(0-6), dtype=[('h', int), ('year', int), ('day', int), ('time', int), ('temp', float)]) #10 meter weather readings @ bao tower site june 25, 2015  hourbao=bao10m['time']/100 minutebao=bao10m['time']%100 #print hourbao #print minutebao #time arrays  daybao=bao10m['day'] yearbao=bao10m['year'] #date arrays  datetimebao=np.vstack((yearbao, daybao, hourbao, minutebao)) #t=np.concatenate((a.t, b.t, c.t, d.t), axis=1)  <this gave desired results in simple tests #not working data, use vstack instead, transposition after stack print datetimebao test=np.transpose(datetimebao) #rotate array print test #this prints can used datetime  t=np.concatenate((yearbao.t, daybao.t, hourbao.t, minutebao.t), axis=1) print t #this prints 1d array of year values, day values, etc... #but method worked shorter 1d arrays 

the file used can found @ this site.