How to Make Columns From Arrays Within Array

Question

I am trying to figure out how to make columns out of arrays within an array. I am trying to save these columns to a text file.

I have tried multiple things, but I don't get columns. I get a large array that is going vertically down.

   a = [[array([ 2.05096059,  3.65564871,  0.25845727,  2.86561982,  1.45278606]), 
    array([5,10,15,20,25)]), 
    array([10,11,12,13,14])]

This is what I have tried, but it doesn't work.

for column in np.transpose(C):
    C_arr = np.hstack(column)
    # j = int(k)-1
    C_Values[j].append(C_arr)

I expect that I should get five columns with three elements in each column.

Expected output:

2.05096059 3.65564871 0.25845727 2.86561982 1.45278606
5          10         15         20         25
10         11         12         13         14

Be careful with terminology. a as shown looks like a list (object dtype) containing 3 arrays (ndarray). np.transpose(C) will turn that into a (3,5) array (float dtype) and then (5,3). Each column will be a (5,) shape array. What's wrong with C_Values? — hpaulj
– hpaulj, Commented Jan 11, 2019 at 21:51
Can't you just print each array separately, with its own format string (float vs integer)? It would a lot easier than trying mix them in one array (which normally uses a common dtype). — hpaulj
– hpaulj, Commented Jan 11, 2019 at 22:02
C_Values is not doing the right number of columns and there are too many elements in each column when I use the code in my question. — Cosmoman
– Cosmoman, Commented Jan 11, 2019 at 22:24

hpaulj · Accepted Answer · 2019-01-11 23:26:02Z

1

After cleaning up mismatch :

In [373]: a =[np.array([ 2.05096059,  3.65564871,  0.25845727,  2.86561982,  1.4
     ...: 5278606]), 
     ...:     np.array([5,10,15,20,25]), 
     ...:     np.array([10,11,12,13,14])]
     ...:     
In [374]: a
Out[374]: 
[array([2.05096059, 3.65564871, 0.25845727, 2.86561982, 1.45278606]),
 array([ 5, 10, 15, 20, 25]),
 array([10, 11, 12, 13, 14])]

In [377]: np.transpose(a)  
Out[377]: 
array([[ 2.05096059,  5.        , 10.        ],
       [ 3.65564871, 10.        , 11.        ],
       [ 0.25845727, 15.        , 12.        ],
       [ 2.86561982, 20.        , 13.        ],
       [ 1.45278606, 25.        , 14.        ]])

This is a (5,3) array of floats; plain iteration produces the rows, one by one.

Printing each array individually lets us control format:

In [378]: print(('%10f'*5)%tuple(a[0]))
     ...: print(('%10d'*5)%tuple(a[1]))
     ...: print(('%10d'*5)%tuple(a[2]))
     ...: 
     ...: 
  2.050961  3.655649  0.258457  2.865620  1.452786
         5        10        15        20        25
        10        11        12        13        14

Using the standard numpy csv writter:

In [379]: np.savetxt('test.txt', a, fmt='%10f')
In [380]: cat test.txt
  2.050961   3.655649   0.258457   2.865620   1.452786
  5.000000  10.000000  15.000000  20.000000  25.000000
 10.000000  11.000000  12.000000  13.000000  14.000000

It's possible to set a different format for each column, but not for each row.

answered Jan 11, 2019 at 23:26

hpaulj

233k14 gold badges260 silver badges392 bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

Cosmoman Over a year ago

This works! I still have gaps in my Python understanding, so thanks for the help!

Collectives™ on Stack Overflow

How to Make Columns From Arrays Within Array

1 Answer 1

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related