Java Tutorial - Arrays and ForEach Loop
This tutorialvideo on 'Arrays in Python' will help you establish a strong hold on all the fundamentals in python programming language. Below are the topics covered in this video:
1:15 What is an array?
2:53 Is python list same as an array?
3:48 How to create arrays in python?
7:19 Accessing array elements
9:59 Basic array operations
- 10:33 Finding the length of an array
- 11:44 Adding Elements
- 15:06 Removing elements
- 18:32 Array concatenation
- 20:59 Slicing
- 23:26 Looping
Python Array Tutorial – Define, Index, Methods
In this article, you'll learn how to use Python arrays. You'll see how to define them and the different methods commonly used for performing operations on them.
The artcile covers arrays that you create by importing the
array module. We won't cover NumPy arrays here.
Let's get started!
Arrays are a fundamental data structure, and an important part of most programming languages. In Python, they are containers which are able to store more than one item at the same time.
Specifically, they are an ordered collection of elements with every value being of the same data type. That is the most important thing to remember about Python arrays - the fact that they can only hold a sequence of multiple items that are of the same type.
Lists are one of the most common data structures in Python, and a core part of the language.
Lists and arrays behave similarly.
Just like arrays, lists are an ordered sequence of elements.
They are also mutable and not fixed in size, which means they can grow and shrink throughout the life of the program. Items can be added and removed, making them very flexible to work with.
However, lists and arrays are not the same thing.
Lists store items that are of various data types. This means that a list can contain integers, floating point numbers, strings, or any other Python data type, at the same time. That is not the case with arrays.
As mentioned in the section above, arrays store only items that are of the same single data type. There are arrays that contain only integers, or only floating point numbers, or only any other Python data type you want to use.
Lists are built into the Python programming language, whereas arrays aren't. Arrays are not a built-in data structure, and therefore need to be imported via the
array module in order to be used.
Arrays of the
array module are a thin wrapper over C arrays, and are useful when you want to work with homogeneous data.
They are also more compact and take up less memory and space which makes them more size efficient compared to lists.
If you want to perform mathematical calculations, then you should use NumPy arrays by importing the NumPy package. Besides that, you should just use Python arrays when you really need to, as lists work in a similar way and are more flexible to work with.
In order to create Python arrays, you'll first have to import the
array module which contains all the necassary functions.
There are three ways you can import the
import arrayat the top of the file. This includes the module
array. You would then go on to create an array using
import array #how you would create an array array.array()
array.array()all the time, you could use
import array as arrat the top of the file, instead of
import arrayalone. You would then create an array by typing
arracts as an alias name, with the array constructor then immediately following it.
import array as arr #how you would create an array arr.array()
from array import *, with
*importing all the functionalities available. You would then create an array by writing the
from array import * #how you would create an array array()
Once you've imported the
array module, you can then go on to define a Python array.
The general syntax for creating an array looks like this:
variable_name = array(typecode,[elements])
Let's break it down:
variable_namewould be the name of the array.
typecodespecifies what kind of elements would be stored in the array. Whether it would be an array of integers, an array of floats or an array of any other Python data type. Remember that all elements should be of the same data type.
elementsthat would be stored in the array, with each element being separated by a comma. You can also create an empty array by just writing
variable_name = array(typecode)alone, without any elements.
Below is a typecode table, with the different typecodes that can be used with the different data types when defining Python arrays:
|TYPECODE||C TYPE||PYTHON TYPE||SIZE|
|'q'||signed long long||int||8|
|'Q'||unsigned long long||int||8|
Tying everything together, here is an example of how you would define an array in Python:
import array as arr numbers = arr.array('i',[10,20,30]) print(numbers) #output #array('i', [10, 20, 30])
Let's break it down:
import array as arr.
import array as arr.
array()constructor, we first included
i, for signed integer. Signed integer means that the array can include positive and negative values. Unsigned integer, with
Hfor example, would mean that no negative values are allowed.
Keep in mind that if you tried to include values that were not of
i typecode, meaning they were not integer values, you would get an error:
import array as arr numbers = arr.array('i',[10.0,20,30]) print(numbers) #output #Traceback (most recent call last): # File "/Users/dionysialemonaki/python_articles/demo.py", line 14, in <module> # numbers = arr.array('i',[10.0,20,30]) #TypeError: 'float' object cannot be interpreted as an integer
In the example above, I tried to include a floating point number in the array. I got an error because this is meant to be an integer array only.
Another way to create an array is the following:
from array import * #an array of floating point values numbers = array('d',[10.0,20.0,30.0]) print(numbers) #output #array('d', [10.0, 20.0, 30.0])
The example above imported the
array module via
from array import * and created an array
numbers of float data type. This means that it holds only floating point numbers, which is specified with the
To find out the exact number of elements contained in an array, use the built-in
It will return the integer number that is equal to the total number of elements in the array you specify.
import array as arr numbers = arr.array('i',[10,20,30]) print(len(numbers)) #output # 3
In the example above, the array contained three elements –
10, 20, 30 – so the length of
Each item in an array has a specific address. Individual items are accessed by referencing their index number.
