She turns suddenly and sees the fallen books.įrightened now, she walks slowly to the end of the aisle and tentatively She continues her task but suddenlyĪs the Librarian walks down the aisle, books start shooting off the shelfīehind her. She puts the books back in their proper places, she slowly gets theįeeling that she's being watched. The Librarian works her way through rows and rows of old iron shelvesĬontaining many thousands of volumes stacked from floor to ceiling. Open drawers just behind her, but the Librarian still doesn't notice. Quietly slide open, and thousands of file cards start shooting out of the She gets up and moves past another row of cabinets. Librarian continues reading completely oblivious to this strange One of the books attracts her interestĪnother eerie note is heard as one of the drawers silently slides openīehind the Librarian and hundreds of index cards start popping out. The Librarian is alone in a back room sorting books for reshelving.īehind her is the card catalogue. It follows the Librarian as she pushes her cart around the corner. Looking down on the Librarian from a vantage point high above the room. Quietly among the tables picking up books and putting them on her cart.Įverything seems completely normal and peaceful.Ī single eerie musical note signals the presence of something strange It is veryĪ slightly stout, studious looking girl in her late twenties circulates Reading lamps with green glass shades cast a People are dotted throughout the room sitting at the long oak tables In the adjacent park area, pretty hustlers andĪ few people lounge on the steps flanked by the familiar stone lions. The sun shines brightly on the classic facade of the main library at FifthĪvenue and 42nd Street. It would be much better to programmatically access the text data attached to every URL. Though we could manually navigate to each URL and copy/paste each screenplay into a file, that would be suuuuper slow and painstaking, and we would lose crucial data in the process - information that might help us automatically distinguish the title of the movie from the screenplay itself, for example. How can we actually use these URLs to get computationally tractable text data? Make an Interactive Network Visualization with BokehĮach movie title in this CSV file is paired with a URL for the screenplay. Tomotopy & Text Files (NYT Articles) - No Java required Term-Frequency Inverse Document Frequency Users’ Data: Legal & Ethical ConsiderationsĪpplication Programming Interfaces (APIs) Data Collection (Web Scraping, APIs, Social Media)
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