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In this project, I analyzed the prosper load data, studied the trends and concluded that monthly income, loan amount and borrower's rate significantly affect the prosper rating and a good predictors of delinquency.

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Camera to denote movie industry

What Happened to the Movie Industry?

Overview

What can we say about the success of a movie before it is released? Are there certain companies (Pixar?) that have found a consistent formula? Given that major films costing over $100 million to produce can still flop, this question is more important than ever to the industry. Film aficionados might have different interests. Can we predict which films will be highly rated, whether or not they are a commercial success?

About Data

The data set used in this project contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue.

Findings

  • It was gathered that movies like Jurassic World 32.985763, Mad Max: Fury Road, Interstellar, etc are well know by the people. However, this does not relate to higher rating nor increase in profit. Instead, movies like Pink Floyd: Pulse, Queen - Rock Montreal, The Art of Flight, The Shawshank Redemption are not popularly known but are highly rated.
  • Also, it was established that the duration of a movie, day, month and year of release of a movie affect its popularity and most importantly, profit.
  • Lastly, It is a good thing to note the upward trend in the film industry over the years.

Recommendations

  • The best day of the week to release a movie is Wednesday
  • The best month of the year to release a movie is Wednesday
  • That the future is bright for the film industry

Limitations:

  • The number of rows with misssing values are to many (2199 after dropping extraneous columns) and this reduced the total number of available data.
  • Data on the release time would have been helpful in determining when people normally have time to see movies.
  • Having a single (most appropriate class) for genres would have made it easy to determine which genre of movies are highly rated. Read more

About

In this project, I analyzed the prosper load data, studied the trends and concluded that monthly income, loan amount and borrower's rate significantly affect the prosper rating and a good predictors of delinquency.

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