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MovieLensProject.html - Project - MovieLens Data Analysis¶...

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Project - MovieLens Data AnalysisThe GroupLens Research Project is a research group in the Department of ComputerScience and Engineering at the University of Minnesota. The data is widely used forcollaborative filtering and other filtering solutions. However, we will be using thisdata to act as a means to demonstrate our skill in using Python to “play” with data.Objective:To implement the techniques learnt as a part of the course.Datasets Information:rating.csv:It contains information on ratings given by the users to a particularmovie.user id: id assigned to every usermovie id: id assigned to every movierating: rating given by the usertimestamp: Time recorded when the user gave a ratingmovie.csv:File contains information related to the movies and their genre.movie id: id assigned to every moviemovie title: Title of the movierelease date: Date of release of the movieAction: Genre containing binary values (1 - for action 0 - not action)Adventure: Genre containing binary values (1 - for adventure 0 - notadventure)Animation: Genre containing binary values (1 - for animation 0 - notanimation)Children’s: Genre containing binary values (1 - for children's 0 - not children's)Comedy: Genre containing binary values (1 - for comedy 0 - not comedy)Crime: Genre containing binary values (1 - for crime 0 - not crime)Documentary: Genre containing binary values (1 - for documentary 0 - notdocumentary)Drama: Genre containing binary values (1 - for drama 0 - not drama)Fantasy: Genre containing binary values (1 - for fantasy 0 - not fantasy)Film-Noir: Genre containing binary values (1 - for film-noir 0 - not film-noir)Horror: Genre containing binary values (1 - for horror 0 - not horror)Musical: Genre containing binary values (1 - for musical 0 - not musical)Mystery: Genre containing binary values (1 - for mystery 0 - not mystery)Romance: Genre containing binary values (1 - for romance 0 - not romance)Sci-Fi: Genre containing binary values (1 - for sci-fi 0 - not sci-fi)Thriller: Genre containing binary values (1 - for thriller 0 - not thriller)War: Genre containing binary values (1 - for war 0 - not war)Western: Genre containing binary values (1 - for western - not western)user.csv:It contains information of the users who have rated the movies.user id: id assigned to every userage: Age of the usergender: Gender of the useroccupation: Occupation of the userzip code: Zip code of the usePlease provide your insights wherever necessary.Learning Outcomes:Exploratory Data AnalysisVisualization using PythonPandas – groupby, mergingDomainInternet and EntertainmentNote that the project will need you to apply the concepts of groupby andmerging extensively.
1. Import the necessary packages - 2.5 marksIn [1]:import numpy as npimport pandas as pdimport seaborn as snsimport matplotlib.pyplot as plt2. Read the 3 datasets into dataframes - 2.5 marksIn [2]:pd1 = pd.read_csv("data.csv") #Importing the data.csv filepd2 = pd.read_csv("item.csv") #Importing the item.csv filepd3 = pd.read_csv("user.csv") #Importig the user.csv file

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Term
Winter
Professor
N/A
Tags
Horror film, Music genre

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