Indexing in Python, and in all programming languages and computing in general, starts at
0. It is important to remember that counting starts at
0 and not at
To access an element, you first write the name of the array followed by square brackets. Inside the square brackets you include the item's index number.
The general syntax would look something like this:
Here is how you would access each individual element in an array:
import array as arr numbers = arr.array('i',[10,20,30]) print(numbers) # gets the 1st element print(numbers) # gets the 2nd element print(numbers) # gets the 3rd element #output #10 #20 #30
Remember that the index value of the last element of an array is always one less than the length of the array. Where
n is the length of the array,
n - 1 will be the index value of the last item.
Note that you can also access each individual element using negative indexing.
With negative indexing, the last element would have an index of
-1, the second to last element would have an index of
-2, and so on.
Here is how you would get each item in an array using that method:
import array as arr numbers = arr.array('i',[10,20,30]) print(numbers[-1]) #gets last item print(numbers[-2]) #gets second to last item print(numbers[-3]) #gets first item #output #30 #20 #10
You can find out an element's index number by using the
You pass the value of the element being searched as the argument to the method, and the element's index number is returned.
import array as arr numbers = arr.array('i',[10,20,30]) #search for the index of the value 10 print(numbers.index(10)) #output #0
If there is more than one element with the same value, the index of the first instance of the value will be returned:
import array as arr numbers = arr.array('i',[10,20,30,10,20,30]) #search for the index of the value 10 #will return the index number of the first instance of the value 10 print(numbers.index(10)) #output #0
You've seen how to access each individual element in an array and print it out on its own.
You've also seen how to print the array, using the
print() method. That method gives the following result:
import array as arr numbers = arr.array('i',[10,20,30]) print(numbers) #output #array('i', [10, 20, 30])
What if you want to print each value one by one?
This is where a loop comes in handy. You can loop through the array and print out each value, one-by-one, with each loop iteration.
For this you can use a simple
import array as arr numbers = arr.array('i',[10,20,30]) for number in numbers: print(number) #output #10 #20 #30
You could also use the
range() function, and pass the
len() method as its parameter. This would give the same result as above:
import array as arr values = arr.array('i',[10,20,30]) #prints each individual value in the array for value in range(len(values)): print(values[value]) #output #10 #20 #30
To access a specific range of values inside the array, use the slicing operator, which is a colon
When using the slicing operator and you only include one value, the counting starts from
0 by default. It gets the first item, and goes up to but not including the index number you specify.
import array as arr #original array numbers = arr.array('i',[10,20,30]) #get the values 10 and 20 only print(numbers[:2]) #first to second position #output #array('i', [10, 20])
When you pass two numbers as arguments, you specify a range of numbers. In this case, the counting starts at the position of the first number in the range, and up to but not including the second one:
import array as arr #original array numbers = arr.array('i',[10,20,30]) #get the values 20 and 30 only print(numbers[1:3]) #second to third position #output #rray('i', [20, 30])
Arrays are mutable, which means they are changeable. You can change the value of the different items, add new ones, or remove any you don't want in your program anymore.
Let's see some of the most commonly used methods which are used for performing operations on arrays.
You can change the value of a specific element by speficying its position and assigning it a new value:
import array as arr #original array numbers = arr.array('i',[10,20,30]) #change the first element #change it from having a value of 10 to having a value of 40 numbers = 40 print(numbers) #output #array('i', [40, 20, 30])
To add one single value at the end of an array, use the
import array as arr #original array numbers = arr.array('i',[10,20,30]) #add the integer 40 to the end of numbers numbers.append(40) print(numbers) #output #array('i', [10, 20, 30, 40])
Be aware that the new item you add needs to be the same data type as the rest of the items in the array.
Look what happens when I try to add a float to an array of integers:
import array as arr #original array numbers = arr.array('i',[10,20,30]) #add the integer 40 to the end of numbers numbers.append(40.0) print(numbers) #output #Traceback (most recent call last): # File "/Users/dionysialemonaki/python_articles/demo.py", line 19, in <module> # numbers.append(40.0) #TypeError: 'float' object cannot be interpreted as an integer
But what if you want to add more than one value to the end an array?
extend() method, which takes an iterable (such as a list of items) as an argument. Again, make sure that the new items are all the same data type.
import array as arr #original array numbers = arr.array('i',[10,20,30]) #add the integers 40,50,60 to the end of numbers #The numbers need to be enclosed in square brackets numbers.extend([40,50,60]) print(numbers) #output #array('i', [10, 20, 30, 40, 50, 60])
And what if you don't want to add an item to the end of an array? Use the
insert() method, to add an item at a specific position.
insert() function takes two arguments: the index number of the position the new element will be inserted, and the value of the new element.
import array as arr #original array numbers = arr.array('i',[10,20,30]) #add the integer 40 in the first position #remember indexing starts at 0 numbers.insert(0,40) print(numbers) #output #array('i', [40, 10, 20, 30])
To remove an element from an array, use the
remove() method and include the value as an argument to the method.
import array as arr #original array numbers = arr.array('i',[10,20,30]) numbers.remove(10) print(numbers) #output #array('i', [20, 30])
remove(), only the first instance of the value you pass as an argument will be removed.
