Python programs

 1)


#Using intersection()

list1=[10,20,30,40,50,'geeks']

list2=[10,20,'geeks']

if(set(list1).intersection(set(list2))==set(list2)):

    print("Sublist exist")

else:

    print("Sublist not exist")


#Getting i/p from user

l1=list(input(""))

print("List1:",l1)

l2=list(input(""))

print("List2:",l2)

flag=False

for i in range(len(l1)-len(l2)+1):

    if l1[i:i+len(l2)]==l2:

        flag=True

        break

print("Is sublist present in list....",flag)


#Using for loop

list1=[10,20,30,40,50]

list2=[10,20]

list=False

for i in range(0,len(list1)):

    j=0

    while((i+j)<len(list1) and j<len(list2) and list1[i+j] == list2[j]):

        j+=1

    if j==len(list2):

        list=True

        break

if(list):

    print("Sublist exist")

else:

    print("Sublist not exist")



#Using subset()

list1=[10,20,30,40,50]

list2=[10,20]

print(set(list2).issubset(set(list1)))


OUTPUT:


Sublist exist


123456

List1: ['1', '2', '3', '4', '5', '6']

123

List2: ['1', '2', '3']

Is sublist present in list.... True


Sublist exist


True










2)


def dict(dictionary):

    values = list(dictionary.values())

    average = sum(values) / len(values)

    new_dict = {key: average for key in dictionary}

    return new_dict

dict1 = {'a': 10, 'b': 20, 'c': 30}

new_dict= dict(dict1)

print("Dictionary:",dict1)

print("Values Replaced by Average:", new_dict)


OUTPUT:

Dictionary: {'a': 10, 'b': 20, 'c': 30}

Values Replaced by Average: {'a': 20.0, 'b': 20.0, 'c': 20.0}









3)

t1=(1,4,5,6,11,30,40,56)

t2=('Python','java',)

print("Tuple elements:",t1+t2)

print("Length:",len(t1))

print("3rd element:",t1[3])

print("Value at t2[-1]:",t2[-1])

print("Repetition:",t2*3)

print("Slicing:",t1[2:5])

print("Slicing:",t1[1:])

print("Slicing:",t1[:4])

print("Slicing:",t1[2:5:2])

print("Slicing:",t1[::-2])

l1=[23,34,45]

print("List1:",tuple(l1))


OUTPUT:

Tuple elements: (1, 4, 5, 6, 11, 30, 40, 56, 'Python', 'java')

Length: 8

3rd element: 6

Value at t2[-1]: java

Repetition: ('Python', 'java', 'Python', 'java', 'Python', 'java')

Slicing: (5, 6, 11)

Slicing: (4, 5, 6, 11, 30, 40, 56)

Slicing: (1, 4, 5, 6)

Slicing: (5, 11)

Slicing: (56, 30, 6, 4)

List1: (23, 34, 45)







4)


import numpy as np

array = np.arange(8) 

print("Original array") 

print(array)  

print("Power of 3 for every element-wise:") 

print(np.power(array, 3))

a1= np.arange(5) 

a2 = np.arange(0, 10, 2) 

print("Array1:",a1) 

print("Array2:", a2) 

print("Power of array1 to array2",a1**a2)


OUTPUT:


Original array

[0 1 2 3 4 5 6 7]

Power of 3 for every element-wise:

[  0   1   8  27  64 125 216 343]

Array1: [0 1 2 3 4]

Array2: [0 2 4 6 8]

Power of array1 to array2 [    1     1    16   729 65536]












5)


def ispangram(str):

   alphabet = "abcdefghijklmnopqrstuvwxyz"

   for char in alphabet:

      if char not in str.lower():

         return False

   return True

string = input(“Enter a string:”)

if(ispangram(string) == True):

   print("This is pangram")

else:

   print("This is not pangram")


OUTPUT:

Enter a string:qwertyuiopasdfghjklzxcvbnm

This is pangram


6)

from sklearn import datasets

from sklearn.tree import DecisionTreeClassifier

from sklearn.model_selection import KFold, cross_val_score

X, y = datasets.load_iris(return_X_y=True)

clf = DecisionTreeClassifier(random_state=42)

k_folds = KFold(n_splits = 5)

scores = cross_val_score(clf, X, y, cv = k_folds)

print("Cross Validation Scores: ", scores)

print("Average CV Score: ", scores.mean())

print("Number of CV Scores used in Average: ", len(scores))


Output:

Cross Validation Scores:  [1.         1.         0.83333333 0.93333333 0.8       ]

Average CV Score:  0.9133333333333333

Number of CV Scores used in Average:  5



7)


import csv

with open('sample1.csv') as sam:

    file=csv.reader(sam)

    for row in file:

        print(row)

        

sample.csv

ROLL.no Name Department

23MCA001 Abi MCA

23MCA002 Amudha MCA

23MCA003 Aruljothi MCA

23MCA004 Divya MCA

23MCA005 Duruv MCA

23MCA006 Kalai MCA

23MCA007 Mano MCA

23MCA008 Pavithra MCA

23MCA009 Priya MCA

23MCA010 Saranya MCA


OUTPUT:


['ROLL.no', 'Name', 'Department']

['23MCA001', 'Abi', 'MCA']

['23MCA002', 'Amudha', 'MCA']

['23MCA003', 'Aruljothi', 'MCA']

['23MCA004', 'Divya', 'MCA']

['23MCA005', 'Duruv', 'MCA']

['23MCA006', 'Kalai', 'MCA']

['23MCA007', 'Mano', 'MCA']

['23MCA008', 'Pavithra', 'MCA']

['23MCA009', 'Priya', 'MCA']

['23MCA010', 'Saranya', 'MCA']


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