Python Programming - Lab Part B

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Program 1: Demonstrate use of Basic Regular Expressions *

import re 
text = "Hello There!" 
#re.match() tries to match a pattern at the beginning of the string. 
match = re.match("Hello", text) 
print("Match: ", match.group() if match else None) 
# re.search() searches the string for a match, and returns a Match object if there is a match. 
search = re.search("BCA", text) 
print("Search: ", search.group() if search else None) 
#re.findall() returns a list containing all matches. 
findall = re.findall("[0-9]", text) 
print("Findall: ", findall) 
# re.split() returns a list where the string has been split at each match. 
split = re.split(r"\s", text) 
print("Split: ", split) 
#re.sub() replaces the matches with the text of choice. 
sub = re.sub("4th", "Third", text) 
print("Sub: ", sub)

Show Output

Match:  Hello
Search:  None
Findall:  []
Split:  ['Hello', 'There!']
Sub:  Hello There!

Try it out

import re 
text = "Hello There!" 
#re.match() tries to match a pattern at the beginning of the string. 
match = re.match("Hello", text) 
print("Match: ", match.group() if match else None) 
# re.search() searches the string for a match, and returns a Match object if there is a match. 
search = re.search("BCA", text) 
print("Search: ", search.group() if search else None) 
#re.findall() returns a list containing all matches. 
findall = re.findall("[0-9]", text) 
print("Findall: ", findall) 
# re.split() returns a list where the string has been split at each match. 
split = re.split("\s", text) 
print("Split: ", split) 
#re.sub() replaces the matches with the text of choice. 
sub = re.sub("4th", "Third", text) 
print("Sub: ", sub)

Program 2: Demonstrate use of Advanced Regular Expressions for Data Validation

import re

def validate_data():
    email = input("Enter Email Addr: ")
    phone = input("Enter Mobile Number: ")
    url = input("Enter a URL: ")
    password = input("Enter Password: ")

    email_regex = r'\S+@\S+\.\S+'
    phone_regex = r'\d{10}'
    url_regex = r'https?://(www\.)?(\S+\.\S+)'
    password_regex = r'.{8,}'

    if not re.fullmatch(email_regex, email):
        print("Invalid Email Address")
    elif not re.fullmatch(phone_regex, phone):
        print("Invalid Phone")
    elif not re.fullmatch(url_regex, url):
        print("Invalid URL")
    elif not re.fullmatch(password_regex, password):
        print("Invalid Password. Minimum 8 Characters.")
    else:
        print("Data is Valid.")
validate_data()

Show Output

Enter Email Addr: example@email.net
Enter Mobile Number: 1234567890
Enter a URL: https://example.net
Enter Password: password123
Data is Valid.

Try it out

import re

def validate_data():
    email = input("Enter Email Addr: ")
    phone = input("Enter Mobile Number: ")
    url = input("Enter a URL: ")
    password = input("Enter Password: ")

    email_regex = r'\S+@\S+\.\S+'
    phone_regex = r'\d{10}'
    url_regex = r'https?://(www\.)?(\S+\.\S+)'
    password_regex = r'.{8,}'

    if not re.fullmatch(email_regex, email):
        print("Invalid Email Address")
    elif not re.fullmatch(phone_regex, phone):
        print("Invalid Phone")
    elif not re.fullmatch(url_regex, url):
        print("Invalid URL")
    elif not re.fullmatch(password_regex, password):
        print("Invalid Password. Minimum 8 Characters.")
    else:
        print("Data is Valid.")
validate_data()

Program 3: Demonstrate use of List *

my_list = [10, 20, 30, 3.142, 'Python', 'BCA']
print("Initial List: ", my_list)

print("Element at list index 0: ", my_list[0])
print("Element at list index 2: ", my_list[2])

my_list[4] = 'Java'
print("List after modifying an item: ", my_list)

my_list.append('ExamDawn')
print("List after appending an item: ", my_list)

my_list.remove('Java')
print("List after removing an item: ", my_list)

del my_list[0]
print("List after deleting an item: ", my_list)

print("Popped item: ", my_list.pop(1))
print("List after popping an item: ", my_list)

print("Index of 'BCA': ", my_list.index('BCA'))

print("Count of '3.142'", my_list.count(3.142))

print("Length of List: ", len(my_list))

my_list.reverse()
print("Reversed List: ", my_list)

my_list.clear()
print("List after clearing: ", my_list)

