1. 1. Calculate the sum of 10.8, 12.2 and 0.2, store it in the variable total, then display total's value.
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3. 2. Evaluate the expressions 4**3**2, (4**3)**2 and 4**(3**2). Are any of the parentheses redundant?
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5. 3. Use float to convert '6.2' (a string) to a floating-point value. Multiply the value by 3.3 and show the answers
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7. 4.For the value 47, 95, 88, 73 and 84 calculate the minimum and maximum.
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9. 5. Write a Python program to calculate a dog's age in a dog's years. Note: For the first two years, a dog year is equal to 10.5 human years. After that, each dog year equals 4 human years. Expected Output:
10. Input a dog's age in human years: 15
    The dog's age in dog's years is 73
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12. 6.Write a Python program to find the median of three values. Expected Output:
13. Input first number: 15
    Input second number: 26
    Input third number: 29
    The median is 26.0
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15. 7.Write a Pandas program to select the rows the score is between 15 and 20 (inclusive). Sample Python dictionary data and list labels:
    exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'], 'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
    'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
    'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
    labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
    Expected Output:
    Rows where score between 15 and 20 (inclusive):
       attempts   name   qualify   score
    c      2     Katherine yes      16.5
    f      3     Michael    yes       20.0
    j      1     Jonas       yes       19.0
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17. 8.Write a Pandas program to calculate the sum of the examination attempts by the students.
18. Sample DataFrame: exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'], 'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19], 'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1], 'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']} labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
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20. 9.Write a Pandas program to sort the data frame first by 'name' in descending order, then by 'score' in ascending order.
21. Sample DataFrame: exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'], 'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19], 'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1], 'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']} labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'] Values for each column will be: name : 'Suresh', score: 15.5, attempts: 1, qualify: 'yes', label: 'k'
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23. 10.Write a Python program to create the multiplication table (from 1 to 10) of a number. Expected Output:
     
24. Input a number: 6
    6 x 1 = 6
    6 x 2 = 12
    6 x 3 = 18
    6 x 4 = 24
    6 x 5 = 30
    6 x 6 = 36
    6 x 7 = 42
    6 x 8 = 48
    6 x 9 = 54
    6 x 10 = 60
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