Numpy :
Numpy is a python library which is used to perform wide variety of mathematical operations on array.
The question now arises as to why we require NumPy when we have lists and can execute these operations directly in Python ?. 🤔
So, the answer is that NumPy intends to deliver an array object that is up to 50 times faster than typical Python lists or Python operations. ⚡️
Where it used ?
NumPy 🚀 enables efficient numerical computing and array operations in :
 Scientific computing
 Data analysis
 Machine learning
 Signal processing
 Image processing
 Statistical analysis
 Financial and economic modelling
Basics of NumPy:
How to install :
pip install numpy
How to import :
import numpy as np
Creating NumPy Array :
arr = np.array([1, 2, 3, 4])
Change DataType of Array :
arr = np.array([1,2,3],dtype=float)
Creating 2Dimensional Array :
arr = np.array([(1,2,3,4),(7,8,9,10)],dtype=int)
Dummy Arrays Creation :
Creating Dummy array of zeroes(2x3 matrix) :
arr = np.zeros((2,3))
Creating Dummy Array of Specific Number :
Here (3,4) refers to (rows x columns) with all values of 3.
arr = np.full((3,4),3)
Creating Dummy arrays of ones (3x4 matrix):
arr = np.ones((3,4))
Creating array of 0 with 1 on diagonal (4x4 matrix) :
arr = np.eye(4)
Creating matrix of (3x5 matrix) random number:
arr = np.random.rand(3,5)
Properties of Arrays :

arr.size
 Returns number of elements in array. 
arr.shape
 Returns dimensions of array(rows, columns) 
arr.dtype
 Returns data type of elements in array 
arr.ndim
 Returns number of array dimension
Arithmetic Operations
Assume a and b are array or matrices.
Addition:
np.add(a,b)
Subtraction
np.subtract(a,b)
Division :
np.divide(a,b)
Multiply :
np.multiply(a,b)
Exponential:
np.exp(a)
Square root :
np.sqrt(a)
Logarithm :
np.log(a)
Dot Product :
a.dot(b)
Important Inbuilt functions
Creating Copy of Array :
arr_two = arr_one.copy()
Sorting of an Array :
sorted_arr = arr.sort()
Transpose of an Array :
t = np.transpose(a)
Need Help ?
np.info(np.ndarray.dtype)
That's all in this blog.Feel free to add more useful methods to this cheatsheet! 📝✨
Top comments (4)
I use this :
For Concatenate arrays
Nice one !!
Thanks for sharing.
@jagroop2001 , Very insightful!
I kept up with you over your adventure, and I eagerly await your blogs each week. I hope you'll share it frequently.
Thanks, @works!!
Thank you for your support. I'd attempt to maintain consistency and post twice a week.