The first function you will write and test is the clean_data function. The function is described in the starter code in a function header comment above the function. Here is the function: def clean_data(list, x): #TODO: write your code here pass Take a look at the first few lines of the data file: A 83 140 228 286 426 612 486 577 836 0 0 Aaliyah 0 0 0 0 0 0 0 0 0 380 215 Aaron 193 208 218 274 279 232 132 36 32 31 41 Each line is a baby name followed by how popular the name was in 11 different years. Each number is a ranking, so Aaron was 193th most popular name in 1900 and 41st most popular name in 2000. The lower the number, the more popular the name. However, if the name was not popular enough to make the list in a particular year, a zero was recorded. If we plot the data as is, a name that was so unpopular that it didn’t make the list (ranked 0) will appear most popular (since lower means more popular). Therefore, we need to clean up the data a bit in order for it to make sense. The function clean_data has two parameters. The first parameter is a list (e.g. a list of rankings by year for a particular baby name). The second parameter is a value x. The function will do in-place modification of the parameter list and replace all zeros with the value x. You will write this function generally. Here are three of the cases you should test: # test 1 # before data is cleaned list1 = [0, 4, 3, 2, 0, 6, 7, 8, 3, 0, 7, 7, 8, 3, 0] x1 = 5 # after data is cleaned list1 = [5, 4, 3, 2, 5, 6, 7, 8, 3, 5, 7, 7, 8, 3, 5] # test 2 # before data is cleaned list2 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] x2 = 10001 # after data is cleaned list2 = [10001, 10001, 10001, 10001, 10001, 10001, 10001, 10001, 10001, 10001, 10001]

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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The first function you will write and test is the clean_data function. The function is described in the starter code in a function header comment above the function. Here is the function:

def clean_data(list, x):

#TODO: write your code here

pass

Take a look at the first few lines of the data file:

A 83 140 228 286 426 612 486 577 836 0 0

Aaliyah 0 0 0 0 0 0 0 0 0 380 215

Aaron 193 208 218 274 279 232 132 36 32 31 41

Each line is a baby name followed by how popular the name was in 11 different years. Each number is a ranking, so Aaron was 193th most popular name in 1900 and 41st most popular name in 2000. The lower the number, the more popular the name. However, if the name was not popular enough to make the list in a particular year, a zero was recorded. If we plot the data as is, a name that was so unpopular that it didn’t make the list (ranked 0) will appear most popular (since lower means more popular). Therefore, we need to clean up the data a bit in order for it to make sense.

The function clean_data has two parameters. The first parameter is a list (e.g. a list of rankings by year for a particular baby name). The second parameter is a value x. The function will do in-place modification of the parameter list and replace all zeros with the value x.

You will write this function generally. Here are three of the cases you should test:

# test 1

# before data is cleaned

list1 = [0, 4, 3, 2, 0, 6, 7, 8, 3, 0, 7, 7, 8, 3, 0]

x1 = 5

# after data is cleaned

list1 = [5, 4, 3, 2, 5, 6, 7, 8, 3, 5, 7, 7, 8, 3, 5]

# test 2

# before data is cleaned

list2 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

x2 = 10001

# after data is cleaned

list2 = [10001, 10001, 10001, 10001, 10001, 10001, 10001, 10001, 10001, 10001, 10001]

# test 3

# before data is cleaned

list3 = [857, 797, 972, 883, 0, 0, 0, 0, 0, 0, 0]

x3 = 1113

# after data is cleaned

list3 = [857, 797, 972, 883, 1113, 1113, 1113, 1113, 1113, 1113, 1113]

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