If one of your hobbies is to binge, then chance is you want to at least watch some sort of top movie watchlist. Good things, now it's quite easy to make such list without any complex scraping.
We will use Python with Pandas module
First you need to declare the Pandas
import pandas as pd
Then declare the url to obtain the datasets
s = 'https://datasets.imdbws.com/'
t = 'title.basics.tsv.gz'
r = 'title.ratings.tsv.gz'
Next load the dataset and join basics and ratings using its primary key, tconst.
titles = pd.read_csv((s+t), compression='gzip', sep='\t', low_memory=False)
ratings = pd.read_csv((s+r), compression='gzip', sep='\t')
rated = titles.set_index('tconst').join(ratings.set_index('tconst'))
You likely just need the title, ratings, and number of votes so we can filter the output just that.
I prefer to add number of votes above 50k since it filter out a lot of poor movies with <5 ratings to <3%.
Of course there are many new movies below that, and some nice particular movies or regional movies.
top = rated[['primaryTitle','startYear','averageRating','numVotes']][(rated.titleType=='movie')&(rated.numVotes>50000)].sort_values(by='numVotes', ascending=False)
Finally you can export the result into csv. To simplify i used ; separator as its easier for my region to detect.
top.to_csv('imdbtop50k.csv', index=False, sep=';')
That's it. you'll get roughly around 5,000 movie watch list. How many movies have you watched?