Project overview
In this project, you’ll assume the role of a data analyst tasked with scraping movie data from IMDb using R. You’ll extract details like titles, years, runtimes, genres, ratings, and votes for the top 30 movies released between March and July 2020.
Applying your web scraping skills, you’ll use packages like rvest and dplyr to load the webpage, find the right CSS selectors, and extract the desired information. You’ll also practice data cleaning by handling missing values. Finally, you’ll visualize the relationship between user ratings and number of votes using ggplot2.
Objective: Use R to scrape and analyze IMDb movie data, uncovering trends in ratings and votes to build data extraction, manipulation and visualization skills for real-world applications.
Key skill required
To complete this project, it's recommended to build these foundational skills in R
- Understanding the structure of webpages using HTML to locate desired data
- Defining the basics of web scraping to extract data from websites
- Using CSS selectors to precisely extract specific webpage elements
- Implementing web scraper tools in R to automate data extraction from websites
Projects steps
Step 1: Introduction
Step 2: Loading the Web Page
Step 3: String Manipulation Reminder
Step 4: Setting down a strategy
Step 5: Extracting Elements from the Header
Step 6: Extracting the Movies' Features
Step 7: Extracting the Movies' Ratings
Step 8: Extracting the Movies' Votes
Step 9: Dealing with Missing Values
Step 10: Putting It All Together and Visualizing
Step 11: Next Steps
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