array

array Python Lists type error 

TypeError: Array() Argument 1 Must Be A Unicode Character, Not List

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In a recent post, we discussed arrays and what they mean and how they differ from lists. When you have a list in an array, one of the things that you need to define is what data type it is. If you don’t then the array will throw the error that you are on this page to resolve.

On the Python.org website, below are the list of values that can be populated to indicate what the data type of a list is in an array.

If you don’t add in the value you will get the below error:

ValueError: bad typecode (must be b, B, u, h, H, i, I, l, L, q, Q, f or d)

Let’s look at an example

import array as test_array

a = test_array.array([1,2,3])

print(a)

Gives an error of:
TypeError: array() argument 1 must be a unicode character, not list

As can be seen, the above logic tries to print a list within an array. The problem here is that an array can only be of one data type, and it has to be specified on the array creation.

How do we fix this?

It is quite simple! Before the list, we simply specify which type code we would like to apply from the above list. In this instance we are going to assign it as “signed int” that being the value “i” as follows:

import array as test_array

a = test_array.array("i",[1,2,3])

print(a)

Prints the following with no error:
array('i', [1, 2, 3])

Process finished with exit code 0

I can change the value “i” to any of the values I want from the above list, just picked that one to show as an example.

array numpy Python Python Tutorial 

What Is An Array In Python?

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Estimated reading time: 3 minutes

Python arrays are used to manage how data is analysed and have the data in a structured form for the data analyst or data scientist to use.

What is an Array?

An array has the following properties:

  1. The data in it is of the same data type.
  2. The data is stored as contiguous memory locations, meaning the lowest value is at index 0 and the last value is at the highest index value.
  3. Arrays assign index values to each data point contained within it.
  4. You can append values to the array.
  5. You can delete values from the array, that is it is mutable.

What are the differences between arrays and lists?

For the most part arrays and lists are the same, but with one difference:

A list can store any data type you want e.g. strings, integers etc.

On the other hand, arrays can only store data that is of the same data type.

What are the different ways that I can create an array?

(A) Use Numpy 

# Use numpy

import numpy as np

a = np.array([1,2,3,4])

print(a)
print(type(a))
print(a.dtype)

Output:
[1 2 3 4]
<class 'numpy.ndarray'>
int32

If we have one of the values as a string, all the other values are converted to a string , as follows:
# Use numpy

import numpy as np

a = np.array([1,2,3,'4'])

print(a)
print(type(a))
print(a.dtype)

Output:

['1' '2' '3' '4']
<class 'numpy.ndarray'>
<U11

# <U11 - When this happens, it means one of the values was returning as a string
# All the other values in the array as a result are converted to strings

(B) Use array

import array as test_array

a = test_array.array('i',[1,2,3])

print(a)
print(type(a))

Output:
array('i', [1, 2, 3])
<class 'array.array'>

On the Python.org website, below are the list of values that can be populated into the above program, depending on what your need is:

When should I use arrays?

It really depends on the nature of your python program, but below are some examples that may help you make a decision:

(A) Many variables of the same type : There maybe a scenario where you have to create an array to store data that is of the same data type. For example you have a list of codes to look up against, which are all integers.

(B) Faster and more efficient : If speed is what you are looking for using arrays, will help improve performance of your computer program, using lists is much slower.

(C) Compactability and efficiency : If the nature of your program needs to store large amounts of data that needs to be accessed quickly , then this would be a good reason to use them.

(D) Ability to retrieve data quickly through indexing: As arrays have index values associated with them, they data can be easiy retrieved.

(E) Need to compute some mathematical values: Arrays are excellent for any numerical operations you need to complete, as the level of coding is minimal.

import array as test_array

a = test_array.array('i',[1,2,3])

mydivider = 2

mynewlist = [x / mydivider for x in a]
print(mynewlist)

result:
[0.5, 1.0, 1.5]

So in summary:

Speed , efficiency and ease of use are the main reasons to use an array.

We use arrays here in how to show percentage differences between files in python , why not go over and see it in action!