How do I create an empty array matrix in NumPy

Question

I can t figure out how to use an array or matrix in the way that I would normally use a list  I want to create an empty array  or matrix  and then add one column  or row  to it at a time   At the moment the only way I can find to do this is like   mat   None for col in columns      if mat is None          mat   col     else          mat   hstack  mat  col     Whereas if it were a list  I d do something like this   list      for item in data      list append item    Is there a way to use that kind of notation for NumPy arrays or matrices

User · Accepted Answer

You have the wrong mental model for using NumPy efficiently. NumPy arrays are stored in contiguous blocks of memory. If you want to add rows or columns to an existing array, the entire array needs to be copied to a new block of memory, creating gaps for the new elements to be stored. This is very inefficient if done repeatedly to build an array.

In the case of adding rows, your best bet is to create an array that is as big as your data set will eventually be, and then assign data to it row-by-row:

>>> import numpy
>>> a = numpy.zeros(shape=(5,2))
>>> a
array([[ 0.,  0.],
   [ 0.,  0.],
   [ 0.,  0.],
   [ 0.,  0.],
   [ 0.,  0.]])
>>> a[0] = [1,2]
>>> a[1] = [2,3]
>>> a
array([[ 1.,  2.],
   [ 2.,  3.],
   [ 0.,  0.],
   [ 0.,  0.],
   [ 0.,  0.]])

User · Answer

You can apply it to build any kind of array  like zeros   a   range 5  a    i 0 for i in a  print a   0  0  0  0  0

User · Answer

Here is some workaround to make numpys look more like Lists  np arr   np array     np arr   np append np arr   2  np arr   np append np arr   24  print np arr    OUTPUT  array   2   24

User · Answer

I think you want to handle most of the work with lists then use the result as a matrix  Maybe this is a way     ur list      for col in columns      ur list append list col    mat   np matrix ur list

User · Answer

You can use the append function   For rows    gt  gt  gt  from numpy import    gt  gt  gt  a   array  10 20 30    gt  gt  gt  append a    1 2 3    axis 0  array   10  20  30                 1  2  3      For columns    gt  gt  gt  append a    15   15    axis 1  array   10  20  30  15                 1  2  3  15        EDIT Of course  as mentioned in other answers  unless you re doing some processing  ex  inversion  on the matrix array EVERY time you append something to it  I would just create a list  append to it then convert it to an array

User · Answer

I looked into this a lot because I needed to use a numpy array as a set in one of my school projects and I needed to be initialized empty    I didn t found any relevant answer here on Stack Overflow  so I started doodling something      Initialize your variable as an empty list first In  32   x      and now cast it as a numpy ndarray In  33   x np array x    The result will be   In  34   x Out 34   array     dtype float64    Therefore you can directly initialize an np array as follows   In  36   x  np array     dtype np float64    I hope this helps

User · Answer

If you absolutely don t know the final size of the array  you can increment the size of the array like this   my arr   numpy zeros  0 5   for i in range 3       my arr numpy concatenate    my arr  numpy ones  1 5       print my arr      1   1   1   1   1      1   1   1   1   1      1   1   1   1   1       Notice the 0 in the first line  numpy append is another option  It calls numpy concatenate

User · Answer

For creating an empty NumPy array without defining its shape    arr   np array       this is preferred  because you know you will be using this as a NumPy array     arr          and use it as NumPy array later by converting it  arr   np asarray arr     NumPy converts this to np ndarray type afterward  without extra     dimension

User · Answer

Perhaps what you are looking for is something like this    x np array 0    In this way you can create an array without any element  It similar than   x      This way you will be able to append new elements to your array in advance

User · Answer

I think you can create empty numpy array like    gt  gt  gt  import numpy as np  gt  gt  gt  empty array  np zeros 0   gt  gt  gt  empty array array     dtype float64   gt  gt  gt  empty array shape  0     This format is useful when you want to append numpy array in the loop

User · Answer

A NumPy array is a very different data structure from a list and is designed to be used in different ways   Your use of hstack is potentially very inefficient    every time you call it  all the data in the existing array is copied into a new one   The append function will have the same issue    If you want to build up your matrix one column at a time  you might be best off to keep it in a list until it is finished  and only then convert it into an array   e g    mylist      for item in data      mylist append item  mat   numpy array mylist    item can be a list  an array or any iterable  as long  as each item has the same number of elements  In this particular case  data is some iterable holding the matrix columns  you can simply use   mat   numpy array data     Also note that using list as a variable name is probably not good practice since it masks the built-in type by that name  which can lead to bugs    EDIT   If for some reason you really do want to create an empty array  you can just use  numpy array      but this is rarely useful

User · Answer

Depending on what you are using this for  you may need to specify the data type  see  dtype     For example  to create a 2D array of 8-bit values  suitable for use as a monochrome image    myarray   numpy empty shape  H W  dtype  u1     For an RGB image  include the number of color channels in the shape  shape  H W 3   You may also want to consider zero-initializing with numpy zeros instead of using numpy empty   See the note here

User · Answer

To create an empty multidimensional array in NumPy  e g  a 2D array m n to store your matrix   in case you don t know m how many rows you will append and don t care about the computational cost Stephen Simmons mentioned  namely re-buildinging the array at each append   you can squeeze to 0 the dimension to which you want to append to  X   np empty shape  0  n     This way you can use for example  here m   5 which we assume we didn t know when creating the empty matrix  and n   2    import numpy as np  n   2 X   np empty shape  0  n    for i in range 5       for j  in range 2           X   np append X    i  j    axis 0   print X   which will give you      0   0      0   1      1   0      1   1      2   0      2   1      3   0      3   1      4   0      4   1

[python] How do I create an empty array/matrix in NumPy?

Examples related to python

Examples related to arrays

Examples related to numpy