How to add items into a numpy array

Question

I need to accomplish the following task   from   a   array   1 3 4   1 2 3     1 2 1       add one element to each row  to   a   array   1 3 4 x   1 2 3 x     1 2 1 x      I have tried doing stuff like a n    array  1 3 4 x    but numpy complained of shape mismatch  I tried iterating through a and appending element x to each item  but the changes are not reflected   Any ideas on how I can accomplish this

User · Answer

target       for line in a tolist        new line   line append X      target append new line   return array target

User · Answer

One way to do it  may not be the best  is to create another array with the new elements and do column stack  i e    gt  gt  gt a   array   1 3 4   1 2 3     1 2 1      1 3 4    1 2 3    1 2 1     gt  gt  gt b   array  1 2 3    gt  gt  gt column stack  a b   array   1  3  4  1           1  2  3  2           1  2  1  3

User · Answer

If x is just a single scalar value  you could try something like this to ensure the correct shape of the array that is being appended concatenated to the rightmost column of a   import numpy as np a   np array   1 3 4   1 2 3   1 2 1    x   10 b   np hstack  a x np ones  a shape 0  1       returns b as   array     1     3     4    10              1     2     3    10              1     2     1    10

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import numpy as np a   np array   1 3 4   1 2 3   1 2 1    b   np array  10 20 30   c   np hstack  a  np atleast 2d b  T     returns c   array    1   3   4  10            1   2   3  20            1   2   1  30

User · Answer

Appending a single scalar could be done a bit easier as already shown  and also without converting to float  by expanding the scalar to a python-list-type     import numpy as np a   np array   1 3 4   1 2 3   1 2 1    x   10  b   np hstack   a    x     len  a       returns b as   array    1   3   4  10            1   2   3  10            1   2   1  10      Appending a row could be done by   c   np vstack   a   x    len  a 0        returns c as   array    1   3   4            1   2   3            1   2   1           10  10  10

User · Answer

Appending data to an existing array is a natural thing to want to do for anyone with python experience   However  if you find yourself regularly appending to large arrays  you ll quickly discover that NumPy doesn t easily or efficiently do this the way a python list will   You ll find that every  append  action requires re-allocation of the array memory and short-term doubling of memory requirements   So  the more general solution to the problem is to try to allocate arrays to be as large as the final output of your algorithm   Then perform all your operations on sub-sets  slices  of that array   Array creation and destruction should ideally be minimized   That said  It s often unavoidable and the functions that do this are   for 2-D arrays    np hstack  np vstack np column stack np row stack   for 3-D arrays  the above plus     np dstack   for N-D arrays    np concatenate

User · Answer

np insert can also be used for the purpose  import numpy as np a   np array   1  3  4                  1  2  3                  1  2  1    x   5 index   3   the position for x to be inserted before np insert a  index  x  axis 1      array   1  3  4  5           1  2  3  5           1  2  1  5      index can also be a list tuple   gt  gt  gt  index    1  1  3    equivalently  1  1  3   gt  gt  gt  np insert a  index  x  axis 1  array   1  5  5  3  4  5           1  5  5  2  3  5           1  5  5  2  1  5      or a slice   gt  gt  gt  index   slice 0  3   gt  gt  gt  np insert a  index  x  axis 1  array   5  1  5  3  5  4           5  1  5  2  5  3           5  1  5  2  5  1

[python] How to add items into a numpy array

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