From 7feb712f44b90e276d2bcb6b0f191febf6e3c269 Mon Sep 17 00:00:00 2001 From: Nicholas Pease Date: Thu, 18 Dec 2025 18:15:29 -0500 Subject: [PATCH] Package --- task1.py | 1 + 1 file changed, 1 insertion(+) diff --git a/task1.py b/task1.py index a197c68..c284a5d 100644 --- a/task1.py +++ b/task1.py @@ -2,6 +2,7 @@ # Nicholas Pease # I decided to try MongoD because structure of documents, which aligns closely with JSON format, where I store a majority of the data I work with in other projects. # I stored the data in this assignment in a collection of movie documents, where each document contains information about a movie, its directors, and its cast. +# Answer to part c: If we were accessing movies primarily by their years, followed by their names, I would create a compound index on the 'year' and 'movie_name' fields in the MongoDB collection. import csv import pandas as pd