ValueError all the input arrays must have same number of dimensions

Question

I m having a problem with np append   I m trying to duplicate the last column of 20x361 matrix n list converted by using the code below   n last      n last   n list converted    -1  n lists   np append n list converted  n last  axis 1    But I get error       ValueError  all the input arrays must have same number of dimensions   However  I ve checked the matrix dimensions by doing   print n last shape  type n last   n list converted shape  type n list converted     and I get       20L     20L  361L     so the dimensions match  Where is the mistake

User · Answer

You can also cast  n   to  n 1  by enclosing within brackets        e g  Instead of np append b a axis 0  use np append b  a  axis 0   a  1 2  b   5 6   7 8   np append b  a  axis 0    returns  array   5  6           7  8           1  2

User · Answer

n   and  n 1  are not the same shape  Try casting the vector to an array by using the     None  notation   n lists   np append n list converted  n last    None   axis 1    Alternatively  when extracting n last you can use  n last   n list converted    -1     to get a  20  1  array

User · Answer

The reason why you get your error is because a  1 by n  matrix is different from an array of length n   I recommend using hstack   and vstack   instead  Like this   import numpy as np a   np arange 32  reshape 4 8    4 rows 8 columns matrix  b   a   -1                        last column of that matrix   result   np hstack  a b           stack them horizontally like this   array    0   1   2   3   4   5   6   7   7             8   9  10  11  12  13  14  15  15            16  17  18  19  20  21  22  23  23            24  25  26  27  28  29  30  31  31      Notice the repeated  7  15  23  31  column  Also  notice that I used a   -1   instead of a   -1   My version generates a column   array   7           15           23           31      Instead of a row array  7 15 23 31      Edit  append   is much slower  Read this answer

User · Answer

If I start with a 3x4 array  and concatenate a 3x1 array  with axis 1  I get a 3x5 array   In  911   x   np arange 12  reshape 3 4  In  912   np concatenate  x x   -1     axis 1  Out 912    array    0   1   2   3   3            4   5   6   7   7            8   9  10  11  11    In  913   x shape x   -1   shape Out 913     3  4    3  1     Note that both inputs to concatenate have 2 dimensions   Omit the    and x   -1  is  3   shape - it is 1d  and hence the error   In  914   np concatenate  x x   -1    axis 1      ValueError  all the input arrays must have same number of dimensions   The code for np append is  in this case where axis is specified   return concatenate  arr  values   axis axis    So with a slight change of syntax append works   Instead of a list it takes 2 arguments   It imitates the list append is syntax  but should not be confused with that list method   In  916   np append x  x   -1    axis 1  Out 916    array    0   1   2   3   3            4   5   6   7   7            8   9  10  11  11      np hstack first makes sure all inputs are atleast 1d  and then does concatenate   return np concatenate  np atleast 1d a  for a in arrs   1    So it requires the same x   -1   input   Essentially the same action   np column stack also does a concatenate on axis 1   But first it passes 1d inputs through  array arr  copy False  subok True  ndmin 2  T   This is a general way of turning that  3   array into a  3 1  array   In  922   np array x   -1   copy False  subok True  ndmin 2  T Out 922    array    3            7           11    In  923   np column stack  x x   -1    Out 923    array    0   1   2   3   3            4   5   6   7   7            8   9  10  11  11      All these  stacks  can be convenient  but in the long run  it s important to understand dimensions and the base np concatenate   Also know how to look up the code for functions like this   I use the ipython    magic a lot   And in time tests  the np concatenate is noticeably faster - with a small array like this the extra layers of function calls makes a big time difference

[python] ValueError: all the input arrays must have same number of dimensions

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