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Web-scraping for data from Cheap-shark site to analyse the lowest prized games on sale

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Data534 Final Project

R-CMD-check

Overview

This package is designed to allow users to more easily query the Cheap Shark API which collects information on current PC game deals. This API has a lot of information available, but most users may not be interested in all of the data available. This package is not exhaustive, but is intended to give users some useful custom functions that will allow them to access interesting consumer information quickly and easily.

  • get_active_stores() returns data frame on the current actively monitored PC game vendors and stores
  • get_game_deals_df() returns data frame with various game price information by store under certain price threshold
  • get_game_reviews_df() returns data frame with game titles and ratings from a particular store
  • get_deals_by_store_df() returns a dataframe of all game deals in a particular store regardless of price
  • response() takes multiple user inputs and returns a graph based on user choices. Designed to show various top 10 functionalities that were considered to be of interest to the average consumer.

You can learn more about these in `vignette("PcGameDeals")

##Installation

The easiest way to get PCGameDeals is to simply install in your console. install.packages("dplyr") library(devtools) install_github("DishaDH123/pcgamedeals")

##Usage

We have to call the response function to use this package. Once we call the response function, we can see the below workflow:

First the user is asked to choose from the given list of stores and is prompted to enter the store ID. First output

Once the user types in the store ID, he is asked to choose from 3 options. On choosing option 1, the user is asked to enter a budget. A graph with the top 10 games within the specified budget is displayed. Second output

On choosing option 2, the user is displayed with the top 10 games by deal rating Third output

On choosing option 3, the user is asked to enter the percentage savings, and the graph showing top 10 games within the specified savings is displayed. Fourth output


Link needs to be updated to our project once we are ready

Please note that this project is released with a Contributor Code of Conduct.

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Web-scraping for data from Cheap-shark site to analyse the lowest prized games on sale

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