import numpy as np
x = np.array([11, 13, 121, 181, 99, 100])
print('Numpy Array Elements',x)
print ('Minimum Value in array',x.min())
print ('Maximum Value in array',x.max())
print ('Index of Minimum Value',x.argmin())
print ('Index of Maximum Value',x.argmax())
print ('Mean of Array Values',x.mean())
print ('Median of Array Values',np.median(x))
print ('Standard deviation of Array Values',x.std())
Solve Problems by Coding Solutions - A Complete solution for python programming
Elementwise sum of two array elemets
import numpy as np
x = [[11,22],[33,44]]
y = [[55,66],[77,88]]
x1 = np.array([[11,22],[33,44]], dtype=np.int32)
y1 = np.array([[55,66],[77,88]], dtype=np.int32)
print("ADD USING LIST\n",x + y)
print("ADD NUMPY ARRAY\n",np.add(x1, y1))
x = [[11,22],[33,44]]
y = [[55,66],[77,88]]
x1 = np.array([[11,22],[33,44]], dtype=np.int32)
y1 = np.array([[55,66],[77,88]], dtype=np.int32)
print("ADD USING LIST\n",x + y)
print("ADD NUMPY ARRAY\n",np.add(x1, y1))
Datatypes in Numpy
import numpy as np
x = np.array([101, 202])
print(x.dtype)
x = np.array([11.75, 21.75])
print(x.dtype)
x = np.array([1, 2], dtype=np.int64)
print(x.dtype)
x = np.array([1, 2], dtype=np.complex128)
print(x.dtype)
x = np.array([101, 202])
print(x.dtype)
x = np.array([11.75, 21.75])
print(x.dtype)
x = np.array([1, 2], dtype=np.int64)
print(x.dtype)
x = np.array([1, 2], dtype=np.complex128)
print(x.dtype)
2D-array representation using with & without numpy implementation
import numpy as np
a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])
print ("Using Numpy\n",a)
b=[[1,2,3,4], [5,6,7,8], [9,10,11,12]]
print ("Without Numpy\n", b)
a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])
print ("Using Numpy\n",a)
b=[[1,2,3,4], [5,6,7,8], [9,10,11,12]]
print ("Without Numpy\n", b)
Matrix representation and version detailsof Numpy
import numpy as np
print("\nVersion of Numpy is ",np.__version__)
x = np.arange(25, 50).reshape(5,5)
print("\n Matrix representation in Numpy\n",x)
print("\nVersion of Numpy is ",np.__version__)
x = np.arange(25, 50).reshape(5,5)
print("\n Matrix representation in Numpy\n",x)
Different Set Operations
A = {1,2,3,4,5,6,7,8};
B = {5,10,15,20,25,30,35,40};
print("Union of A and B is",A | B)
print("\nIntersection of A and B is",A & B)
print("\nDifference of A and B is",A - B)
print("\nSymmetric difference of A and B is",A ^ B)
B = {5,10,15,20,25,30,35,40};
print("Union of A and B is",A | B)
print("\nIntersection of A and B is",A & B)
print("\nDifference of A and B is",A - B)
print("\nSymmetric difference of A and B is",A ^ B)
Use pass for an empty block
#Credits to NPTEL MOOC, Programming, Data Structures & Algorithms in #Python by Madhavan Mukund, Chennai Mathematical Institute
while(True):
try:
userdata = input("Enter a number: ")
usernum = int(userdata)
except ValueError:
print("Not a number. Try again")
except NameError:
pass
else:
break
Check wheather a number is composite or not
#Credits to NPTEL MOOC, Programming, Data Structures & Algorithms in #Python by Madhavan Mukund, Chennai Mathematical Institute
def composite(n): for i in range(2,n): if n%i == 0: return(True) return(False)
Divison with multiple conditions
#Credits to NPTEL MOOC, Programming, Data Structures & Algorithms in #Python by Madhavan Mukund, Chennai Mathematical Institute
def divides(m,n):
if n%m == 0:
return(True)
else:
return(False)
def even(n):
return(divides(2,n))
def odd(n):
return(not divides(2,n))
GCD using euclids algorithms & looping
# Credits to NPTEL MOOC,Programming, Data Structures & Algorithms
#in Python by Madhavan Mukund, Chennai Mathematical Institute
def gcd(m,n):
if m < n: # Assume m >= n
(m,n) = (n,m)
while (m%n) != 0:
diff = m-n
# diff > n? Possible!
(m,n) = (max(n,diff),min(n,diff))
return(n)
#in Python by Madhavan Mukund, Chennai Mathematical Institute
def gcd(m,n):
if m < n: # Assume m >= n
(m,n) = (n,m)
while (m%n) != 0:
diff = m-n
# diff > n? Possible!
(m,n) = (max(n,diff),min(n,diff))
return(n)
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