# Introduction To Numpy

### In this Blog, I will be writing about all the basic stuff you need to know about numpy .


- 
### What is NumPy?

     NumPy(Numerical Python) is a Python library used for working with arrays.


- 

### Why Use NumPy?

     In Python we have lists that serve the purpose of arrays, but they are slow to process.
     NumPy aims to provide an array object that is up to 50x faster than traditional Python 
     lists.The array object in NumPy is called *ndarray*.

     Numpy Arrays are very frequently used in data science.


- 
### Installing NumPy

      pip install numpy




- 
### Importing NumPy
   To import NumPy in your workspace
        import numpy as np


1. 
### Creating array using NumPy

  The array object in NumPy is called ndarray.

   We can create a NumPy ndarray object by using the array() function.

   Example :
         import numpy as np
         arr=np.array([2,4,6,8,10])
         print(arr)
         type(arr)
   type() - Built in python library which tells the type of object passed.
   Here it will show - numpy.ndarray

2. ### NumPy Array Indexing
    You can access an array element by referring to its index number.

     The indexes in NumPy arrays start with 0, meaning that the first element has index 0, 
      and the second has index 1 etc.

    Example - Access 2nd element of an array.
         import numpy as np
         arr=np.array([1,3,5,7])
         print(arr[1])
      
         #output -> 3

3. ### Access 2-D Arrays
      To access elements from 2-D arrays we can use comma separated integers 
      representing the dimension and the index of the element.
     
      Example - Access 4th element on 2nd dimension .

            import numpy as np
            arr=np.array([[1,2,3,4,5],[6,7,8,9]])
            print(‘4th element on 2nd dim: ‘, arr[1, 3])
        
            #output -> 9

4. ###  Array Slicing
      Slicing in python means taking elements from one given index to another given index.

      We pass slice instead of index like this: [start:end].

      Example - Access elements from index 2 to 5

            import numpy as np
            arr=np.array([1,2,3,4,5,6])
            print(arr[2:5])

            #output -> [3,4,5]

5. ### NumPy Array Shape

      NumPy arrays have an attribute called shape that returns a tuple with each index 
      having the number of corresponding elements.

      Example - Print shape of 2D Array-

          import numpy as np

          arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])

          print(arr.shape)
          
          #output -> (2,4)



I tried to provide all the important information on numpy for beginners. I hope you will find something useful here. Happy Learning !!