See what happens when there are more than one identical values:
import array as arr #original array numbers = arr.array('i',[10,20,30,10,20]) numbers.remove(10) print(numbers) #output #array('i', [20, 30, 10, 20])
Only the first occurence of
10 is removed.
You can also use the
pop() method, and specify the position of the element to be removed:
import array as arr #original array numbers = arr.array('i',[10,20,30,10,20]) #remove the first instance of 10 numbers.pop(0) print(numbers) #output #array('i', [20, 30, 10, 20])
And there you have it - you now know the basics of how to create arrays in Python using the
array module. Hopefully you found this guide helpful.
Thanks for reading and happy coding!
OpenJDk or Open Java Development Kit is a free, open-source framework of the Java Platform, Standard Edition (or Java SE). It contains the virtual machine, the Java Class Library, and the Java compiler. The difference between the Oracle OpenJDK and Oracle JDK is that OpenJDK is a source code reference point for the open-source model. Simultaneously, the Oracle JDK is a continuation or advanced model of the OpenJDK, which is not open source and requires a license to use.
In this article, we will be installing OpenJDK on Centos 8.
#tutorials #alternatives #centos #centos 8 #configuration #dnf #frameworks #java #java development kit #java ee #java environment variables #java framework #java jdk #java jre #java platform #java sdk #java se #jdk #jre #open java development kit #open source #openjdk #openjdk 11 #openjdk 8 #openjdk runtime environment
When we’re programming in R (or any other language, for that matter), we often want to control when and how particular parts of our code are executed. We can do that using control structures like if-else statements, for loops, and while loops.
Control structures are blocks of code that determine how other sections of code are executed based on specified parameters. You can think of these as a bit like the instructions a parent might give a child before leaving the house:
“If I’m not home by 8pm, make yourself dinner.”
Control structures set a condition and tell R what to do when that condition is met or not met. And unlike some kids, R will always do what we tell it to! You can learn more about control structures in the R documentation if you would like.
In this tutorial, we assume you’re familiar with basic data structures, and arithmetic operations in R.
Not quite there yet? Check out our Introductory R Programming course that’s part of our Data Analyst in R path. It’s free to start learning, there are no prerequisites, and there’s nothing to install — you can start learning in your browser right now.
Start learning R today with our Introduction to R course — no credit card required!
(This tutorial is based on our intermediate R programming course, so check that out as well! It’s interactive and will allow you to write and run code right in your browser.)
In order to use control structures, we need to create statements that will turn out to be either
FALSE. In the kids example above, the statement “It’s 8pm. Are my parents home yet?” yields
TRUE (“Yes”) or
FALSE (“No”). In R, the most fundamental way to evaluate something as
FALSE is through comparison operators.
Below are six essential comparison operators for working with control structures in R:
==means equality. The statement
x == aframed as a question means “Does the value of
xequal the value of
!=means “not equal”. The statement
x == bmeans “Does the value of
xnot equal the value of
<means “less than”. The statement
x < cmeans “Is the value of
xless than the value of
<=means “less than or equal”. The statement
x <= dmeans “Is the value of
xless or equal to the value of
>means “greater than”. The statement
x >e means “Is the value of
xgreater than the value of
>=means “greater than or equal”. The statement
x >= fmeans “Is the value of
xgreater than or equal to the value of
#data science tutorials #beginner #for loop #for loops #if #if else #learn r #r #r tutorial #rstats #tutorial #tutorials #while loop #while loops
Printing an array is a quick way to give us visibility on the values of the contents inside. Sometimes the array values are the desired output of the program.
In this article, we’ll take a look at how to print an array in Java using four different ways.
While the “best way” depends on what your program needs to do, we begin with the simplest method for printing and then show more verbose ways to do it.
#java #array #how to print an array in java #array in java #print an array in java #print
According to some surveys, such as JetBrains’s great survey, Java 8 is currently the most used version of Java, despite being a 2014 release.
What you are reading is one in a series of articles titled ‘Going beyond Java 8,’ inspired by the contents of my book, Java for Aliens. These articles will guide you step-by-step through the most important features introduced to the language, starting from version 9. The aim is to make you aware of how important it is to move forward from Java 8, explaining the enormous advantages that the latest versions of the language offer.
In this article, we will talk about the most important new feature introduced with Java 10. Officially called local variable type inference, this feature is better known as the **introduction of the word **
var. Despite the complicated name, it is actually quite a simple feature to use. However, some observations need to be made before we can see the impact that the introduction of the word
var has on other pre-existing characteristics.
#java #java 11 #java 10 #java 12 #var #java 14 #java 13 #java 15 #verbosity