Benefits of using numpy module in Python (Part 1)

A demonstration on how Python's numpy module is Fast, convenient and
takes up less memory.

Author: Juzer Shakir

How_to_Python/Modules/Numpy/Numpy_operation_1.py

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+""" Author : Juzer Shakir   ||  Created on 10 Nov 2017     ||   Last modified on 19 Dec 2017 10:10am
+Topic : How to use numpy module in python (Introduction 1)
+
+What Numpy can do?
+#1. Find the dimension of the array
+#2. Find the byte size of each element
+#3. Find the data type of the elements
+#4. Find the size of an array (finding total number of elements)
+#5. Find the shape of an array (giving you no. of columns and rows)
+#6. You can reshape the array
+#7. You can slice the array
+#8. Finding min, max and sum of the elements in the array"""
+"""----------------------------------------------------------------------------------------------------------------------------------------------------------"""
+
+import numpy as np
+
+#----1
+a = np.array([(1, 2, 3), (4, 5, 6)])
+print(a)
+#this will give us the dimension of the numpy variable
+dim = a.ndim
+print("\nThe dimension of this array is --> {}".format(dim))
+"""----------------------------------------------------------------------------------------------------------------------------------------------------------"""
+
+#----2
+#this will give the byte size of the array
+size = a.itemsize
+print("\nThe size is --> {} bytes".format(size))
+"""----------------------------------------------------------------------------------------------------------------------------------------------------------"""
+
+#----3
+#this will give the data type the array
+data_type = a.dtype
+print("\nThe data type of this array is --> {}".format(data_type))
+"""----------------------------------------------------------------------------------------------------------------------------------------------------------"""
+
+#----4
+#this will give the size of the array(no.of elements)
+size = a.size
+print("\nThe number of elements in this array are --> {}".format(size))
+"""----------------------------------------------------------------------------------------------------------------------------------------------------------"""
+
+#-----5
+#this will give the shape of the array (no. of rows and no. of columns)
+shape = a.shape
+print("\nThere are {} number of rows and columns respectively.".format(shape))
+"""----------------------------------------------------------------------------------------------------------------------------------------------------------"""
+
+#-----6
+#this will reshape the shape of the array to different rows and columns (arguments - (r,c))
+reshape = a.reshape(3, 2)
+print("\nThe new shape of the array is \n {}".format(reshape))
+"""----------------------------------------------------------------------------------------------------------------------------------------------------------"""
+
+#-----7
+#this will output a specific number in the elemnts of an array(arguments (r,c))
+n = a[0,2]
+print("\nThe number at the first row and third column is {}".format(n))
+#printing third column of every rows (arguments (r,c))
+n3 = a[0: ,2]
+print("\nThe number at every row of third column is {}".format(n3))
+"""----------------------------------------------------------------------------------------------------------------------------------------------------------"""
+
+#----8
+#Finding maximum value in the array
+maxn = a.max()
+print("\nThe maximum value in this array is {}".format(maxn))
+#Finding minimum value in the array
+minn = a.min()
+print("\nThe minimum value in this array is {}".format(minn))
+#Finding sum of all the value in the array
+sumn = a.sum()
+print("\nThe sum of all the value in the array is {}".format(sumn))
+"""----------------------------------------------------------------------------------------------------------------------------------------------------------"""
+
+
+#That's it!
+print("\nThe End!")