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Hollywood movie analysis to identify the main driver of growth . We used a CSV file with over 45,000 films on which we performed data cleaning, data visualization, and statistical analysis.

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KWASSI09/hollywood_vc

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Hollywood_vc

In this project, we analysed Movies made in the USA between 2000 and 2020, focusing on various factors of their international successes. Elements of the study include film genre, profit, directors, runtime, public rating, and fan reviews, on which we performed correlation and interdependence analyses. We also analysed what makes films successful both in terms of ratings and profitability to generate valuable insights for anyone interested in entering the cinema world or even those who already work in the sector.

A Google search for Box Office Data Analysis revealed a public dataset that contains the raw data we used: Kaggle compiled the ratings and metadata of over 45,000 movies in their Movies dataset, from which we used the TMDB 5000 Movie Dataset.csv.zip file.

The questions we answered are the following:

The questions we answered are the following:

  1. Do movies become profitable with a longer runtime?
  2. Are different genres more profitable than other genres?
  3. Does the runtime of the film affect the average vote?
  4. Does the genre of a film determine or affect its average vote and runtime?
  5. Do fan reviews by genre affect global gross revenue?
  6. Are there directors who are more favorites, how good are the films they have directed so far and their career in general?
  7. Does the film release time affect the profitability of the film?

Project Members:

. Kouamé Kouassi
. Ruchi Sharma
. Shola Daropale
. Marcus William Garnham

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Hollywood movie analysis to identify the main driver of growth . We used a CSV file with over 45,000 films on which we performed data cleaning, data visualization, and statistical analysis.

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