--- title: "Web Scraping Excercise" author: "Akshay Kulkarni " output: pdf_document --- In this excercise we will learn how to use rvest to scrape the IMDB website for our favorite movie data. #Task 1 - Building a dataframe from full cast page of a movie of your choice and storing ONLY the cast info i.e. the Actor and their respective character name in a df. 1.Use rvest to request and store the data from the url e.g. "https://www.imdb.com/title/tt4154796/fullcredits?ref_=tt_cl_sm#cast" Write R statements to answer the following questions on the retrieved contents: . How many nodes are direct descendents of the HTML element (the actual visible content of a web page)? . What are the nodes names of the direct descendents of the ? . What is the css selector to select the characters ? #Task 2 - Building a dataframe for most popular(top 100) feature films in 2018 and generate some statistics and some plots to gain insight. Your final dataframe should contain these following columns. -Rank: The rank of the film from 1 to 100 on the list of 100 most popular feature films released in 2018. -Title: The title of the feature film. -Description: The description of the feature film. -Runtime: The duration of the feature film. -Genre: The genre of the feature film, -Rating: The IMDb rating of the feature film. after compiling your final dataframe answer the following questions. . What was the average runtime for movies in 2018 ? . Which was the leading genre for movies in 2018 ? . Explore any variable/s in your data set and generate a plot. (Give any Inference you may discover from this) . Choose another previous year i.e 2016 nd compare your results.