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代寫(xiě)program,、代做c++,,Java程序語(yǔ)言
代寫(xiě)program,、代做c++,Java程序語(yǔ)言

時(shí)間:2024-10-26  來(lái)源:合肥網(wǎng)hfw.cc  作者:hfw.cc 我要糾錯(cuò)



Assignment 1: Web Scraping & Data Analysis
Sep 31, 2024
In this assignment, you should work with data from https://www.themoviedb.org/movie (Online Popular Movies Platform)
The Movie Database (TMDb) is a popular platform for movie enthusiasts, offering a vast collection of movies from all genres and regions. TMDb provides users with detailed information such as movie titles, release dates, cast, crew, genres, ratings, and more. It's a go- to source for finding information about both classic and upcoming films, as well as the latest in TV shows.
Everyone is interested in great movies, but with so many films released each year, how can we find the best ones? Scraping high-quality data from movie websites is crucial. In this project, we will utilize the skills we've learned with requests and regular expressions to scrape essential movie details from The Movie Database (TMDb) website, allowing us to build a comprehensive dataset for further analysis.
Task1. You are required to scrape 200 Movies from the website and save result into ‘your_name+id.csv’. This file should contain data with the following columns: (40 marks)
Title of Movie     5 marks
     Year
User Score     5 marks
5 marks
   Description
5 marks
  Director     5 marks Screenplay     5 marks
Type
Revenue     5 marks
5 marks
  
           You are free to explore data with more properties if needed.
Task2. You are required to do a data analysis on the data. What do you think is interesting about this data? Tell a story about some interesting thing you have discovered by looking at the data. (60 marks)
For example, which one is the best movie you might watch? Does the type of movie affect movie sales? Which category of movies sells the best?
Note: This is an open topic project. You are required to provide a novel topic and demonstrate your hypotheses (view points) with data analysis and figures illustrations.
The reports and running code (web scraping + data analysis) should be submitted using Jupter Notebook file.
Submission Checklist:
Yes/No Items
Jupyter Notenook code your_name+id.csv
           
Marking Guidelines
Marking Criteria
      Idea (5 marks)
    Presents a novel idea
 Clearly demonstrate your viewpoints.  Demonstrates good understanding of
the topic.
   Discussion (30 marks)
   Provide convincing arguments to your viewpoints.
 Backs up arguments with appropriate data analysis results.
 Visualize data analysis results by
 using more than 5 figures.
   Organization (20 marks)
  Use of figures to support ideas discussed in the report.
 The quality of the figures.
 These figures should be informative.
 Use of sub-titles and/or clear topic
sentences.
 Usemultiplevisualizationmethods
(line, bar, pie chart, etc, ).
   Writing Style (5 marks)
    Concise writing style
Strong scientific writing without grammatical errors.
 
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