In Curious-Joe/HollywoodApp2.0: Explore Knn with Hollywood Movies

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HollywoodMovies2.0

HollywoodMovies2.0 is a Shiny app that has been re-built using golem framework. Among many other benefits, golem builds a Shiny app as an R package thus it's quite easy to ensure the robustness of the application. Learn more here about golem.

The primary goal of this HollywoodMovies2.0 is to use Shiny to achieve two things:

• Interactively explore the data, and
• Enabling user to interact with an algorithm: K-Nearest Neighbors (KNN) to have a better understanding of the data and the KNN model.

Description of the App

This application has three tabs. The main contents are presented in the tabs. Other than the tabs, the sidebar serves two purposes:

• Works as a tab navigation panel,
• Provides users a way to select movie genre(s) that they would like to explore.

Here's a brief summary about what tasks can be performed in each of the tabs:

Summary:

• Top 4 boxes gives a summary of Highest Grossing and Highest Profit generating movie title and director name,
• The first bar plot shows yearly total movie production numbers. Users can zoom in on this plot and see the zoomed-in plot on right,
• The second plot bar is the zoomed-in plot,
• The boxes at the bottom provide median value of Gross Earning, Gross Budget, Gross Profit, and User Rating of the movies selected by the users. The color of the boxes represents a comparison between the overall performance of all movies across all genres vs the performance of the movies from the genre selected by the user.

Bivariate Relations:

• The plot shows a scatter plot for the two variables selected by the users using the selectors on the right pane. Users can select any number of points on this plot by using a mouse. Detail data of the selected points are shown in the table below,
• Right below the selector panes users get a summary statistics of the variables chosen,
• A data table showing detail about the points selected by the user on the scatter plot.

Clustering Model:

• The left pane provides users with selectors to select a subset of movies. The maximum is set fixed at 200 movies to make sure faster performance,
• Users can select two variables of their choice to run clustering. The total number of variables are set fixed at 2 to make sure a 2D plot can be drawn to show the clusters,
• Users can select optimum numbers of clusters to create based on looking at the Elbow Plot,
• Right pane shows the clusters with the ID of the clusters and row number of the movies,
• The data table at the bottom shows the movie details along with their cluster numbers. Filter the movies based on cluster and see the actual data of the movies.

Installation

If you are interested you can install this application as an R library.

# install.packages("remotes")
remotes::install_github("Curious-Joe/HollywoodApp2.0")
# run the shiny app
HollywoodMovies2.0::run_app()

App Demo

A live demo of this application is available here on the shinyapp.io platform.

Curious-Joe/HollywoodApp2.0 documentation built on Dec. 17, 2021, 3:09 p.m.