Can you have a 3d array in python?

There are many ways to address your problem.

  1. First one as accepted answer by @robert. Here is the generalised solution for it:
def multi_dimensional_list(value, *args):
  #args dimensions as many you like. EG: [*args = 4,3,2 => x=4, y=3, z=2]
  #value can only be of immutable type. So, don't pass a list here. Acceptable value = 0, -1, 'X', etc.
  if len(args) > 1:
    return [ multi_dimensional_list(value, *args[1:]) for col in range(args[0])]
  elif len(args) == 1: #base case of recursion
    return [ value for col in range(args[0])]
  else: #edge case when no values of dimensions is specified.
    return None

Eg:

>>> multi_dimensional_list(-1, 3, 4)  #2D list
[[-1, -1, -1, -1], [-1, -1, -1, -1], [-1, -1, -1, -1]]
>>> multi_dimensional_list(-1, 4, 3, 2)  #3D list
[[[-1, -1], [-1, -1], [-1, -1]], [[-1, -1], [-1, -1], [-1, -1]], [[-1, -1], [-1, -1], [-1, -1]], [[-1, -1], [-1, -1], [-1, -1]]]
>>> multi_dimensional_list(-1, 2, 3, 2, 2 )  #4D list
[[[[-1, -1], [-1, -1]], [[-1, -1], [-1, -1]], [[-1, -1], [-1, -1]]], [[[-1, -1], [-1, -1]], [[-1, -1], [-1, -1]], [[-1, -1], [-1, -1]]]]

P.S If you are keen to do validation for correct values for args i.e. only natural numbers, then you can write a wrapper function before calling this function.

  1. Secondly, any multidimensional dimensional array can be written as single dimension array. This means you don't need a multidimensional array. Here are the function for indexes conversion:
def convert_single_to_multi(value, max_dim):
  dim_count = len(max_dim)
  values = [0]*dim_count
  for i in range(dim_count-1, -1, -1): #reverse iteration
    values[i] = value%max_dim[i]
    value /= max_dim[i]
  return values


def convert_multi_to_single(values, max_dim):
  dim_count = len(max_dim)
  value = 0
  length_of_dimension = 1
  for i in range(dim_count-1, -1, -1): #reverse iteration
    value += values[i]*length_of_dimension
    length_of_dimension *= max_dim[i]
  return value

Since, these functions are inverse of each other, here is the output:

>>> convert_single_to_multi(convert_multi_to_single([1,4,6,7],[23,45,32,14]),[23,45,32,14])
[1, 4, 6, 7]
>>> convert_multi_to_single(convert_single_to_multi(21343,[23,45,32,14]),[23,45,32,14])
21343
  1. If you are concerned about performance issues then you can use some libraries like pandas, numpy, etc.

Can you have a 3d array in python?

Introduction to 3D Arrays in Python

Before starting with 3d array, one thing to be clear that arrays are in every programming language is there and does some work in python also. Every programming language its behavior as it is written in its compiler. Many people have one question: Do we need to use a list in the form of 3d array, or we have Numpy. And the answer is we can go with the simple implementation of 3d arrays with the list. But for some complex structure, we have an easy way of doing it by including Numpy. It is not recommended which way to use it. It depends on the project and requirement that how you want to implement particular functionality.

What does the library mean?

Python has a set of libraries defines to ease the task. For the same reason to work with array efficiently and by looking at today’s requirement, Python has a library called Numpy. Numpy deals with the arrays. Numpy is useful in Machine learning also. It is good to be included as we come across multi-dimensional arrays in python. As we know, arrays are to store homogeneous data items in a single variable. Arrays in Python is nothing but the list. Look at the following code snippet. Here, we have a list of named colors. We are printing colors. This is a simple single-dimensional list we can say.

Example

colors = ["red", "blue", "orange"]
print(colors)

Output:

[‘red’, ‘blue’, ‘orange’]

Also, multidimensional arrays or a list have row and column to define. We can say that multidimensional arrays as a set of lists.

Following is the example of 2 dimensional Array or a list.

Example

rows = int(input("Enter the no.of rows you want: "))
cols = int(input("Enter the number of cols you want: "))
myList = [[0 for c in range(cols)] for r in range(rows)]
for r in range(rows):
  for c in range(cols):
   myList[r][c]= r*c
print(myList)

Output:

Enter the no. of rows you want: 2
Enter the number of cols you want: 2
[[0, 0], [0, 1]]

In the above example, we are just taking input from the end-user for no. of rows and columns. After that, we are storing respective values in a variable called rows and cols. Further, we created a nested loop and assigned it to a variable called my list. Here we are just taking items to be a loop over the numbers, which we are taking from end-user in the form of rows and cols.

After that, we are a loop over rows and columns. Finally, we are generating the list as per the numbers provided by the end-user.

Try this program. If you don’t know about how for loop works in python, then first check that concept and then come back here. You will understand this better.

How it is defined in Python?

Suppose we have a matrix of 1*3*3. We need to define it in the form of the list then it would be 3 items, 3 rows, and 3 columns.

 

Can you have a 3d array in python?

In the above diagram, we have only one @ in each set, i.e. one element in each set. 3 columns and 3 rows, respectively.

How can we define it then? In python, with the help of a list, we can define this 3-dimensional array. 3-dimensional arrays are arrays of arrays. There is no limit while nesting this.

How to Create 3D Arrays in Python?

