The function print_mean() that you wrote in the previous lesson calculates an average value and prints...

The function print_mean() that you wrote in the previous lesson calculates an average value and prints it on the screen. Change this function so that instead of printing the average it returns the average.In order to calculate the sum, you won't need to form a loop; call the function column_sum() instead.

# columns are [0]title [1]year [2]rating [3]length(min) [4]genre [5]budget($mil) [6]box_office_gross($mil)
oscar_data = [
["The Shape of Water", 2017, 6.914, 123, ['sci-fi', 'drama'], 19.4, 195.243464],
["Moonlight", 2016, 6.151, 110, ['drama'], 1.5, 65.046687],
["Spotlight", 2015, 7.489, 129, ['drama', 'crime', 'history'], 20.0, 88.346473],
["Birdman", 2014, 7.604, 119, ['drama', 'comedy'], 18.0, 103.215094],
["12 Years a Slave", 2013, 7.71, 133, ['drama', 'biography', 'history'], 20.0, 178.371993],
["Argo", 2012, 7.517, 120, ['thriller', 'drama', 'biography'], 44.5, 232.324128],
["The Artist", 2011, 7.942, 96, ['drama', 'melodrama', 'comedy'], 15.0, 133.432856],
["The King\'s Speech", 2010, 7.977, 118, ['drama', 'biography', 'history'], 15.0, 414.211549],
["The Hurt Locker", 2008, 7.298, 126, ['thriller', 'drama', 'war', 'history'], 15.0, 49.230772],
["Slumdog Millionaire", 2008, 7.724, 120, ['drama', 'melodrama'], 15.0, 377.910544],
["No Country for Old Men", 2007, 7.726, 122, ['thriller', 'drama', 'crime'], 25.0, 171.627166],
["The Departed", 2006, 8.456, 151, ['thriller', 'drama', 'crime'], 90.0, 289.847354],
["Crash", 2004, 7.896, 108, ['thriller', 'drama', 'crime'], 6.5, 98.410061],
["Million Dollar Baby", 2004, 8.075, 132, ['drama', 'sport'], 30.0, 216.763646],
["The Lord of the Rings: Return of the King", 2003, 8.617, 201, ['fantasy', 'drama', 'adventure'], 94.0, 1119.110941],
["Chicago", 2002, 7.669, 113, ['musical', 'comedy', 'crime'], 45.0, 306.776732],
['A Beautiful Mind', 2001, 8.557, 135, ['drama', 'biography', 'melodrama'], 58.0, 313.542341],
["Gladiator", 2000, 8.585, 155, ['action', 'drama', 'adventure'], 103.0, 457.640427],
["American Beauty", 1999, 7.965, 122, ['drama'], 15.0, 356.296601],
["Shakespeare in Love", 1998, 7.452, 123, ['drama', 'melodrama', 'comedy', 'history'], 25.0, 289.317794],
["Titanic", 1997, 8.369, 194, ['drama', 'melodrama'], 200.0, 2185.372302],
["The English Patient", 1996, 7.849, 155, ['drama', 'melodrama', 'war'], 27.0, 231.976425],
["Braveheart", 1995, 8.283, 178, ['drama', 'war', 'biography', 'history'], 72.0, 210.409945],
["Forrest Gump", 1994, 8.915, 142, ['drama', 'melodrama'], 55.0, 677.386686],
["Schindler\'s List", 1993, 8.819, 195, ['drama', 'biography', 'history'], 22.0, 321.265768],
["Unforgiven", 1992, 7.858, 131, ['drama', 'western'], 14.4, 159.157447],
["Silence of the Lambs", 1990, 8.335, 114, ['thriller', 'crime', 'mystery', 'drama', 'horror'], 19.0, 272.742922],
["Dances with Wolves", 1990, 8.112, 181, ['drama', 'adventure', 'western'], 22.0, 424.208848],
["Driving Miss Daisy", 1989, 7.645, 99, ['drama'], 7.5, 145.793296],
["Rain Man", 1988, 8.25, 133, ['drama'], 25.0, 354.825435],
]

def column_sum(data, column):
result = 0
for row in data:
result += row[column]
return result

def column_mean(data, column):
# < write code here >

mean_score = column_mean(oscar_data, 2)
print('Average rating: {:.2f}'.format(mean_score))

mean_length = column_mean(oscar_data, 3)
print('Average length: {:.2f} min.'.format(mean_length))

mean_budget = column_mean(oscar_data, 5)
print('Average budget: ${:.2f} mil.'.format(mean_budget))

mean_gross = column_mean(oscar_data, 6)
print('Average revenue: ${:.2f} mil.'.format(mean_gross))

Solutions

Expert Solution

Code snippets are provided below the typed code.
Please refer to snippet of code to understand the indentation of code.
Output snippet is also attached at the end.