Show Output

Initial List:  [10, 20, 30, 3.142, 'Python', 'BCA']
Element at list index 0:  10
Element at list index 2:  30
List after modifying an item:  [10, 20, 30, 3.142, 'Java', 'BCA']
List after appending an item:  [10, 20, 30, 3.142, 'Java', 'BCA', 'ExamDawn']
List after removing an item:  [10, 20, 30, 3.142, 'BCA', 'ExamDawn']
List after deleting an item:  [20, 30, 3.142, 'BCA', 'ExamDawn']
Popped item:  30
List after popping an item:  [20, 3.142, 'BCA', 'ExamDawn']
Index of 'BCA':  2
Count of '3.142' 1
Length of List:  4
Reversed List:  ['ExamDawn', 'BCA', 3.142, 20]
List after clearing:  []

Try it out

my_list = [10, 20, 30, 3.142, 'Python', 'BCA']
print("Initial List: ", my_list)

print("Element at list index 0: ", my_list[0])
print("Element at list index 2: ", my_list[2])

my_list[4] = 'Java'
print("List after modifying an item: ", my_list)

my_list.append('ExamDawn')
print("List after appending an item: ", my_list)

my_list.remove('Java')
print("List after removing an item: ", my_list)

del my_list[0]
print("List after deleting an item: ", my_list)

print("Popped item: ", my_list.pop(1))
print("List after popping an item: ", my_list)

print("Index of 'BCA': ", my_list.index('BCA'))

print("Count of '3.142'", my_list.count(3.142))

print("Length of List: ", len(my_list))

my_list.reverse()
print("Reversed List: ", my_list)

my_list.clear()
print("List after clearing: ", my_list)

Program 4: Demonstrate use of Dictionaries *

my_dict = {'name': 'Souhrud', 'age': 19, 'city': 'Bangalore'}
print("Initial dictionary:", my_dict)
print("Value for 'name':", my_dict['name'])
print("Value for 'age':", my_dict['age'])

print("Value for 'country':", my_dict.get('country'))

print("Value for 'country' with default:", my_dict.get('country', 'India'))

my_dict['age'] = 25
print("Dictionary after modifying an item:", my_dict)

my_dict['job'] = 'Developer'
print("Dictionary after adding an item:", my_dict)

del my_dict['city']
print("Dictionary after deleting an item by key:", my_dict)

print("Popped item:", my_dict.pop('job'))
print("Dictionary after popping an item:", my_dict)

print("Keys:", list(my_dict.keys()))
print("Values:", list(my_dict.values()))
print("Items:", list(my_dict.items()))

print("Number of items:", len(my_dict))

print("'name' in dictionary:", 'name' in my_dict)
print("'city' in dictionary:", 'city' in my_dict)

my_dict2 = {'country': 'India', 'job': 'Developer'}
my_dict.update(my_dict2)
print("Dictionary after merging:", my_dict)

my_dict.clear()
print("Dictionary after clearing:", my_dict)

Show Output

Initial dictionary: {'name': 'Souhrud', 'age': 19, 'city': 'Bangalore'}
Value for 'name': Souhrud
Value for 'age': 19
Value for 'country': None
Value for 'country' with default: India
Dictionary after modifying an item: {'name': 'Souhrud', 'age': 25, 'city': 'Bangalore'}
Dictionary after adding an item: {'name': 'Souhrud', 'age': 25, 'city': 'Bangalore', 'job': 'Developer'}
Dictionary after deleting an item by key: {'name': 'Souhrud', 'age': 25, 'job': 'Developer'}
Popped item: Developer
Dictionary after popping an item: {'name': 'Souhrud', 'age': 25}
Keys: ['name', 'age']
Values: ['Souhrud', 25]
Items: [('name', 'Souhrud'), ('age', 25)]
Number of items: 2
'name' in dictionary: True
'city' in dictionary: False
Dictionary after merging: {'name': 'Souhrud', 'age': 25, 'country': 'India', 'job': 'Developer'}
Dictionary after clearing: {}

Try it out

my_dict = {'name': 'Souhrud', 'age': 19, 'city': 'Bangalore'}
print("Initial dictionary:", my_dict)
print("Value for 'name':", my_dict['name'])
print("Value for 'age':", my_dict['age'])

print("Value for 'country':", my_dict.get('country'))

print("Value for 'country' with default:", my_dict.get('country', 'India'))

my_dict['age'] = 25
print("Dictionary after modifying an item:", my_dict)

my_dict['job'] = 'Developer'
print("Dictionary after adding an item:", my_dict)

del my_dict['city']
print("Dictionary after deleting an item by key:", my_dict)

print("Popped item:", my_dict.pop('job'))
print("Dictionary after popping an item:", my_dict)

print("Keys:", list(my_dict.keys()))
print("Values:", list(my_dict.values()))
print("Items:", list(my_dict.items()))

print("Number of items:", len(my_dict))

print("'name' in dictionary:", 'name' in my_dict)
print("'city' in dictionary:", 'city' in my_dict)

my_dict2 = {'country': 'India', 'job': 'Developer'}
my_dict.update(my_dict2)
print("Dictionary after merging:", my_dict)

my_dict.clear()
print("Dictionary after clearing:", my_dict)