We are creating a list that will be nested. Try out the following small example. If you are familiar with python for loops, then you will easily understand the below example.

symbol = [[ ['@' for col in range(2)] for col in range(2)] for row in range(3)]
print(symbol)

Output:

[[[‘@’, ‘@’], [‘@’, ‘@’]], [[‘@’, ‘@’], [‘@’, ‘@’]], [[‘@’, ‘@’], [‘@’, ‘@’]]]

If you look closely at the above example, we have one variable of type list. With the square brackets, we are defining a list in python. In the list, we have given for loop with the help of the range function. Which is simply defines 2 elements in one set. Each sublist will have two such sets. And we have a total of 3 elements on the list.

How to Insert Elements of 3D Arrays in Python?

Python has given us every solution that we might require. Python has many methods predefined in it. These methods help us to add an element to a given list. Python does not support the array fully. At this point, to get simpler with the array, we need to make use of function insert.

Kindly look at the below program.

Example:

mylist = [[['@', '@'], ['@', '@']], [['@', '@'], ['@', '@']], [['@', '@'], ['@', '@']]]
# number tuple
addition = ['$','$']
# inserting $ symbol in the existing list
my list.insert(2, addition)
print('Updated List is: ', mylist)

Output:

Updated List is:  [[[‘@’, ‘@’], [‘@’, ‘@’]], [[‘@’, ‘@’], [‘@’, ‘@’]], [‘$’, ‘$’], [[‘@’, ‘@’], [‘@’, ‘@’]]]

Here, in the above program, we are inserting a new array element with the insert method’s help, which python provides. In the above program, we have one 3 dimensional lists called my list.

The insert method takes two arguments. One is position, i.e. nothing but the index number. And second is an actual element you want to insert in the existing array or a list. Here, we took the element in one variable which we wanted to insert. We are applying the insert method on mylist.

Try to execute this program. Play with the output for different combinations. In the above program, we have given the position as 2. We all know that the array index starts at zero (0). That means a new element got added into the 3rd place, as you can see in the output.

How to Remove Elements of 3D Arrays in Python?

If we want to remove the last element in a list/array, we use a pop method. Look at the below example. Here we have removed the last element in an array. We have a pop() method. This method removes the last element in the list. We have used a pop() method in our 3d list/array, and it gives us a result with only two list elements. Try out the following example.

Example

symbol = [[ ['@' for col in range(2)] for col in range(2)] for row in range(3)]
symbol.pop()
print(symbol)

Output:

[[[‘@’, ‘@’], [‘@’, ‘@’]], [[‘@’, ‘@’], [‘@’, ‘@’]]]

Numpy

Here, we will look at the Numpy. As we already know, Numpy is a python package used to deal with arrays in python. Let’s start to understand how it works. For using this package, we need to install it first on our machine. For installing it on MAC or Linux, use the following command.

Pip Install Numpy

Let’s discuss how to install pip in NumPy.

  • Forgetting it on windows, we need to install it by an installer of Numpy. We are not getting in too much because every program we will run with numpy needs a Numpy in our system.
  • Numpy has a predefined function which makes it easy to manipulate the array. An array is generally like what comes with a fixed size. Increasing or decreasing the size of an array is quite crucial. Numpy overcomes this issue and provides you with good functionality to deal with this.
  • To start work with Numpy after installing it successfully on your machine, we need to import it into our program. After importing, we are using an object of it.
  • Using Numpy has a set of some new buzzword as every package has. If you want to learn more about Numpy, then do visit the link: https://docs.scipy.org/doc/ .
  • Here you will find the most accurate data and the current updated version of Numpy.

Conclusion

Python is a scripting language and mostly used for writing small automated scripts. If we closely look at the requirements that we should know, then it is how to play with multi-dimensional arrays. With Python, we can write a big script with less code. Many emerging technologies need this aspect to work. ML, AI, big data, Hadoop, automation needs python to do more in fewer amounts of time. The packages like Numpy will be the added advantage in this.

This is a guide to 3d Arrays in Python. Here we discuss how 3D Arrays are defined in Python along with creation, insertion and removing the elements of 3D Arrays in Python. You may also look at the following articles to learn more –

  1. Constructor in Python
  2. Boolean Operators in Python
  3. 3D Arrays in C
  4. 3D Arrays in Java

Can you have a 3D list in Python?

Python uses its native list class for array data structures. A 3D list is a list of lists containing lists with the innermost lists holding the 3D lists's values. For example, [[[0, 0], [0, 0]], [[0, 0], [0, 0]]] is a 2-by-2-by-2 3D list of zeros.

Can an array be 3

A 3D array is a multi-dimensional array(array of arrays). A 3D array is a collection of 2D arrays . It is specified by using three subscripts:Block size, row size and column size. More dimensions in an array means more data can be stored in that array.

How do you access a 3

The following code creates a 3-dimensional array:.
# a 3D array, shape-(2, 2, 2) >>> d3_array = np. ... .
# retrieving a single element from a 3D-array >>> d3_array[0, 1, 0] 2..
# retrieving a 1D sub-array from a 3D-array >>> d3_array[:, 0, 0] array([0, 4]).

How do you declare a 3

Two dimensional array: int[][] twoD_arr = new int[10][20]; Three dimensional array: int[][][] threeD_arr = new int[10][20][30];.
data_type: Type of data to be stored in the array. ... .
dimension: The dimension of the array created. ... .
array_name: Name of the array..