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1. Read a list of mobile apps from a file named "Apps.txt" and store them in a Python list of dictionaries. Apps.txt: WhatsApp, Communication, 4.7, Free Instagram, Social Media, 4.8, Free Candy Crush Saga, Puzzle, 4.5, Free Google Maps, Navigation, 4.6, Free Spotify, Music, 4.9, Freemium Zoom, Business, 4.4, Freemium 1. Output all the mobile apps in your list. 2. Output all apps that are categorized as games. 3. Output all apps with a rating higher than 4.7. 4. Calculate the average user rating of all apps in your list. 5. Create a histogram of the app categories. Each element in the histogram should represent the count of apps in a specific category. 6. Take all the apps in "Apps.txt" and store them in a Python set of tuples where each tuple represents (app title, category). 7. Output all unique pricing models (e.g., Free, Freemium) among the apps. 8. Output the total number of entries in your set.

1. Read a list of mobile apps from a file named "Apps.txt" and store them in a Python list of dictionaries. Apps.txt: WhatsApp, Communication, 4.7, Free Instagram, Social Media, 4.8, Free Candy Crush Saga, Puzzle, 4.5, Free Google Maps, Navigation, 4.6, Free Spotify, Music, 4.9, Freemium Zoom, Business, 4.4, Freemium 1. Output all the mobile apps in your list. 2. Output all apps that are categorized as games. 3. Output all apps with a rating higher than 4.7. 4. Calculate the average user rating of all apps in your list. 5. Create a histogram of the app categories. Each element in the histogram should represent the count of apps in a specific category. 6. Take all the apps in "Apps.txt" and store them in a Python set of tuples where each tuple represents (app title, category). 7. Output all unique pricing models (e.g., Free, Freemium) among the apps. 8. Output the total number of entries in your set.

Database System Concepts
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
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1. Read a list of mobile apps from a file named "Apps.txt" and store them in a Python list of dictionaries. Apps.txt: WhatsApp, Communication, 4.7, Free Instagram, Social Media, 4.8, Free Candy Crush Saga, Puzzle, 4.5, Free Google Maps, Navigation, 4.6, Free Spotify, Music, 4.9, Freemium Zoom, Business, 4.4, Freemium 1. Output all the mobile apps in your list. 2. Output all apps that are categorized as games. 3. Output all apps with a rating higher than 4.7. 4. Calculate the average user rating of all apps in your list. 5. Create a histogram of the app categories. Each element in the histogram should represent the count of apps in a specific category. 6. Take all the apps in "Apps.txt" and store them in a Python set of tuples where each tuple represents (app title, category). 7. Output all unique pricing models (e.g., Free, Freemium) among the apps. 8. Output the total number of entries in your set.
Transcribed Image Text:1. Read a list of mobile apps from a file named "Apps.txt" and store them in a Python list of dictionaries. Apps.txt: WhatsApp, Communication, 4.7, Free Instagram, Social Media, 4.8, Free Candy Crush Saga, Puzzle, 4.5, Free Google Maps, Navigation, 4.6, Free Spotify, Music, 4.9, Freemium Zoom, Business, 4.4, Freemium 1. Output all the mobile apps in your list. 2. Output all apps that are categorized as games. 3. Output all apps with a rating higher than 4.7. 4. Calculate the average user rating of all apps in your list. 5. Create a histogram of the app categories. Each element in the histogram should represent the count of apps in a specific category. 6. Take all the apps in "Apps.txt" and store them in a Python set of tuples where each tuple represents (app title, category). 7. Output all unique pricing models (e.g., Free, Freemium) among the apps. 8. Output the total number of entries in your set.
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