Program 5: Create SQLite Database and Perform Operations on tables *

import sqlite3

def display_rows(cursor):
    rows = cursor.fetchall()
    for row in rows:
        print(row)

conn = sqlite3.connect('employee.db')
cursor = conn.cursor()

cursor.execute("DROP TABLE IF EXISTS emp")

cursor.execute("""
CREATE TABLE emp
(empno INTEGER PRIMARY KEY,
empname TEXT,
salary REAL,
department TEXT)""")


print("Table Created")
cursor.execute("INSERT INTO emp VALUES (1 , 'Souhrud' , 50000 , 'IT')")
cursor.execute("INSERT INTO emp VALUES (2 , 'John' , 35000 , 'Sales')")
conn.commit()
print("Records inserted")


cursor.execute("SELECT * from emp")
print("Records in the table:")
display_rows(cursor)
cursor.execute("UPDATE emp SET salary = 100000 WHERE empno = 1")
conn.commit()
print("Record Updated")

cursor.execute("SELECT * from emp")
print("Records in the table after update:")
display_rows(cursor)

cursor.execute("DROP TABLE emp")
conn.commit()
print("Table Dropped")

conn.close()

Try it out

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Program 6: Create GUI using Tkinter Module

import tkinter as tk
from tkinter import messagebox, ttk

def submit():
    messagebox.showinfo("Submitted", "Form Submitted Successfully.")

root = tk.Tk()
root.geometry("300x300")

root.title("Student Registration Form")

tk.Label(root, text="Student Name").grid(row=0)
tk.Label(root, text="Phone Number").grid(row=1)
tk.Label(root, text="Email Address").grid(row=2)
tk.Label(root, text="Residential Address").grid(row=3)
tk.Label(root, text="Gender").grid(row=4)
tk.Label(root, text="Course").grid(row=5)


name_entry = tk.Entry(root)
phone_entry = tk.Entry(root)
email_entry = tk.Entry(root)
address_text = tk.Text(root, width=20, height=5)

name_entry.grid(row=0, column=1)
phone_entry.grid(row=1, column=1)
email_entry.grid(row=2, column=1)
address_text.grid(row=3, column=1)

gender_var = tk.StringVar()
tk.Radiobutton(root, text="Male", variable=gender_var, value="Male").grid(row=4,column=1, sticky='w')
tk.Radiobutton(root, text="Female", variable=gender_var, value="Female").grid(row=4,column=1, sticky='e')

course_var = tk.StringVar()
course_combobox = ttk.Combobox(root, textvariable=course_var)
course_combobox['values'] = ('BCA','BBA','BCOM')
course_combobox.grid(row=5, column=1)

tk.Button(root, text="Submit", command=submit).grid(row=10,column=1)

root.mainloop()

Show Output

Program 7: Demonstrate exceptions in Python *

try: 
    num = int(input("Enter a number: ")) 
except ValueError: 
    print("That's not a valid number!") 
else: 
    print(f"You entered {num}.") 
finally: 
    print("This statement is always executed.")

Show Output

Enter a number: 5
You entered 5.
This statement is always executed.

Try it out

try: 
    num = int(input("Enter a number: ")) 
except ValueError: 
    print("That's not a valid number!") 
else: 
    print(f"You entered {num}.") 
finally: 
    print("This statement is always executed.")

Program 8: Drawing Line Chart and Bar Chart using Matplotlib *

Line Chart

import matplotlib.pyplot as plt

x = [1,2,3,4,5]
y = [1,4,9,16,25]

plt.plot(x,y)

plt.title("Simple Line Graph")
plt.xlabel("Number")
plt.ylabel("Square")

plt.show()

plt.savefig("simple_line_graph.png")

Try it out

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Bar Chart

import matplotlib.pyplot as plt


courses = ["BCA","BCOM", "BBA", "BSc", "BA" ]
count = [120, 180, 60, 30, 80]
plt.bar(courses, count, color="maroon", width=0.4)

plt.xlabel("Courses")
plt.ylabel("Count")
plt.title("Count of Students in Different Courses")

plt.show()

Try it out

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Program 9: Drawing Histograms and Pie Chart using Matplotlib *

Histogram

import matplotlib.pyplot as plt 
ages = [25, 22, 23, 23, 30, 31, 22, 35, 34, 56, 27, 45, 41, 19, 19, 26, 32, 33, 45, 40] 
plt.hist(ages, bins=5, edgecolor='black') 
plt.title('Ages of Customers')
plt.xlabel('Age')
plt.ylabel('Number')

plt.show()

