Numpy
NumPy is a python library, and it’s used for working with arrays.
It provides a high-performance multidimensional array object, and tools for working with these. arrays.it’s also provide many function to create arrays
it’s written partially in Python, but most of the parts that require fast computation are written in C or C++.
How to Install NumPy
If you have Python on your system and PIP already installed on a system, then you can easily install numpy .
Install it using this command:
If this command fails in your system , then use a python distribution already has NumPy installed like, Spyder ,Anaconda etc.
Import NumPy
After the installation of NumPy , import it in your application by adding the import keyword:
NumPy as np
It is (numpy)usually imported under the np alias.
for Create an alias with the as keyword while importing
Import numpy as np
Creating 0-D Arrays
import numpy as np
arr = np.array(42)
print(arr)
Creating 1-D Arrays
import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
print(arr)
3-D Array
import numpy as np
arr = np. array ([[[1, 3, 2], [6, 5, 4]], [[4, 5, 3], [7, 5, 6]]])
print(arr)
Check Number of Dimensions
Import numpy as np
b = np.array([1, 2, 3, 4, 5])
print(b.ndim)
Access Array Elements
We can access an array element by referring to its index number.
import numpy as np
arr = np.array([1, 2, 3, 4])
print(arr[0])
Access 2-D Arrays
for access elements from 2-D arrays we can use comma separated integers it’s representing the dimension and the index of the element.
Access the 2nd element on the 1st dim:
import numpy as np
arr = np.array([[1,5,3,2,4], [7,11,8,9,10]])
print(‘2nd element on 1st dim: ‘, arr[0, 1])
Conclusion
In this blog you can learn about Numpy , and how to install numpy in your system(python) ,How to use numpy like-how to create Arrays (1-D Array ,2-D Array etc.)you can also learn about how to access these array and element .
References
numpy.org
https://www.tutorialspoint.com/numpy/index.html
w3schools.com/python/numpy_intro.asp
