__  __            _        _____        _           _____
 |  \/  |          (_)      |  __ \      | |         / ____|
 | \  / | _____   ___  ___  | |  | | __ _| |_ __ _  | (___   ___ _ __ __ _ _ __   ___ _ __
 | |\/| |/ _ \ \ / / |/ _ \ | |  | |/ _` | __/ _` |  \___ \ / __| '__/ _` | '_ \ / _ \ '__|
 | |  | | (_) \ V /| |  __/ | |__| | (_| | || (_| |  ____) | (__| | | (_| | |_) |  __/ |
 |_|  |_|\___/ \_/ |_|\___| |_____/ \__,_|\__\__,_| |_____/ \___|_|  \__,_| .__/ \___|_|
                                                                          |_|

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Overview

-The Movie Data Scraper is a Python-based program designed to process large IMDb datasets and generate customized Excel reports. -filters movies and TV series based on various criteria, such as ratings, genres, languages, and more.

  ______         _                       
 |  ____|       | |                      
 | |__ ___  __ _| |_ _   _ _ __ ___  ___ 
 |  __/ _ \/ _` | __| | | | '__/ _ \/ __|
 | | |  __/ (_| | |_| |_| | | |  __/\__ \
 |_|  \___|\__,_|\__|\__,_|_|  \___||___/     

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Dataset Processing - Handles large IMDb datasets, including:

title.basics.tsv for general title information.
title.ratings.tsv for ratings and votes.
title.akas.tsv for alternate titles and languages.

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Interactive Filtering

Filter by rating (e.g., movies with a minimum rating of 8.0).
Filter by genre (e.g., Comedy, Action).
Filter by language (e.g., English, Spanish).

#These variables must be modified in the code.

Exclude "vintage" films older than a specified year. The default is 1960.
Exclude movies or TV series with fewer than a specified number of votes.

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User-Specific Exclusions

-Excludes titles that the user has already watched based on user-defined Excel files. -Outputs two separate Excel files:

filtered_movies.xlsx: Contains filtered movies.
filtered_tvseries.xlsx: Contains filtered TV series.

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Optimized Column Presentation

-Removes unnecessary columns and reorders key columns, placing tconst, titleType, startYear, and endYear at the end.

 _____                               _     _ _            
|  __ \                             (_)   (_) |           
| |__) | __ ___ _ __ ___  __ _ _   _ _ ___ _| |_ ___  ___
|  ___/ '__/ _ \ '__/ _ \/ _` | | | | / __| | __/ _ \/ __|
| |   | | |  __/ | |  __/ (_| | |_| | \__ \ | ||  __/\__ \
|_|   |_|  \___|_|  \___|\__, |\__,_|_|___/_|\__\___||___/
                            | |                           
                            |_|

-Python 3.8 or higher. -Virtual environment recommended for dependency management. -Required Python packages pandas openpyxl

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Usage

1. Prepare the Datasets

2. Place the IMDb datasets (.tsv files) in the datasets/ folder. Ensure the required datasets are available:

   title.basics.tsv title.ratings.tsv title.akas.tsv

• These datasets are distributed for non-Commercial use on the IMDB website.

3. Set Up Watched Lists -Add user-specific watched lists (Excel files) to the usrdata// folder. -Example:

   cole_watched_movies.xlsx for movies. cole_watched_tvseries.xlsx for TV series.

4. Run the Program -Execute the program from the command line:

   python src/main.py

5. Follow Interactive Prompts The program will guide you through various filtering options, such as:

   Minimum rating (e.g., 8.0) Genre (e.g., Comedy, Action) Language (e.g., English, Spanish)

6. Output The program generates two Excel files in the outputs/ folder: