Python Multidimensional arrays

In python, you get to learn and implement a variety of things, including the python multidimensional arrays. Learn more about this here.

Python Multidimensional arrays: Lists in lists

Depending what you’re doing, you may not really have a 2-D array.

80% of the time you have simple list of “row-like objects”, which might be proper sequences.

myArray = [ ('pi',3.14159,'r',2), ('e',2.71828,'theta',.5) ] myArray[0][1] == 3.14159 myArray[1][1] == 2.71828

More often, they’re instances of a class or a dictionary or a set or something more interesting that you didn’t have in your previous languages.

myArray = [ {'pi':3.1415925,'r':2}, {'e':2.71828,'theta':.5} ]

20% of the time you have a dictionary, keyed by a pair

myArray = { (2009,'aug'):(some,tuple,of,values), (2009,'sep'):(some,other,tuple) }

Rarely, will you actually need a matrix.

You have a large, large number of collection classes in Python. Odds are good that you have something more interesting than a matrix.

A good way to visualize a 2d array is as a list of lists. Something like this:

lst=[[1,2,3],[4,5,6],[7,8,9]]

here the outer list lst has three things in it. each of those things is another list: The first one is: [1,2,3], the second

one is: [4,5,6] and the third one is: [7,8,9]. You can access these lists the same way you would access another other element of a list, like this:

print (lst[0])

output: [1, 2, 3]

print (lst[1])

output: [4, 5, 6]

print (lst[2])

output: [7, 8, 9]

You can then access the different elements in each of those lists the same way:

print (lst[0][0])

output: 1

print (lst[0][1])

output: 2

Here the first number inside the [] brackets means get the list in that position. In the above example we used the number 0 to mean get the list in the 0th position which is [1,2,3]. The second set of [] brackets means get the item in that position from the inner list. In this case we used both 0 and 1 the 0th position in the list we got is the number 1 and in the 1st position it is 2

You can also set values inside these lists the same way:

lst[0]=[10,11,12]

Now the list is [[10,11,12],[4,5,6],[7,8,9]]. In this example we changed the whole first list to be a completely new list.

lst[1][2]=15

Now the list is [[10,11,12],[4,5,15],[7,8,9]]. In this example we changed a single element inside of one of the inner lists. First we went into the list at position 1 and changed the element within it at position 2, which was 6 now it’s 15.

Lists in lists in lists in..

This behaviour can be extended. Here is a 3-dimensional array:

[[[111,112,113],[121,122,123],[131,132,133]],[[211,212,213],[221,222,223],[231,232,233]],[[311,312, 313],[321,322,323],[331,332,333]]]

As is probably obvious, this gets a bit hard to read. Use backslashes to break up the different dimensions:

[[[111,112,113],[121,122,123],[131,132,133]],\

[[211,212,213],[221,222,223],[231,232,233]],\

[[311,312,313],[321,322,323],[331,332,333]]]

By nesting the lists like this, you can extend to arbitrarily high dimensions.

Accessing is similar to 2D arrays:

print(myarray)

print(myarray[1])

print(myarray[2][1])

print(myarray[1][0][2])

etc.

And editing is also similar:

myarray[1]=new_n-1_d_list

myarray[2][1]=new_n-2_d_list

myarray[1][0][2]=new_n-3_d_list #or a single number if you're dealing with 3D arrays etc.

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