1603216440
Nested For loop means “A For loop inside another For loop”. You’ll learn how to loop over nested object keys using ngFor in Angular.
#angular
1666082925
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 array module
:
import array
at the top of the file. This includes the module array
. You would then go on to create an array using array.array()
.import array
#how you would create an array
array.array()
array.array()
all the time, you could use import array as arr
at the top of the file, instead of import array
alone. You would then create an array by typing arr.array()
. The arr
acts 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 array()
constructor alone.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_name
would be the name of the array.typecode
specifies 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.elements
that 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 |
---|---|---|---|
'b' | signed char | int | 1 |
'B' | unsigned char | int | 1 |
'u' | wchar_t | Unicode character | 2 |
'h' | signed short | int | 2 |
'H' | unsigned short | int | 2 |
'i' | signed int | int | 2 |
'I' | unsigned int | int | 2 |
'l' | signed long | int | 4 |
'L' | unsigned long | int | 4 |
'q' | signed long long | int | 8 |
'Q' | unsigned long long | int | 8 |
'f' | float | float | 4 |
'd' | double | float | 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
.numbers
array.arr.array()
because of 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 H
for 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 'd'
typecode.
To find out the exact number of elements contained in an array, use the built-in len()
method.
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 numbers
is 3
.
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 1
.
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:
array_name[index_value_of_item]
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[0]) # gets the 1st element
print(numbers[1]) # gets the 2nd element
print(numbers[2]) # 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 index()
method.
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 for
loop:
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[0] = 40
print(numbers)
#output
#array('i', [40, 20, 30])
To add one single value at the end of an array, use the append()
method:
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?
Use the 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.
The 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])
With 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!
#python #programming
1670560264
Learn how to use Python arrays. Create arrays in Python using the array module. 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 array module
:
import array
at the top of the file. This includes the module array
. You would then go on to create an array using array.array()
.import array
#how you would create an array
array.array()
array.array()
all the time, you could use import array as arr
at the top of the file, instead of import array
alone. You would then create an array by typing arr.array()
. The arr
acts 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 array()
constructor alone.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_name
would be the name of the array.typecode
specifies 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.elements
that 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 |
---|---|---|---|
'b' | signed char | int | 1 |
'B' | unsigned char | int | 1 |
'u' | wchar_t | Unicode character | 2 |
'h' | signed short | int | 2 |
'H' | unsigned short | int | 2 |
'i' | signed int | int | 2 |
'I' | unsigned int | int | 2 |
'l' | signed long | int | 4 |
'L' | unsigned long | int | 4 |
'q' | signed long long | int | 8 |
'Q' | unsigned long long | int | 8 |
'f' | float | float | 4 |
'd' | double | float | 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
.numbers
array.arr.array()
because of 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 H
for 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 'd'
typecode.
To find out the exact number of elements contained in an array, use the built-in len()
method.
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 numbers
is 3
.
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 1
.
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:
array_name[index_value_of_item]
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[0]) # gets the 1st element
print(numbers[1]) # gets the 2nd element
print(numbers[2]) # 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 index()
method.
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 for
loop:
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[0] = 40
print(numbers)
#output
#array('i', [40, 20, 30])
To add one single value at the end of an array, use the append()
method:
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?
Use the 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.
The 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])
With 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.
You'll start from the basics and learn in an interacitve and beginner-friendly way. You'll also build five projects at the end to put into practice and help reinforce what you learned.
Thanks for reading and happy coding!
Original article source at https://www.freecodecamp.org
#python
1599099600
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.
install.packages(“Dataquest”)
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(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 TRUE
or 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 TRUE
or FALSE
is through comparison operators.
Below are six essential comparison operators for working with control structures in R:
==
means equality. The statement x == a
framed as a question means “Does the value of x
equal the value of a
?”!=
means “not equal”. The statement x == b
means “Does the value of x
not equal the value of b
?”<
means “less than”. The statement x < c
means “Is the value of x
less than the value of c
?”<=
means “less than or equal”. The statement x <= d
means “Is the value of x
less or equal to the value of d
?”>
means “greater than”. The statement x >
e means “Is the value of x
greater than the value of e
?”>=
means “greater than or equal”. The statement x >= f
means “Is the value of x
greater than or equal to the value of f
?”#data science tutorials #beginner #for loop #for loops #if #if else #learn r #r #r tutorial #rstats #tutorial #tutorials #while loop #while loops
1598940617
Angular is a TypeScript based framework that works in synchronization with HTML, CSS, and JavaScript. To work with angular, domain knowledge of these 3 is required.
In this article, you will get to know about the Angular Environment setup process. After reading this article, you will be able to install, setup, create, and launch your own application in Angular. So let’s start!!!
For Installing Angular on your Machine, there are 2 prerequisites:
First you need to have Node.js installed as Angular require current, active LTS or maintenance LTS version of Node.js
Download and Install Node.js version suitable for your machine’s operating system.
Angular, Angular CLI and Angular applications are dependent on npm packages. By installing Node.js, you have automatically installed the npm Package manager which will be the base for installing angular in your system. To check the presence of npm client and Angular version check of npm client, run this command:
· After executing the command, Angular CLI will get installed within some time. You can check it using the following command
Now as your Angular CLI is installed, you need to create a workspace to work upon your application. Methods for it are:
To create a workspace:
#angular tutorials #angular cli install #angular environment setup #angular version check #download angular #install angular #install angular cli
1610191977
Angular 9/10/11 social login with google using angularx-social-login library example. In this tutorial, i will show you step by step on how to implement google social login in angular 11 app.
And also, this tutorial will show you How to login into Angular 10/11 application with google using angularx-social-login library in angular 11 app.
https://www.tutsmake.com/angular-11-google-social-login-example/
#angular 11 google login #angular 11 social-login example #login with google button angular 8/9/10/11 #angular 10/11 login with google #angular 10 social google login #angular social login google