Required Function:

def column_mean(data, column):
    # returning average using column_sum() and len() functions
    return column_sum(data, column)/len(data)

Snippet:

Complete Code:

oscar_data = [
["The Shape of Water", 2017, 6.914, 123, ['sci-fi', 'drama'], 19.4, 195.243464],
["Moonlight", 2016, 6.151, 110, ['drama'], 1.5, 65.046687],
["Spotlight", 2015, 7.489, 129, ['drama', 'crime', 'history'], 20.0, 88.346473],
["Birdman", 2014, 7.604, 119, ['drama', 'comedy'], 18.0, 103.215094],
["12 Years a Slave", 2013, 7.71, 133, ['drama', 'biography', 'history'], 20.0, 178.371993],
["Argo", 2012, 7.517, 120, ['thriller', 'drama', 'biography'], 44.5, 232.324128],
["The Artist", 2011, 7.942, 96, ['drama', 'melodrama', 'comedy'], 15.0, 133.432856],
["The King\'s Speech", 2010, 7.977, 118, ['drama', 'biography', 'history'], 15.0, 414.211549],
["The Hurt Locker", 2008, 7.298, 126, ['thriller', 'drama', 'war', 'history'], 15.0, 49.230772],
["Slumdog Millionaire", 2008, 7.724, 120, ['drama', 'melodrama'], 15.0, 377.910544],
["No Country for Old Men", 2007, 7.726, 122, ['thriller', 'drama', 'crime'], 25.0, 171.627166],
["The Departed", 2006, 8.456, 151, ['thriller', 'drama', 'crime'], 90.0, 289.847354],
["Crash", 2004, 7.896, 108, ['thriller', 'drama', 'crime'], 6.5, 98.410061],
["Million Dollar Baby", 2004, 8.075, 132, ['drama', 'sport'], 30.0, 216.763646],
["The Lord of the Rings: Return of the King", 2003, 8.617, 201, ['fantasy', 'drama', 'adventure'], 94.0, 1119.110941],
["Chicago", 2002, 7.669, 113, ['musical', 'comedy', 'crime'], 45.0, 306.776732],
['A Beautiful Mind', 2001, 8.557, 135, ['drama', 'biography', 'melodrama'], 58.0, 313.542341],
["Gladiator", 2000, 8.585, 155, ['action', 'drama', 'adventure'], 103.0, 457.640427],
["American Beauty", 1999, 7.965, 122, ['drama'], 15.0, 356.296601],
["Shakespeare in Love", 1998, 7.452, 123, ['drama', 'melodrama', 'comedy', 'history'], 25.0, 289.317794],
["Titanic", 1997, 8.369, 194, ['drama', 'melodrama'], 200.0, 2185.372302],
["The English Patient", 1996, 7.849, 155, ['drama', 'melodrama', 'war'], 27.0, 231.976425],
["Braveheart", 1995, 8.283, 178, ['drama', 'war', 'biography', 'history'], 72.0, 210.409945],
["Forrest Gump", 1994, 8.915, 142, ['drama', 'melodrama'], 55.0, 677.386686],
["Schindler\'s List", 1993, 8.819, 195, ['drama', 'biography', 'history'], 22.0, 321.265768],
["Unforgiven", 1992, 7.858, 131, ['drama', 'western'], 14.4, 159.157447],
["Silence of the Lambs", 1990, 8.335, 114, ['thriller', 'crime', 'mystery', 'drama', 'horror'], 19.0, 272.742922],
["Dances with Wolves", 1990, 8.112, 181, ['drama', 'adventure', 'western'], 22.0, 424.208848],
["Driving Miss Daisy", 1989, 7.645, 99, ['drama'], 7.5, 145.793296],
["Rain Man", 1988, 8.25, 133, ['drama'], 25.0, 354.825435],
]


def column_sum(data, column):
    result = 0
    for row in data:
        result += row[column]
    return result


def column_mean(data, column):
    # returning average using column_sum() and len() functions
    return column_sum(data, column)/len(data)


# printing output
mean_score = column_mean(oscar_data, 2)
print('Average rating: {:.2f}'.format(mean_score))

mean_length = column_mean(oscar_data, 3)
print('Average length: {:.2f} min.'.format(mean_length))

mean_budget = column_mean(oscar_data, 5)
print('Average budget: ${:.2f} mil.'.format(mean_budget))

mean_gross = column_mean(oscar_data, 6)
print('Average revenue: ${:.2f} mil.'.format(mean_gross))

Code Snippet:

Output Snippet:

I hope you got the provided solution.

Thank You.

venereology answered 2 hours ago

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