Try it out

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Pie Chart

import matplotlib.pyplot as plt 
# Data 
languages = ['Python', 'Java', 'C++', 'JavaScript', 'C#'] 
votes = [250, 150, 100, 75, 50] 
# Create a pie chart 
plt.figure(figsize=[5,5]) 
plt.pie(votes, labels=languages, autopct='%1.1f%%') 
plt.title('Favorite Programming Languages') 
plt.show()

Try it out

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Program 10: Create array using Numpy and Perform Operations on Array

import numpy as np 
#Create two arrays 
a = np.array([1, 2, 3]) 
b = np.array([4, 5, 6]) 
#Perform arithmetic operations 
print("Addition:", a + b)
print("Subtraction:", a - b)
print("Multiplication:", a * b)
print("Division:", a / b) 
#Perform relational operations 
print("a Greater than b", a > b) 
print("a Less than b", a < b) 
print("a Equal to b:", a == b) 
print("a Not Equal to b:", a != b) 
#Perform logical operations 
print("Logical OR:", np.logical_or(a, b))
print("Logical AND:", np.logical_and(a, b))
print("Logical NOT:", np.logical_not(a)) 
#Perform aggregation functions 
print("Sum of a:", np.sum(a))
print("Max of b:", np.max(b))
print("Min of a:", np.min(a))
print("Average of b:", np.average(b))
# Perform matrix operations 
print("Matrix Addition:\n", a + b) 
print("Matrix Subtraction:\n", a - b) 
print("Matrix Multiplication (element-wise):\n", a* b) 
print("Matrix Multiplication:\n", np.matmul(a, b)) 
print("Transpose of a:\n", np.transpose(a)) 
#Perform statistical functions 
print("Standard Deviation:", np.std(a)) 
print("Variance:", np.var(a)) 
print("Median:", np.median(a))
#Reshape array 
c = a.reshape((3, 1)) 
print("Reshaped a:", c) 
#Stack arrays 
print("Horizontal Stack:\n", np.hstack((a, b))) 
print("Vertical Stack:\n", np.vstack((a, b))) 
#Split array 
d= np.array([[1, 2, 3, 4], [5, 6, 7, 8]]) 
print("Horizontal Split:\n", np.hsplit(d, 2)) 
print("Vertical Split:\n", np.vsplit(d, 2)) 
#Broadcasting 
print("Broadcasting addition:\n", a + 5)

Try it out

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Program 11: Create Data Frame from Excel Sheets using Pandas and Perform Operations on Data Frames

import pandas as pd 
#Read DataFrame from excel file 
df = pd.read_excel("emp.xlsx") 
#Data selection of single column print("Single column: \n", df[ 'Name']) 
#Data selection of double columns 
print("\nDouble columns: \n", df[['Name', 'Gender']]) 
# Select first row by index label using .loc[] 
print("\nFirst row using loc[]:\n", df.loc[0]) 
# Select first row by position using iloc[] print("\nFirst row using .iloc[]: \n", df.iloc[0]) 
#Slice the first two rows and select 'Student Name' and 'Age' columns print("The first two rows of Name and Age Columns: ") 
print(df[:2][['Name', 'Age']]) 
#Filtering based on age>30 
print("\nFiltered DataFrame (Age > 30):\n", df[df['Age'] > 30]) 
# Grouping based on Course and Age 
grouped_df = df.groupby('Gender') ['Age'].mean() 
print("\nGrouped DataFrame (based on 'Gender' and 'Age'):\n", grouped_df) 
# Sorting by index 
df_by_index= df.sort_index(ascending=False) 
print("\nDataFrame sorted by index: \n", df_by_index) 
# Sorting by values 
df_by_value = df.sort_values (by='Age') 
print("\nDataFrame sorted by 'Age' column: \n", df_by_value)

Sample Data: https://showai.undo.it/sample_data/emp.xlsx

Show Output

Double columns: 
       Name  Gender
0    Alice  Female
1      Bob    Male
2  Charlie    Male
3    Daisy  Female

First row using loc[]:
 Name           Alice
Gender        Female
Age               28
Department        HR
Name: 0, dtype: object
    Name  Age
0  Alice   28
1    Bob   35

Filtered DataFrame (Age > 30):
       Name Gender  Age Department
1      Bob   Male   35         IT
2  Charlie   Male   40    Finance

Grouped DataFrame (based on 'Gender' and 'Age'):
 Gender
Female    26.5
Male      37.5
Name: Age, dtype: float64

DataFrame sorted by index: 
       Name  Gender  Age Department
3    Daisy  Female   25  Marketing
2  Charlie    Male   40    Finance
1      Bob    Male   35         IT
0    Alice  Female   28         HR

DataFrame sorted by 'Age' column: 
       Name  Gender  Age Department
3    Daisy  Female   25  Marketing
0    Alice  Female   28         HR
1      Bob    Male   35         IT
2  Charlie    Male   40    Finance